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API Reference

Table of Contents

  1. Device Models
  2. Decision Models
  3. Emulation Models
  4. Service Models
  5. Simulation Models
  6. Variables
  7. Constraints
  8. Parameters

Device Models

List of structures and methods for Device models

PowerSimulations.DeviceModel — Type
DeviceModel(
+    ::Type{D},
+    ::Type{B},
+    feedforwards::Vector{<:AbstractAffectFeedforward}
+    use_slacks::Bool,
+    duals::Vector{DataType},
+    services::Vector{ServiceModel}
+    attributes::Dict{String, Any}
+)

Establishes the model for a particular device specified by type. Uses the keyword argument feedforward to enable passing values between operation model at simulation time

Arguments

  • ::Type{D} where D<:PSY.Device: Power System Device Type
  • ::Type{B} where B<:AbstractDeviceFormulation: Abstract Device Formulation
  • feedforward::Array{<:AbstractAffectFeedforward} = Vector{AbstractAffectFeedforward}() : use to pass parameters between models
  • use_slacks::Bool = false : Add slacks to the device model. Implementation is model dependent and not all models feature slacks
  • duals::Vector{DataType} = Vector{DataType}(): use to pass constraint type to calculate the duals. The DataType needs to be a valid ConstraintType
  • time_series_names::Dict{Type{<:TimeSeriesParameter}, String} = get_default_time_series_names(D, B) : use to specify time series names associated to the device`
  • attributes::Dict{String, Any} = get_default_attributes(D, B) : use to specify attributes to the device

Example

thermal_gens = DeviceModel(ThermalStandard, ThermalBasicUnitCommitment)
source

Formulations

Refer to the Formulations Page for each Abstract Device Formulation.

Problem Templates

Refer to the Problem Templates Page for available ProblemTemplates.

Problem Templates

Refer to the Problem Templates Page for available ProblemTemplates.

  + 

Service Models

List of structures and methods for Service models

PowerSimulations.ServiceModel — Type

Establishes the model for a particular services specified by type. Uses the keyword argument use_service_name to assign the model to a service with the same name as the name in the template. Uses the keyword argument feedforward to enable passing values between operation model at simulation time

Arguments

-::Type{D}: Power System Service Type -::Type{B}: Abstract Service Formulation

Accepted Key Words

  • feedforward::Array{<:AbstractAffectFeedforward} : use to pass parameters between models
  • use_service_name::Bool : use the name as the name for the service

Example

reserves = ServiceModel(PSY.VariableReserve{PSY.ReserveUp}, RangeReserve)

source

Decision Models

PowerSimulations.DecisionModel — Type
DecisionModel{M}(
+    template::ProblemTemplate,
+    sys::PSY.System,
+    jump_model::Union{Nothing, JuMP.Model}=nothing;
+    kwargs...) where {M<:DecisionProblem}

Build the optimization problem of type M with the specific system and template.

Arguments

  • ::Type{M} where M<:DecisionProblem: The abstract operation model type
  • template::ProblemTemplate: The model reference made up of transmission, devices, branches, and services.
  • sys::PSY.System: the system created using Power Systems
  • jump_model::Union{Nothing, JuMP.Model}: Enables passing a custom JuMP model. Use with care
  • name = nothing: name of model, string or symbol; defaults to the type of template converted to a symbol.
  • optimizer::Union{Nothing,MOI.OptimizerWithAttributes} = nothing : The optimizer does not get serialized. Callers should pass whatever they passed to the original problem.
  • horizon::Int = UNSET_HORIZON: Manually specify the length of the forecast Horizon
  • warm_start::Bool = true: True will use the current operation point in the system to initialize variable values. False initializes all variables to zero. Default is true
  • system_to_file::Bool = true:: True to create a copy of the system used in the model.
  • initialize_model::Bool = true: Option to decide to initialize the model or not.
  • initialization_file::String = "": This allows to pass pre-existing initialization values to avoid the solution of an optimization problem to find feasible initial conditions.
  • deserialize_initial_conditions::Bool = false: Option to deserialize conditions
  • export_pwl_vars::Bool = false: True to export all the pwl intermediate variables. It can slow down significantly the build and solve time.
  • allow_fails::Bool = false: True to allow the simulation to continue even if the optimization step fails. Use with care.
  • optimizer_solve_log_print::Bool = false: Uses JuMP.unset_silent() to print the optimizer's log. By default all solvers are set to MOI.Silent()
  • detailed_optimizer_stats::Bool = false: True to save detailed optimizer stats log.
  • calculate_conflict::Bool = false: True to use solver to calculate conflicts for infeasible problems. Only specific solvers are able to calculate conflicts.
  • direct_mode_optimizer::Bool = false: True to use the solver in direct mode. Creates a JuMP.direct_model.
  • store_variable_names::Bool = false: to store variable names in optimization model. Decreases the build times.
  • rebuild_model::Bool = false: It will force the rebuild of the underlying JuMP model with each call to update the model. It increases solution times, use only if the model can't be updated in memory.
  • initial_time::Dates.DateTime = UNSET_INI_TIME: Initial Time for the model solve.
  • time_series_cache_size::Int = IS.TIME_SERIES_CACHE_SIZE_BYTES: Size in bytes to cache for each time array. Default is 1 MiB. Set to 0 to disable.

Example

template = ProblemTemplate(CopperPlatePowerModel, devices, branches, services)
+OpModel = DecisionModel(MockOperationProblem, template, system)
source
PowerSimulations.DecisionModel — Method
DecisionModel(
+    ::Type{M<:PowerSimulations.DecisionProblem},
+    template::ProblemTemplate,
+    sys::System
+) -> DecisionModel
+DecisionModel(
+    ::Type{M<:PowerSimulations.DecisionProblem},
+    template::ProblemTemplate,
+    sys::System,
+    jump_model::Union{Nothing, JuMP.Model};
+    kwargs...
+) -> DecisionModel
+

Build the optimization problem of type M with the specific system and template

Arguments

  • ::Type{M} where M<:DecisionProblem: The abstract operation model type
  • template::ProblemTemplate: The model reference made up of transmission, devices, branches, and services.
  • sys::PSY.System: the system created using Power Systems
  • jump_model::Union{Nothing, JuMP.Model} = nothing: Enables passing a custom JuMP model. Use with care.

Example

template = ProblemTemplate(CopperPlatePowerModel, devices, branches, services)
+problem = DecisionModel(MyOpProblemType, template, system, optimizer)
source
PowerSimulations.DecisionModel — Method
DecisionModel(
+    directory::AbstractString,
+    optimizer::MathOptInterface.OptimizerWithAttributes;
+    jump_model,
+    system
+) -> Any
+

Construct an DecisionProblem from a serialized file.

Arguments

  • directory::AbstractString: Directory containing a serialized model
  • jump_model::Union{Nothing, JuMP.Model} = nothing: The JuMP model does not get serialized. Callers should pass whatever they passed to the original problem.
  • optimizer::Union{Nothing,MOI.OptimizerWithAttributes} = nothing: The optimizer does not get serialized. Callers should pass whatever they passed to the original problem.
  • system::Union{Nothing, PSY.System}: Optionally, the system used for the model. If nothing and systofile was set to true when the model was created, the system will be deserialized from a file.
source
PowerSimulations.build! — Method
build!(
+    model::DecisionModel;
+    output_dir,
+    recorders,
+    console_level,
+    file_level,
+    disable_timer_outputs
+)
+

Build the Decision Model based on the specified DecisionProblem.

Arguments

  • model::DecisionModel{<:DecisionProblem}: DecisionModel object
  • output_dir::String: Output directory for results
  • recorders::Vector{Symbol} = []: recorder names to register
  • console_level = Logging.Error:
  • file_level = Logging.Info:
  • disable_timer_outputs = false : Enable/Disable timing outputs
source
PowerSimulations.solve! — Method
solve!(
+    model::DecisionModel;
+    export_problem_results,
+    console_level,
+    file_level,
+    disable_timer_outputs,
+    serialize,
+    kwargs...
+) -> RunStatus
+

Default solve method for models that conform to the requirements of DecisionModel{<: DecisionProblem}.

This will call build! on the model if it is not already built. It will forward all keyword arguments to that function.

Arguments

  • model::OperationModel = model: operation model
  • export_problem_results::Bool = false: If true, export ProblemResults DataFrames to CSV files. Reduces solution times during simulation.
  • console_level = Logging.Error:
  • file_level = Logging.Info:
  • disable_timer_outputs = false : Enable/Disable timing outputs
  • serialize::Bool = true: If true, serialize the model to a file to allow re-execution later.

Examples

results = solve!(OpModel)
+results = solve!(OpModel, export_problem_results = true)
source
  + 

Emulation Models

PowerSimulations.EmulationModel — Type
EmulationModel{M}(
+    template::ProblemTemplate,
+    sys::PSY.System,
+    jump_model::Union{Nothing, JuMP.Model}=nothing;
+    kwargs...) where {M<:EmulationProblem}

Build the optimization problem of type M with the specific system and template.

Arguments

  • ::Type{M} where M<:EmulationProblem: The abstract Emulation model type
  • template::ProblemTemplate: The model reference made up of transmission, devices, branches, and services.
  • sys::PSY.System: the system created using Power Systems
  • jump_model::Union{Nothing, JuMP.Model}: Enables passing a custom JuMP model. Use with care
  • name = nothing: name of model, string or symbol; defaults to the type of template converted to a symbol.
  • optimizer::Union{Nothing,MOI.OptimizerWithAttributes} = nothing : The optimizer does not get serialized. Callers should pass whatever they passed to the original problem.
  • warm_start::Bool = true: True will use the current operation point in the system to initialize variable values. False initializes all variables to zero. Default is true
  • system_to_file::Bool = true:: True to create a copy of the system used in the model.
  • initialize_model::Bool = true: Option to decide to initialize the model or not.
  • initialization_file::String = "": This allows to pass pre-existing initialization values to avoid the solution of an optimization problem to find feasible initial conditions.
  • deserialize_initial_conditions::Bool = false: Option to deserialize conditions
  • export_pwl_vars::Bool = false: True to export all the pwl intermediate variables. It can slow down significantly the build and solve time.
  • allow_fails::Bool = false: True to allow the simulation to continue even if the optimization step fails. Use with care.
  • calculate_conflict::Bool = false: True to use solver to calculate conflicts for infeasible problems. Only specific solvers are able to calculate conflicts.
  • optimizer_solve_log_print::Bool = false: Uses JuMP.unset_silent() to print the optimizer's log. By default all solvers are set to MOI.Silent()
  • detailed_optimizer_stats::Bool = false: True to save detailed optimizer stats log.
  • direct_mode_optimizer::Bool = false: True to use the solver in direct mode. Creates a JuMP.direct_model.
  • store_variable_names::Bool = false: True to store variable names in optimization model.
  • rebuild_model::Bool = false: It will force the rebuild of the underlying JuMP model with each call to update the model. It increases solution times, use only if the model can't be updated in memory.
  • initial_time::Dates.DateTime = UNSET_INI_TIME: Initial Time for the model solve.
  • time_series_cache_size::Int = IS.TIME_SERIES_CACHE_SIZE_BYTES: Size in bytes to cache for each time array. Default is 1 MiB. Set to 0 to disable.

Example

template = ProblemTemplate(CopperPlatePowerModel, devices, branches, services)
+OpModel = EmulationModel(MockEmulationProblem, template, system)
source
PowerSimulations.EmulationModel — Method
EmulationModel(
+    ::Type{M<:PowerSimulations.EmulationProblem},
+    template::ProblemTemplate,
+    sys::System
+) -> EmulationModel
+EmulationModel(
+    ::Type{M<:PowerSimulations.EmulationProblem},
+    template::ProblemTemplate,
+    sys::System,
+    jump_model::Union{Nothing, JuMP.Model};
+    kwargs...
+) -> EmulationModel
+

Build the optimization problem of type M with the specific system and template

Arguments

  • ::Type{M} where M<:EmulationProblem: The abstract Emulation model type
  • template::ProblemTemplate: The model reference made up of transmission, devices, branches, and services.
  • sys::PSY.System: the system created using Power Systems
  • jump_model::Union{Nothing, JuMP.Model}: Enables passing a custom JuMP model. Use with care

Example

template = ProblemTemplate(CopperPlatePowerModel, devices, branches, services)
+problem = EmulationModel(MyEmProblemType, template, system, optimizer)
source
PowerSimulations.EmulationModel — Method
EmulationModel(
+    directory::AbstractString,
+    optimizer::MathOptInterface.OptimizerWithAttributes;
+    jump_model,
+    system,
+    kwargs...
+) -> Any
+

Construct an EmulationProblem from a serialized file.

Arguments

  • directory::AbstractString: Directory containing a serialized model.
  • optimizer::MOI.OptimizerWithAttributes: The optimizer does not get serialized. Callers should pass whatever they passed to the original problem.
  • jump_model::Union{Nothing, JuMP.Model} = nothing: The JuMP model does not get serialized. Callers should pass whatever they passed to the original problem.
  • system::Union{Nothing, PSY.System}: Optionally, the system used for the model. If nothing and systofile was set to true when the model was created, the system will be deserialized from a file.
source
PowerSimulations.build! — Method
build!(
+    model::EmulationModel;
+    executions,
+    output_dir,
+    recorders,
+    console_level,
+    file_level,
+    disable_timer_outputs
+)
+

Implementation of build for any EmulationProblem

source
PowerSimulations.run! — Method
run!(
+    model::EmulationModel;
+    export_problem_results,
+    console_level,
+    file_level,
+    disable_timer_outputs,
+    serialize,
+    kwargs...
+) -> RunStatus
+

Default run method for problems that conform to the requirements of EmulationModel{<: EmulationProblem}

This will call build! on the model if it is not already built. It will forward all keyword arguments to that function.

Arguments

  • model::EmulationModel = model: Emulation model
  • optimizer::MOI.OptimizerWithAttributes: The optimizer that is used to solve the model
  • executions::Int: Number of executions for the emulator run
  • export_problem_results::Bool: If true, export ProblemResults DataFrames to CSV files.
  • output_dir::String: Required if the model is not already built, otherwise ignored
  • enable_progress_bar::Bool: Enables/Disable progress bar printing
  • serialize::Bool: If true, serialize the model to a file to allow re-execution later.

Examples

status = run!(model; optimizer = GLPK.Optimizer, executions = 10)
+status = run!(model; output_dir = ./model_output, optimizer = GLPK.Optimizer, executions = 10)
source
  + 

Simulation Models

Refer to the Simulations Page to explanations on how to setup a Simulation, with Sequencing and Feedforwards.

PowerSimulations.SimulationModels — Type
SimulationModels(
+    decision_models::Vector{<:DecisionModel},
+    emulation_models::Union{Nothing, EmulationModel}
+)

Stores the OperationProblem definitions to be used in the simulation. When creating the SimulationModels, the order in which the models are created determines the order on which the simulation is executed.

Arguments

  • decision_models::Vector{<:DecisionModel}: Vector of decision models.
  • emulation_models::Union{Nothing, EmulationModel}: Optional argument to include

an EmulationModel in the Simulation

Example

template_uc = template_unit_commitment()
+template_ed = template_economic_dispatch()
+my_decision_model_uc = DecisionModel(template_1, sys_uc, optimizer, name = "UC")
+my_decision_model_ed = DecisionModel(template_ed, sys_ed, optimizer, name = "ED")
+models = SimulationModels(
+    decision_models = [
+        my_decision_model_uc,
+        my_decision_model_ed
+    ]
+)
source
PowerSimulations.SimulationSequence — Type
SimulationSequence(
+    models::SimulationModels,
+    feedforward::Dict{String, Vector{<:AbstractAffectFeedforward}}
+    ini_cond_chronology::InitialConditionChronology
+)

Construct the simulation sequence between decision and emulation models.

Arguments

  • models::SimulationModels: Vector of decisions and emulation models.
  • feedforward = Dict{String, Vector{<:AbstractAffectFeedforward}}(): Optional dictionary to specify how information

and variables are exchanged between decision and emulation models.

  • ini_cond_chronology::nitialConditionChronology = InterProblemChronology(): TODO

Example

template_uc = template_unit_commitment()
+template_ed = template_economic_dispatch()
+my_decision_model_uc = DecisionModel(template_1, sys_uc, optimizer, name = "UC")
+my_decision_model_ed = DecisionModel(template_ed, sys_ed, optimizer, name = "ED")
+models = SimulationModels(
+    decision_models = [
+        my_decision_model_uc,
+        my_decision_model_ed
+    ]
+)
+# The following sequence set the commitment variables (`OnVariable`) for `ThermalStandard` units from UC to ED.
+sequence = SimulationSequence(;
+    models = models,
+    feedforwards = Dict(
+        "ED" => [
+            SemiContinuousFeedforward(;
+                component_type = ThermalStandard,
+                source = OnVariable,
+                affected_values = [ActivePowerVariable],
+            ),
+        ],
+    ),
+)
source
PowerSimulations.Simulation — Type
Simulation(
+    sequence::SimulationSequence,
+    name::String,
+    steps::Int
+    models::SimulationModels,
+    simulation_folder::String,
+    initial_time::Union{Nothing, Dates.DateTime}
+)

Construct the Simulation structure to run the sequence of decision and emulation models specified.

Arguments

-sequence::SimulationSequence: Simulation sequence that specify how the decision and emulation models will be executed. -name::String: Name of the Simulation -steps::Int: Number of steps on which the sequence of models will be executed -models::SimulationModels: List of Decision and Emulation Models -simulation_folder::String: Folder on which results will be stored -initial_time::Union{Nothing, Dates.DateTime} = nothing: Initial time of which the simulation starts. If nothing it will default to the first timestamp of time series of the system.

Example

template_uc = template_unit_commitment()
+template_ed = template_economic_dispatch()
+my_decision_model_uc = DecisionModel(template_1, sys_uc, optimizer, name = "UC")
+my_decision_model_ed = DecisionModel(template_ed, sys_ed, optimizer, name = "ED")
+models = SimulationModels(
+    decision_models = [
+        my_decision_model_uc,
+        my_decision_model_ed
+    ]
+)
+# The following sequence set the commitment variables (`OnVariable`) for `ThermalStandard` units from UC to ED.
+sequence = SimulationSequence(;
+    models = models,
+    feedforwards = Dict(
+        "ED" => [
+            SemiContinuousFeedforward(;
+                component_type = ThermalStandard,
+                source = OnVariable,
+                affected_values = [ActivePowerVariable],
+            ),
+        ],
+    ),
+)
+
+sim = Simulation(
+    sequence = sequence,
+    name = "Sim",
+    steps = 5,
+    models = models,
+    simulation_folder = mktempdir(cleanup=true),
+)
source
PowerSimulations.Simulation — Method
Simulation(directory::AbstractString, model_info::Dict)
+

Constructs Simulation from a serialized directory. Callers should pass any kwargs here that they passed to the original Simulation.

Arguments

  • directory::AbstractString: the directory returned from the call to serialize
  • model_info::Dict: Two-level dictionary containing model parameters that cannot be serialized. The outer dict should be keyed by the problem name. The inner dict must contain 'optimizer' and may contain 'jump_model'. These should be the same values used for the original simulation.
source
PowerSimulations.build! — Method
build!(
+    sim::Simulation;
+    recorders,
+    console_level,
+    file_level,
+    serialize,
+    partitions,
+    index
+) -> BuildStatus
+

Build the Simulation, problems and the related folder structure.

Arguments

  • sim::Simulation: simulation object
  • recorders::Vector{Symbol} = []: recorder names to register
  • serialize::Bool = true: serializes the simulation objects in the simulation
  • console_level = Logging.Error:
  • file_level = Logging.Info:
source
PowerSimulations.execute! — Method
execute!(sim::Simulation; kwargs...) -> RunStatus
+

Solves the simulation model for sequential Simulations.

Arguments

  • sim::Simulation=sim: simulation object created by Simulation()

The optional keyword argument exports controls exporting of results to CSV files as the simulation runs. Refer to export_results for a description of this argument.

Example

sim = Simulation("Test", 7, problems, "/Users/folder")
+execute!(sim::Simulation; kwargs...)
source
  + 

Variables

For a list of variables for each device refer to its Formulations page.

Common Variables

Missing docstring.

Missing docstring for PieceWiseLinearCostVariable. Check Documenter's build log for details.

Thermal Unit Variables

Missing docstring.

Missing docstring for StartVariable. Check Documenter's build log for details.

Missing docstring.

Missing docstring for StopVariable. Check Documenter's build log for details.

Missing docstring.

Missing docstring for TimeDurationOn. Check Documenter's build log for details.

Missing docstring.

Missing docstring for TimeDurationOff. Check Documenter's build log for details.

Missing docstring.

Missing docstring for HotStartVariable. Check Documenter's build log for details.

Missing docstring.

Missing docstring for WarmStartVariable. Check Documenter's build log for details.

Missing docstring.

Missing docstring for ColdStartVariable. Check Documenter's build log for details.

Storage Unit Variables

Branches and Network Variables

Missing docstring.

Missing docstring for PhaseShifterAngle. Check Documenter's build log for details.

Missing docstring.

Missing docstring for HVDCLosses. Check Documenter's build log for details.

Missing docstring.

Missing docstring for HVDCFlowDirectionVariable. Check Documenter's build log for details.

Missing docstring.

Missing docstring for VoltageMagnitude. Check Documenter's build log for details.

Missing docstring.

Missing docstring for VoltageAngle. Check Documenter's build log for details.

Regulation and Services Variables

Missing docstring.

Missing docstring for ServiceRequirementVariable. Check Documenter's build log for details.

Missing docstring.

Missing docstring for DeltaActivePowerUpVariable. Check Documenter's build log for details.

Missing docstring.

Missing docstring for DeltaActivePowerDownVariable. Check Documenter's build log for details.

Missing docstring.

Missing docstring for AdditionalDeltaActivePowerUpVariable. Check Documenter's build log for details.

Missing docstring.

Missing docstring for AdditionalDeltaActivePowerDownVariable. Check Documenter's build log for details.

Missing docstring.

Missing docstring for AreaMismatchVariable. Check Documenter's build log for details.

Missing docstring.

Missing docstring for SteadyStateFrequencyDeviation. Check Documenter's build log for details.

Missing docstring.

Missing docstring for SmoothACE. Check Documenter's build log for details.

Missing docstring.

Missing docstring for SystemBalanceSlackUp. Check Documenter's build log for details.

Missing docstring.

Missing docstring for SystemBalanceSlackDown. Check Documenter's build log for details.

Missing docstring.

Missing docstring for ReserveRequirementSlack. Check Documenter's build log for details.

  + 

Constraints

Common Constraints

Missing docstring.

Missing docstring for PieceWiseLinearCostConstraint. Check Documenter's build log for details.

Network Constraints

Missing docstring.

Missing docstring for AreaDispatchBalanceConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for AreaParticipationAssignmentConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for BalanceAuxConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for CopperPlateBalanceConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for FrequencyResponseConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for NodalBalanceActiveConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for NodalBalanceReactiveConstraint. Check Documenter's build log for details.

Power Variable Limit Constraints

Missing docstring.

Missing docstring for ActivePowerVariableLimitsConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for ReactivePowerVariableLimitsConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for ActivePowerVariableTimeSeriesLimitsConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for InputActivePowerVariableLimitsConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for OutputActivePowerVariableLimitsConstraint. Check Documenter's build log for details.

Regulation and Services Constraints

Missing docstring.

Missing docstring for ParticipationAssignmentConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for RegulationLimitsConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for RequirementConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for ReserveEnergyCoverageConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for ReservePowerConstraint. Check Documenter's build log for details.

Thermal Unit Constraints

Missing docstring.

Missing docstring for ActiveRangeICConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for CommitmentConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for DurationConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for RampConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for RampLimitConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for StartupInitialConditionConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for StartupTimeLimitTemperatureConstraint. Check Documenter's build log for details.

Renewable Unit Constraints

Missing docstring.

Missing docstring for EqualityConstraint. Check Documenter's build log for details.

Branches Constraints

Missing docstring.

Missing docstring for AbsoluteValueConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for FlowLimitFromToConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for FlowLimitToFromConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for FlowRateConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for FlowRateConstraintFromTo. Check Documenter's build log for details.

Missing docstring.

Missing docstring for FlowRateConstraintToFrom. Check Documenter's build log for details.

Missing docstring.

Missing docstring for HVDCDirection. Check Documenter's build log for details.

Missing docstring.

Missing docstring for HVDCLossesAbsoluteValue. Check Documenter's build log for details.

Missing docstring.

Missing docstring for HVDCPowerBalance. Check Documenter's build log for details.

Missing docstring.

Missing docstring for NetworkFlowConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for RateLimitConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for RateLimitConstraintFromTo. Check Documenter's build log for details.

Missing docstring.

Missing docstring for RateLimitConstraintToFrom. Check Documenter's build log for details.

Missing docstring.

Missing docstring for PhaseAngleControlLimit. Check Documenter's build log for details.

Feedforward Constraints

Missing docstring.

Missing docstring for FeedforwardSemiContinousConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for FeedforwardIntegralLimitConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for FeedforwardUpperBoundConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for FeedforwardLowerBoundConstraint. Check Documenter's build log for details.

Missing docstring.

Missing docstring for FeedforwardEnergyTargetConstraint. Check Documenter's build log for details.

Parameters

Time Series Parameters

Variable Value Parameters

Missing docstring.

Missing docstring for EnergyLimitParameter. Check Documenter's build log for details.

Missing docstring.

Missing docstring for EnergyTargetParameter. Check Documenter's build log for details.

Objective Function Parameters

diff --git a/v0.24.1/assets/documenter.js b/v0.24.1/assets/documenter.js new file mode 100644 index 0000000000..6adfbbbf4b --- /dev/null +++ b/v0.24.1/assets/documenter.js @@ -0,0 +1,331 @@ +// Generated by Documenter.jl +requirejs.config({ + paths: { + 'highlight-julia': 'https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.5.1/languages/julia.min', + 'headroom': 'https://cdnjs.cloudflare.com/ajax/libs/headroom/0.12.0/headroom.min', + 'jqueryui': 'https://cdnjs.cloudflare.com/ajax/libs/jqueryui/1.12.1/jquery-ui.min', + 'katex-auto-render': 'https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.13.24/contrib/auto-render.min', + 'jquery': 'https://cdnjs.cloudflare.com/ajax/libs/jquery/3.6.0/jquery.min', + 'headroom-jquery': 'https://cdnjs.cloudflare.com/ajax/libs/headroom/0.12.0/jQuery.headroom.min', + 'katex': 'https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.13.24/katex.min', + 'highlight': 'https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.5.1/highlight.min', + 'highlight-julia-repl': 'https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.5.1/languages/julia-repl.min', + }, + shim: { + "highlight-julia": { + "deps": [ + "highlight" + ] + }, + "katex-auto-render": { + "deps": [ + "katex" + ] + }, + "headroom-jquery": { + "deps": [ + "jquery", + "headroom" + ] + }, + "highlight-julia-repl": { + "deps": [ + "highlight" + ] + } +} +}); +//////////////////////////////////////////////////////////////////////////////// +require(['jquery', 'katex', 'katex-auto-render'], function($, katex, renderMathInElement) { +$(document).ready(function() { + renderMathInElement( + document.body, + { + "delimiters": [ + { + "left": "$", + "right": "$", + "display": false + }, + { + "left": "$$", + "right": "$$", + "display": true + }, + { + "left": "\\[", + "right": "\\]", + "display": true + } + ] +} + + ); +}) + +}) +//////////////////////////////////////////////////////////////////////////////// +require(['jquery', 'highlight', 'highlight-julia', 'highlight-julia-repl'], function($) { +$(document).ready(function() { + hljs.highlightAll(); +}) + +}) +//////////////////////////////////////////////////////////////////////////////// +require([], function() { +function addCopyButtonCallbacks() { + for (const el of document.getElementsByTagName("pre")) { + const button = document.createElement("button"); + button.classList.add("copy-button", "fas", "fa-copy"); 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+ set_theme(themename); + }); + + // Make sure that the themepicker displays the correct theme when the theme is retrieved + // from localStorage + if(typeof(window.localStorage) !== "undefined") { + var theme = window.localStorage.getItem("documenter-theme"); + if(theme !== null) { + $('#documenter-themepicker option').each(function(i,e) { + e.selected = (e.value === theme); + }) + } else { + $('#documenter-themepicker option').each(function(i,e) { + e.selected = $("html").hasClass(`theme--${e.value}`); + }) + } + } +}) + +}) +//////////////////////////////////////////////////////////////////////////////// +require(['jquery'], function($) { + +// update the version selector with info from the siteinfo.js and ../versions.js files +$(document).ready(function() { + // If the version selector is disabled with DOCUMENTER_VERSION_SELECTOR_DISABLED in the + // siteinfo.js file, we just return immediately and not display the version selector. + if (typeof DOCUMENTER_VERSION_SELECTOR_DISABLED === 'boolean' && DOCUMENTER_VERSION_SELECTOR_DISABLED) { + return; + } + + var version_selector = $("#documenter .docs-version-selector"); + var version_selector_select = $("#documenter .docs-version-selector select"); + + version_selector_select.change(function(x) { + target_href = version_selector_select.children("option:selected").get(0).value; + window.location.href = target_href; + }); + + // add the current version to the selector based on siteinfo.js, but only if the selector is empty + if (typeof DOCUMENTER_CURRENT_VERSION !== 'undefined' && $('#version-selector > option').length == 0) { + var option = $(""); + version_selector_select.append(option); + } + + if (typeof DOC_VERSIONS !== 'undefined') { + var existing_versions = version_selector_select.children("option"); + var existing_versions_texts = existing_versions.map(function(i,x){return x.text}); + DOC_VERSIONS.forEach(function(each) { + var version_url = documenterBaseURL + "/../" + each; + var existing_id = $.inArray(each, existing_versions_texts); + // if not already in the version selector, add it as a new option, + // otherwise update the old option with the URL and enable it + if (existing_id == -1) { + var option = $(""); 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+//////////////////////////////////////////////////////////////////////////////// +require(['jquery', 'lunr', 'lodash'], function($, lunr, _) { + +$(document).ready(function() { + // parseUri 1.2.2 + // (c) Steven Levithan + // MIT License + function parseUri (str) { + var o = parseUri.options, + m = o.parser[o.strictMode ? "strict" : "loose"].exec(str), + uri = {}, + i = 14; + + while (i--) uri[o.key[i]] = m[i] || ""; + + uri[o.q.name] = {}; + uri[o.key[12]].replace(o.q.parser, function ($0, $1, $2) { + if ($1) uri[o.q.name][$1] = $2; + }); + + return uri; + }; + parseUri.options = { + strictMode: false, + key: ["source","protocol","authority","userInfo","user","password","host","port","relative","path","directory","file","query","anchor"], + q: { + name: "queryKey", + parser: /(?:^|&)([^&=]*)=?([^&]*)/g + }, + parser: { + strict: /^(?:([^:\/?#]+):)?(?:\/\/((?:(([^:@]*)(?::([^:@]*))?)?@)?([^:\/?#]*)(?::(\d*))?))?((((?:[^?#\/]*\/)*)([^?#]*))(?:\?([^#]*))?(?:#(.*))?)/, + loose: /^(?:(?![^:@]+:[^:@\/]*@)([^:\/?#.]+):)?(?:\/\/)?((?:(([^:@]*)(?::([^:@]*))?)?@)?([^:\/?#]*)(?::(\d*))?)(((\/(?:[^?#](?![^?#\/]*\.[^?#\/.]+(?:[?#]|$)))*\/?)?([^?#\/]*))(?:\?([^#]*))?(?:#(.*))?)/ + } + }; + + $("#search-form").submit(function(e) { + e.preventDefault() + }) + + // list below is the lunr 2.1.3 list minus the intersect with names(Base) + // (all, any, get, in, is, only, which) and (do, else, for, let, where, while, with) + // ideally we'd just filter the original list but it's not available as a variable + lunr.stopWordFilter = lunr.generateStopWordFilter([ + 'a', + 'able', + 'about', + 'across', + 'after', + 'almost', + 'also', + 'am', + 'among', + 'an', + 'and', + 'are', + 'as', + 'at', + 'be', + 'because', + 'been', + 'but', + 'by', + 'can', + 'cannot', + 'could', + 'dear', + 'did', + 'does', + 'either', + 'ever', + 'every', + 'from', + 'got', + 'had', + 'has', + 'have', + 'he', + 'her', + 'hers', + 'him', + 'his', + 'how', + 'however', + 'i', + 'if', + 'into', + 'it', + 'its', + 'just', + 'least', + 'like', + 'likely', + 'may', + 'me', + 'might', + 'most', + 'must', + 'my', + 'neither', + 'no', + 'nor', + 'not', + 'of', + 'off', + 'often', + 'on', + 'or', + 'other', + 'our', + 'own', + 'rather', + 'said', + 'say', + 'says', + 'she', + 'should', + 'since', + 'so', + 'some', + 'than', + 'that', + 'the', + 'their', + 'them', + 'then', + 'there', + 'these', + 'they', + 'this', + 'tis', + 'to', + 'too', + 'twas', + 'us', + 'wants', + 'was', + 'we', + 'were', + 'what', + 'when', + 'who', + 'whom', + 'why', + 'will', + 'would', + 'yet', + 'you', + 'your' + ]) + + // add . as a separator, because otherwise "title": "Documenter.Anchors.add!" + // would not find anything if searching for "add!", only for the entire qualification + lunr.tokenizer.separator = /[\s\-\.]+/ + + // custom trimmer that doesn't strip @ and !, which are used in julia macro and function names + lunr.trimmer = function (token) { + return token.update(function (s) { + return s.replace(/^[^a-zA-Z0-9@!]+/, '').replace(/[^a-zA-Z0-9@!]+$/, '') + }) + } + + lunr.Pipeline.registerFunction(lunr.stopWordFilter, 'juliaStopWordFilter') + lunr.Pipeline.registerFunction(lunr.trimmer, 'juliaTrimmer') + + var index = lunr(function () { + this.ref('location') + this.field('title',{boost: 100}) + this.field('text') + documenterSearchIndex['docs'].forEach(function(e) { + this.add(e) + }, this) + }) + var store = {} + + documenterSearchIndex['docs'].forEach(function(e) { + store[e.location] = {title: e.title, category: e.category, page: e.page} + }) + + $(function(){ + searchresults = $('#documenter-search-results'); + searchinfo = $('#documenter-search-info'); + searchbox = $('#documenter-search-query'); + searchform = $('.docs-search'); + sidebar = $('.docs-sidebar'); + function update_search(querystring) { + tokens = lunr.tokenizer(querystring) + results = index.query(function (q) { + tokens.forEach(function (t) { + q.term(t.toString(), { + fields: ["title"], + boost: 100, + usePipeline: true, + editDistance: 0, + wildcard: lunr.Query.wildcard.NONE + }) + q.term(t.toString(), { + fields: ["title"], + boost: 10, + usePipeline: true, + editDistance: 2, + wildcard: lunr.Query.wildcard.NONE + }) + q.term(t.toString(), { + fields: ["text"], + boost: 1, + usePipeline: true, + editDistance: 0, + wildcard: lunr.Query.wildcard.NONE + }) + }) + }) + searchinfo.text("Number of results: " + results.length) + searchresults.empty() + results.forEach(function(result) { + data = store[result.ref] + link = $(''+data.title+'') + link.attr('href', documenterBaseURL+'/'+result.ref) + if (data.category != "page"){ + cat = $('('+data.category+', '+data.page+')') + } else { + cat = $('('+data.category+')') + } + li = $('
  • ').append(link).append(" ").append(cat) + searchresults.append(li) + }) + } + + function update_search_box() { + querystring = searchbox.val() + update_search(querystring) + } + + searchbox.keyup(_.debounce(update_search_box, 250)) + searchbox.change(update_search_box) + + // Disable enter-key form submission for the searchbox on the search page + // and just re-run search rather than refresh the whole page. + searchform.keypress( + function(event){ + if (event.which == '13') { + if (sidebar.hasClass('visible')) { + sidebar.removeClass('visible'); + } + update_search_box(); + event.preventDefault(); + } + } + ); + + search_query_uri = parseUri(window.location).queryKey["q"] + if(search_query_uri !== undefined) { + search_query = decodeURIComponent(search_query_uri.replace(/\+/g, '%20')) + searchbox.val(search_query) + } + update_search_box(); + }) +}) + +}) diff --git a/v0.24.1/assets/themes/documenter-dark.css b/v0.24.1/assets/themes/documenter-dark.css new file mode 100644 index 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html.theme--documenter-dark .button.is-white.is-inverted{background-color:#0a0a0a;border-color:transparent;box-shadow:none;color:#fff}html.theme--documenter-dark .button.is-white.is-loading::after{border-color:transparent transparent #0a0a0a #0a0a0a !important}html.theme--documenter-dark .button.is-white.is-outlined{background-color:transparent;border-color:#fff;color:#fff}html.theme--documenter-dark .button.is-white.is-outlined:hover,html.theme--documenter-dark .button.is-white.is-outlined.is-hovered,html.theme--documenter-dark .button.is-white.is-outlined:focus,html.theme--documenter-dark .button.is-white.is-outlined.is-focused{background-color:#fff;border-color:#fff;color:#0a0a0a}html.theme--documenter-dark .button.is-white.is-outlined.is-loading::after{border-color:transparent transparent #fff #fff !important}html.theme--documenter-dark .button.is-white.is-outlined.is-loading:hover::after,html.theme--documenter-dark .button.is-white.is-outlined.is-loading.is-hovered::after,html.theme--documenter-dark .button.is-white.is-outlined.is-loading:focus::after,html.theme--documenter-dark .button.is-white.is-outlined.is-loading.is-focused::after{border-color:transparent transparent #0a0a0a #0a0a0a !important}html.theme--documenter-dark .button.is-white.is-outlined[disabled],fieldset[disabled] html.theme--documenter-dark .button.is-white.is-outlined{background-color:transparent;border-color:#fff;box-shadow:none;color:#fff}html.theme--documenter-dark .button.is-white.is-inverted.is-outlined{background-color:transparent;border-color:#0a0a0a;color:#0a0a0a}html.theme--documenter-dark .button.is-white.is-inverted.is-outlined:hover,html.theme--documenter-dark .button.is-white.is-inverted.is-outlined.is-hovered,html.theme--documenter-dark .button.is-white.is-inverted.is-outlined:focus,html.theme--documenter-dark 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.button.is-black.is-inverted.is-hovered{background-color:#f2f2f2}html.theme--documenter-dark .button.is-black.is-inverted[disabled],fieldset[disabled] html.theme--documenter-dark .button.is-black.is-inverted{background-color:#fff;border-color:transparent;box-shadow:none;color:#0a0a0a}html.theme--documenter-dark .button.is-black.is-loading::after{border-color:transparent transparent #fff #fff !important}html.theme--documenter-dark .button.is-black.is-outlined{background-color:transparent;border-color:#0a0a0a;color:#0a0a0a}html.theme--documenter-dark .button.is-black.is-outlined:hover,html.theme--documenter-dark .button.is-black.is-outlined.is-hovered,html.theme--documenter-dark .button.is-black.is-outlined:focus,html.theme--documenter-dark .button.is-black.is-outlined.is-focused{background-color:#0a0a0a;border-color:#0a0a0a;color:#fff}html.theme--documenter-dark .button.is-black.is-outlined.is-loading::after{border-color:transparent transparent #0a0a0a #0a0a0a !important}html.theme--documenter-dark .button.is-black.is-outlined.is-loading:hover::after,html.theme--documenter-dark .button.is-black.is-outlined.is-loading.is-hovered::after,html.theme--documenter-dark .button.is-black.is-outlined.is-loading:focus::after,html.theme--documenter-dark .button.is-black.is-outlined.is-loading.is-focused::after{border-color:transparent transparent #fff #fff !important}html.theme--documenter-dark .button.is-black.is-outlined[disabled],fieldset[disabled] html.theme--documenter-dark .button.is-black.is-outlined{background-color:transparent;border-color:#0a0a0a;box-shadow:none;color:#0a0a0a}html.theme--documenter-dark .button.is-black.is-inverted.is-outlined{background-color:transparent;border-color:#fff;color:#fff}html.theme--documenter-dark .button.is-black.is-inverted.is-outlined:hover,html.theme--documenter-dark .button.is-black.is-inverted.is-outlined.is-hovered,html.theme--documenter-dark .button.is-black.is-inverted.is-outlined:focus,html.theme--documenter-dark .button.is-black.is-inverted.is-outlined.is-focused{background-color:#fff;color:#0a0a0a}html.theme--documenter-dark .button.is-black.is-inverted.is-outlined.is-loading:hover::after,html.theme--documenter-dark .button.is-black.is-inverted.is-outlined.is-loading.is-hovered::after,html.theme--documenter-dark .button.is-black.is-inverted.is-outlined.is-loading:focus::after,html.theme--documenter-dark .button.is-black.is-inverted.is-outlined.is-loading.is-focused::after{border-color:transparent transparent #0a0a0a #0a0a0a !important}html.theme--documenter-dark .button.is-black.is-inverted.is-outlined[disabled],fieldset[disabled] html.theme--documenter-dark .button.is-black.is-inverted.is-outlined{background-color:transparent;border-color:#fff;box-shadow:none;color:#fff}html.theme--documenter-dark .button.is-light{background-color:#ecf0f1;border-color:transparent;color:#282f2f}html.theme--documenter-dark .button.is-light:hover,html.theme--documenter-dark .button.is-light.is-hovered{background-color:#e5eaec;border-color:transparent;color:#282f2f}html.theme--documenter-dark .button.is-light:focus,html.theme--documenter-dark .button.is-light.is-focused{border-color:transparent;color:#282f2f}html.theme--documenter-dark .button.is-light:focus:not(:active),html.theme--documenter-dark .button.is-light.is-focused:not(:active){box-shadow:0 0 0 0.125em rgba(236,240,241,0.25)}html.theme--documenter-dark .button.is-light:active,html.theme--documenter-dark .button.is-light.is-active{background-color:#dde4e6;border-color:transparent;color:#282f2f}html.theme--documenter-dark .button.is-light[disabled],fieldset[disabled] html.theme--documenter-dark .button.is-light{background-color:#ecf0f1;border-color:transparent;box-shadow:none}html.theme--documenter-dark .button.is-light.is-inverted{background-color:#282f2f;color:#ecf0f1}html.theme--documenter-dark .button.is-light.is-inverted:hover,html.theme--documenter-dark .button.is-light.is-inverted.is-hovered{background-color:#1d2122}html.theme--documenter-dark .button.is-light.is-inverted[disabled],fieldset[disabled] html.theme--documenter-dark .button.is-light.is-inverted{background-color:#282f2f;border-color:transparent;box-shadow:none;color:#ecf0f1}html.theme--documenter-dark .button.is-light.is-loading::after{border-color:transparent transparent #282f2f #282f2f !important}html.theme--documenter-dark .button.is-light.is-outlined{background-color:transparent;border-color:#ecf0f1;color:#ecf0f1}html.theme--documenter-dark .button.is-light.is-outlined:hover,html.theme--documenter-dark .button.is-light.is-outlined.is-hovered,html.theme--documenter-dark .button.is-light.is-outlined:focus,html.theme--documenter-dark .button.is-light.is-outlined.is-focused{background-color:#ecf0f1;border-color:#ecf0f1;color:#282f2f}html.theme--documenter-dark .button.is-light.is-outlined.is-loading::after{border-color:transparent transparent #ecf0f1 #ecf0f1 !important}html.theme--documenter-dark .button.is-light.is-outlined.is-loading:hover::after,html.theme--documenter-dark .button.is-light.is-outlined.is-loading.is-hovered::after,html.theme--documenter-dark .button.is-light.is-outlined.is-loading:focus::after,html.theme--documenter-dark .button.is-light.is-outlined.is-loading.is-focused::after{border-color:transparent transparent #282f2f #282f2f !important}html.theme--documenter-dark .button.is-light.is-outlined[disabled],fieldset[disabled] html.theme--documenter-dark .button.is-light.is-outlined{background-color:transparent;border-color:#ecf0f1;box-shadow:none;color:#ecf0f1}html.theme--documenter-dark .button.is-light.is-inverted.is-outlined{background-color:transparent;border-color:#282f2f;color:#282f2f}html.theme--documenter-dark .button.is-light.is-inverted.is-outlined:hover,html.theme--documenter-dark .button.is-light.is-inverted.is-outlined.is-hovered,html.theme--documenter-dark .button.is-light.is-inverted.is-outlined:focus,html.theme--documenter-dark .button.is-light.is-inverted.is-outlined.is-focused{background-color:#282f2f;color:#ecf0f1}html.theme--documenter-dark .button.is-light.is-inverted.is-outlined.is-loading:hover::after,html.theme--documenter-dark .button.is-light.is-inverted.is-outlined.is-loading.is-hovered::after,html.theme--documenter-dark .button.is-light.is-inverted.is-outlined.is-loading:focus::after,html.theme--documenter-dark .button.is-light.is-inverted.is-outlined.is-loading.is-focused::after{border-color:transparent transparent #ecf0f1 #ecf0f1 !important}html.theme--documenter-dark .button.is-light.is-inverted.is-outlined[disabled],fieldset[disabled] html.theme--documenter-dark .button.is-light.is-inverted.is-outlined{background-color:transparent;border-color:#282f2f;box-shadow:none;color:#282f2f}html.theme--documenter-dark .button.is-dark,html.theme--documenter-dark .content kbd.button{background-color:#282f2f;border-color:transparent;color:#ecf0f1}html.theme--documenter-dark .button.is-dark:hover,html.theme--documenter-dark .content kbd.button:hover,html.theme--documenter-dark .button.is-dark.is-hovered,html.theme--documenter-dark .content kbd.button.is-hovered{background-color:#232829;border-color:transparent;color:#ecf0f1}html.theme--documenter-dark .button.is-dark:focus,html.theme--documenter-dark .content kbd.button:focus,html.theme--documenter-dark .button.is-dark.is-focused,html.theme--documenter-dark .content kbd.button.is-focused{border-color:transparent;color:#ecf0f1}html.theme--documenter-dark .button.is-dark:focus:not(:active),html.theme--documenter-dark .content kbd.button:focus:not(:active),html.theme--documenter-dark .button.is-dark.is-focused:not(:active),html.theme--documenter-dark .content kbd.button.is-focused:not(:active){box-shadow:0 0 0 0.125em rgba(40,47,47,0.25)}html.theme--documenter-dark .button.is-dark:active,html.theme--documenter-dark .content kbd.button:active,html.theme--documenter-dark .button.is-dark.is-active,html.theme--documenter-dark .content kbd.button.is-active{background-color:#1d2122;border-color:transparent;color:#ecf0f1}html.theme--documenter-dark .button.is-dark[disabled],html.theme--documenter-dark .content kbd.button[disabled],fieldset[disabled] html.theme--documenter-dark .button.is-dark,fieldset[disabled] html.theme--documenter-dark .content kbd.button{background-color:#282f2f;border-color:transparent;box-shadow:none}html.theme--documenter-dark .button.is-dark.is-inverted,html.theme--documenter-dark .content kbd.button.is-inverted{background-color:#ecf0f1;color:#282f2f}html.theme--documenter-dark .button.is-dark.is-inverted:hover,html.theme--documenter-dark .content kbd.button.is-inverted:hover,html.theme--documenter-dark .button.is-dark.is-inverted.is-hovered,html.theme--documenter-dark .content kbd.button.is-inverted.is-hovered{background-color:#dde4e6}html.theme--documenter-dark .button.is-dark.is-inverted[disabled],html.theme--documenter-dark .content kbd.button.is-inverted[disabled],fieldset[disabled] html.theme--documenter-dark .button.is-dark.is-inverted,fieldset[disabled] html.theme--documenter-dark .content kbd.button.is-inverted{background-color:#ecf0f1;border-color:transparent;box-shadow:none;color:#282f2f}html.theme--documenter-dark .button.is-dark.is-loading::after,html.theme--documenter-dark .content kbd.button.is-loading::after{border-color:transparent transparent #ecf0f1 #ecf0f1 !important}html.theme--documenter-dark .button.is-dark.is-outlined,html.theme--documenter-dark .content kbd.button.is-outlined{background-color:transparent;border-color:#282f2f;color:#282f2f}html.theme--documenter-dark .button.is-dark.is-outlined:hover,html.theme--documenter-dark .content kbd.button.is-outlined:hover,html.theme--documenter-dark .button.is-dark.is-outlined.is-hovered,html.theme--documenter-dark .content kbd.button.is-outlined.is-hovered,html.theme--documenter-dark .button.is-dark.is-outlined:focus,html.theme--documenter-dark .content kbd.button.is-outlined:focus,html.theme--documenter-dark .button.is-dark.is-outlined.is-focused,html.theme--documenter-dark .content kbd.button.is-outlined.is-focused{background-color:#282f2f;border-color:#282f2f;color:#ecf0f1}html.theme--documenter-dark .button.is-dark.is-outlined.is-loading::after,html.theme--documenter-dark .content kbd.button.is-outlined.is-loading::after{border-color:transparent transparent #282f2f #282f2f !important}html.theme--documenter-dark .button.is-dark.is-outlined.is-loading:hover::after,html.theme--documenter-dark .content kbd.button.is-outlined.is-loading:hover::after,html.theme--documenter-dark .button.is-dark.is-outlined.is-loading.is-hovered::after,html.theme--documenter-dark .content kbd.button.is-outlined.is-loading.is-hovered::after,html.theme--documenter-dark .button.is-dark.is-outlined.is-loading:focus::after,html.theme--documenter-dark .content kbd.button.is-outlined.is-loading:focus::after,html.theme--documenter-dark .button.is-dark.is-outlined.is-loading.is-focused::after,html.theme--documenter-dark .content kbd.button.is-outlined.is-loading.is-focused::after{border-color:transparent transparent #ecf0f1 #ecf0f1 !important}html.theme--documenter-dark .button.is-dark.is-outlined[disabled],html.theme--documenter-dark .content kbd.button.is-outlined[disabled],fieldset[disabled] html.theme--documenter-dark .button.is-dark.is-outlined,fieldset[disabled] html.theme--documenter-dark .content kbd.button.is-outlined{background-color:transparent;border-color:#282f2f;box-shadow:none;color:#282f2f}html.theme--documenter-dark .button.is-dark.is-inverted.is-outlined,html.theme--documenter-dark .content kbd.button.is-inverted.is-outlined{background-color:transparent;border-color:#ecf0f1;color:#ecf0f1}html.theme--documenter-dark .button.is-dark.is-inverted.is-outlined:hover,html.theme--documenter-dark .content kbd.button.is-inverted.is-outlined:hover,html.theme--documenter-dark .button.is-dark.is-inverted.is-outlined.is-hovered,html.theme--documenter-dark .content kbd.button.is-inverted.is-outlined.is-hovered,html.theme--documenter-dark .button.is-dark.is-inverted.is-outlined:focus,html.theme--documenter-dark .content kbd.button.is-inverted.is-outlined:focus,html.theme--documenter-dark .button.is-dark.is-inverted.is-outlined.is-focused,html.theme--documenter-dark .content kbd.button.is-inverted.is-outlined.is-focused{background-color:#ecf0f1;color:#282f2f}html.theme--documenter-dark .button.is-dark.is-inverted.is-outlined.is-loading:hover::after,html.theme--documenter-dark .content kbd.button.is-inverted.is-outlined.is-loading:hover::after,html.theme--documenter-dark .button.is-dark.is-inverted.is-outlined.is-loading.is-hovered::after,html.theme--documenter-dark .content kbd.button.is-inverted.is-outlined.is-loading.is-hovered::after,html.theme--documenter-dark .button.is-dark.is-inverted.is-outlined.is-loading:focus::after,html.theme--documenter-dark .content kbd.button.is-inverted.is-outlined.is-loading:focus::after,html.theme--documenter-dark .button.is-dark.is-inverted.is-outlined.is-loading.is-focused::after,html.theme--documenter-dark .content kbd.button.is-inverted.is-outlined.is-loading.is-focused::after{border-color:transparent transparent #282f2f #282f2f !important}html.theme--documenter-dark .button.is-dark.is-inverted.is-outlined[disabled],html.theme--documenter-dark .content kbd.button.is-inverted.is-outlined[disabled],fieldset[disabled] html.theme--documenter-dark .button.is-dark.is-inverted.is-outlined,fieldset[disabled] html.theme--documenter-dark .content kbd.button.is-inverted.is-outlined{background-color:transparent;border-color:#ecf0f1;box-shadow:none;color:#ecf0f1}html.theme--documenter-dark .button.is-primary,html.theme--documenter-dark .docstring>section>a.button.docs-sourcelink{background-color:#375a7f;border-color:transparent;color:#fff}html.theme--documenter-dark .button.is-primary:hover,html.theme--documenter-dark .docstring>section>a.button.docs-sourcelink:hover,html.theme--documenter-dark .button.is-primary.is-hovered,html.theme--documenter-dark .docstring>section>a.button.is-hovered.docs-sourcelink{background-color:#335476;border-color:transparent;color:#fff}html.theme--documenter-dark .button.is-primary:focus,html.theme--documenter-dark .docstring>section>a.button.docs-sourcelink:focus,html.theme--documenter-dark .button.is-primary.is-focused,html.theme--documenter-dark .docstring>section>a.button.is-focused.docs-sourcelink{border-color:transparent;color:#fff}html.theme--documenter-dark 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.button.is-danger.is-inverted{background-color:#fff;border-color:transparent;box-shadow:none;color:#9e1b0d}html.theme--documenter-dark .button.is-danger.is-loading::after{border-color:transparent transparent #fff #fff !important}html.theme--documenter-dark .button.is-danger.is-outlined{background-color:transparent;border-color:#9e1b0d;color:#9e1b0d}html.theme--documenter-dark .button.is-danger.is-outlined:hover,html.theme--documenter-dark .button.is-danger.is-outlined.is-hovered,html.theme--documenter-dark .button.is-danger.is-outlined:focus,html.theme--documenter-dark .button.is-danger.is-outlined.is-focused{background-color:#9e1b0d;border-color:#9e1b0d;color:#fff}html.theme--documenter-dark .button.is-danger.is-outlined.is-loading::after{border-color:transparent transparent #9e1b0d #9e1b0d !important}html.theme--documenter-dark .button.is-danger.is-outlined.is-loading:hover::after,html.theme--documenter-dark .button.is-danger.is-outlined.is-loading.is-hovered::after,html.theme--documenter-dark .button.is-danger.is-outlined.is-loading:focus::after,html.theme--documenter-dark .button.is-danger.is-outlined.is-loading.is-focused::after{border-color:transparent transparent #fff #fff !important}html.theme--documenter-dark .button.is-danger.is-outlined[disabled],fieldset[disabled] html.theme--documenter-dark .button.is-danger.is-outlined{background-color:transparent;border-color:#9e1b0d;box-shadow:none;color:#9e1b0d}html.theme--documenter-dark .button.is-danger.is-inverted.is-outlined{background-color:transparent;border-color:#fff;color:#fff}html.theme--documenter-dark .button.is-danger.is-inverted.is-outlined:hover,html.theme--documenter-dark .button.is-danger.is-inverted.is-outlined.is-hovered,html.theme--documenter-dark .button.is-danger.is-inverted.is-outlined:focus,html.theme--documenter-dark .button.is-danger.is-inverted.is-outlined.is-focused{background-color:#fff;color:#9e1b0d}html.theme--documenter-dark .button.is-danger.is-inverted.is-outlined.is-loading:hover::after,html.theme--documenter-dark .button.is-danger.is-inverted.is-outlined.is-loading.is-hovered::after,html.theme--documenter-dark .button.is-danger.is-inverted.is-outlined.is-loading:focus::after,html.theme--documenter-dark .button.is-danger.is-inverted.is-outlined.is-loading.is-focused::after{border-color:transparent transparent #9e1b0d #9e1b0d !important}html.theme--documenter-dark .button.is-danger.is-inverted.is-outlined[disabled],fieldset[disabled] html.theme--documenter-dark .button.is-danger.is-inverted.is-outlined{background-color:transparent;border-color:#fff;box-shadow:none;color:#fff}html.theme--documenter-dark .button.is-small,html.theme--documenter-dark #documenter .docs-sidebar form.docs-search>input.button{border-radius:3px;font-size:.85em}html.theme--documenter-dark .button.is-normal{font-size:15px}html.theme--documenter-dark .button.is-medium{font-size:1.25rem}html.theme--documenter-dark .button.is-large{font-size:1.5rem}html.theme--documenter-dark .button[disabled],fieldset[disabled] html.theme--documenter-dark .button{background-color:#8c9b9d;border-color:#dbdee0;box-shadow:none;opacity:.5}html.theme--documenter-dark .button.is-fullwidth{display:flex;width:100%}html.theme--documenter-dark .button.is-loading{color:transparent !important;pointer-events:none}html.theme--documenter-dark .button.is-loading::after{position:absolute;left:calc(50% - (1em / 2));top:calc(50% - (1em / 2));position:absolute !important}html.theme--documenter-dark .button.is-static{background-color:#282f2f;border-color:#5e6d6f;color:#dbdee0;box-shadow:none;pointer-events:none}html.theme--documenter-dark .button.is-rounded,html.theme--documenter-dark #documenter .docs-sidebar form.docs-search>input.button{border-radius:290486px;padding-left:1em;padding-right:1em}html.theme--documenter-dark .buttons{align-items:center;display:flex;flex-wrap:wrap;justify-content:flex-start}html.theme--documenter-dark .buttons .button{margin-bottom:0.5rem}html.theme--documenter-dark .buttons .button:not(:last-child):not(.is-fullwidth){margin-right:0.5rem}html.theme--documenter-dark .buttons:last-child{margin-bottom:-0.5rem}html.theme--documenter-dark .buttons:not(:last-child){margin-bottom:1rem}html.theme--documenter-dark .buttons.are-small .button:not(.is-normal):not(.is-medium):not(.is-large){border-radius:3px;font-size:.85em}html.theme--documenter-dark .buttons.are-medium .button:not(.is-small):not(.is-normal):not(.is-large){font-size:1.25rem}html.theme--documenter-dark .buttons.are-large .button:not(.is-small):not(.is-normal):not(.is-medium){font-size:1.5rem}html.theme--documenter-dark .buttons.has-addons .button:not(:first-child){border-bottom-left-radius:0;border-top-left-radius:0}html.theme--documenter-dark .buttons.has-addons .button:not(:last-child){border-bottom-right-radius:0;border-top-right-radius:0;margin-right:-1px}html.theme--documenter-dark .buttons.has-addons .button:last-child{margin-right:0}html.theme--documenter-dark .buttons.has-addons .button:hover,html.theme--documenter-dark .buttons.has-addons .button.is-hovered{z-index:2}html.theme--documenter-dark .buttons.has-addons .button:focus,html.theme--documenter-dark .buttons.has-addons .button.is-focused,html.theme--documenter-dark .buttons.has-addons .button:active,html.theme--documenter-dark .buttons.has-addons .button.is-active,html.theme--documenter-dark .buttons.has-addons .button.is-selected{z-index:3}html.theme--documenter-dark .buttons.has-addons .button:focus:hover,html.theme--documenter-dark .buttons.has-addons .button.is-focused:hover,html.theme--documenter-dark .buttons.has-addons .button:active:hover,html.theme--documenter-dark .buttons.has-addons .button.is-active:hover,html.theme--documenter-dark .buttons.has-addons .button.is-selected:hover{z-index:4}html.theme--documenter-dark .buttons.has-addons .button.is-expanded{flex-grow:1;flex-shrink:1}html.theme--documenter-dark .buttons.is-centered{justify-content:center}html.theme--documenter-dark .buttons.is-centered:not(.has-addons) .button:not(.is-fullwidth){margin-left:0.25rem;margin-right:0.25rem}html.theme--documenter-dark .buttons.is-right{justify-content:flex-end}html.theme--documenter-dark .buttons.is-right:not(.has-addons) .button:not(.is-fullwidth){margin-left:0.25rem;margin-right:0.25rem}html.theme--documenter-dark .container{flex-grow:1;margin:0 auto;position:relative;width:auto}@media screen and (min-width: 1056px){html.theme--documenter-dark .container{max-width:992px}html.theme--documenter-dark .container.is-fluid{margin-left:32px;margin-right:32px;max-width:none}}@media screen and (max-width: 1215px){html.theme--documenter-dark .container.is-widescreen{max-width:1152px}}@media screen and (max-width: 1407px){html.theme--documenter-dark .container.is-fullhd{max-width:1344px}}@media screen and (min-width: 1216px){html.theme--documenter-dark .container{max-width:1152px}}@media screen and (min-width: 1408px){html.theme--documenter-dark .container{max-width:1344px}}html.theme--documenter-dark .content li+li{margin-top:0.25em}html.theme--documenter-dark .content p:not(:last-child),html.theme--documenter-dark .content dl:not(:last-child),html.theme--documenter-dark .content ol:not(:last-child),html.theme--documenter-dark .content ul:not(:last-child),html.theme--documenter-dark .content blockquote:not(:last-child),html.theme--documenter-dark .content pre:not(:last-child),html.theme--documenter-dark .content table:not(:last-child){margin-bottom:1em}html.theme--documenter-dark .content h1,html.theme--documenter-dark .content h2,html.theme--documenter-dark .content h3,html.theme--documenter-dark .content h4,html.theme--documenter-dark .content h5,html.theme--documenter-dark .content h6{color:#f2f2f2;font-weight:600;line-height:1.125}html.theme--documenter-dark .content h1{font-size:2em;margin-bottom:0.5em}html.theme--documenter-dark .content h1:not(:first-child){margin-top:1em}html.theme--documenter-dark .content h2{font-size:1.75em;margin-bottom:0.5714em}html.theme--documenter-dark .content h2:not(:first-child){margin-top:1.1428em}html.theme--documenter-dark .content h3{font-size:1.5em;margin-bottom:0.6666em}html.theme--documenter-dark .content h3:not(:first-child){margin-top:1.3333em}html.theme--documenter-dark .content h4{font-size:1.25em;margin-bottom:0.8em}html.theme--documenter-dark .content h5{font-size:1.125em;margin-bottom:0.8888em}html.theme--documenter-dark .content h6{font-size:1em;margin-bottom:1em}html.theme--documenter-dark .content blockquote{background-color:#282f2f;border-left:5px solid #5e6d6f;padding:1.25em 1.5em}html.theme--documenter-dark .content ol{list-style-position:outside;margin-left:2em;margin-top:1em}html.theme--documenter-dark .content ol:not([type]){list-style-type:decimal}html.theme--documenter-dark .content ol.is-lower-alpha:not([type]){list-style-type:lower-alpha}html.theme--documenter-dark .content ol.is-lower-roman:not([type]){list-style-type:lower-roman}html.theme--documenter-dark .content ol.is-upper-alpha:not([type]){list-style-type:upper-alpha}html.theme--documenter-dark .content ol.is-upper-roman:not([type]){list-style-type:upper-roman}html.theme--documenter-dark .content ul{list-style:disc outside;margin-left:2em;margin-top:1em}html.theme--documenter-dark .content ul ul{list-style-type:circle;margin-top:0.5em}html.theme--documenter-dark .content ul ul ul{list-style-type:square}html.theme--documenter-dark .content dd{margin-left:2em}html.theme--documenter-dark .content figure{margin-left:2em;margin-right:2em;text-align:center}html.theme--documenter-dark .content figure:not(:first-child){margin-top:2em}html.theme--documenter-dark .content figure:not(:last-child){margin-bottom:2em}html.theme--documenter-dark .content figure img{display:inline-block}html.theme--documenter-dark .content figure figcaption{font-style:italic}html.theme--documenter-dark .content pre{-webkit-overflow-scrolling:touch;overflow-x:auto;padding:0;white-space:pre;word-wrap:normal}html.theme--documenter-dark .content sup,html.theme--documenter-dark .content sub{font-size:75%}html.theme--documenter-dark .content table{width:100%}html.theme--documenter-dark .content table td,html.theme--documenter-dark .content table th{border:1px solid #5e6d6f;border-width:0 0 1px;padding:0.5em 0.75em;vertical-align:top}html.theme--documenter-dark .content table th{color:#f2f2f2}html.theme--documenter-dark .content table th:not([align]){text-align:left}html.theme--documenter-dark .content table thead td,html.theme--documenter-dark .content table thead th{border-width:0 0 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.image.is-square,html.theme--documenter-dark #documenter .docs-sidebar .docs-logo>img.is-square,html.theme--documenter-dark .image.is-1by1,html.theme--documenter-dark #documenter .docs-sidebar .docs-logo>img.is-1by1{padding-top:100%}html.theme--documenter-dark .image.is-5by4,html.theme--documenter-dark #documenter .docs-sidebar .docs-logo>img.is-5by4{padding-top:80%}html.theme--documenter-dark .image.is-4by3,html.theme--documenter-dark #documenter .docs-sidebar .docs-logo>img.is-4by3{padding-top:75%}html.theme--documenter-dark .image.is-3by2,html.theme--documenter-dark #documenter .docs-sidebar .docs-logo>img.is-3by2{padding-top:66.6666%}html.theme--documenter-dark .image.is-5by3,html.theme--documenter-dark #documenter .docs-sidebar .docs-logo>img.is-5by3{padding-top:60%}html.theme--documenter-dark .image.is-16by9,html.theme--documenter-dark #documenter .docs-sidebar .docs-logo>img.is-16by9{padding-top:56.25%}html.theme--documenter-dark .image.is-2by1,html.theme--documenter-dark #documenter .docs-sidebar .docs-logo>img.is-2by1{padding-top:50%}html.theme--documenter-dark .image.is-3by1,html.theme--documenter-dark #documenter .docs-sidebar .docs-logo>img.is-3by1{padding-top:33.3333%}html.theme--documenter-dark .image.is-4by5,html.theme--documenter-dark #documenter .docs-sidebar .docs-logo>img.is-4by5{padding-top:125%}html.theme--documenter-dark .image.is-3by4,html.theme--documenter-dark #documenter .docs-sidebar .docs-logo>img.is-3by4{padding-top:133.3333%}html.theme--documenter-dark .image.is-2by3,html.theme--documenter-dark #documenter .docs-sidebar .docs-logo>img.is-2by3{padding-top:150%}html.theme--documenter-dark .image.is-3by5,html.theme--documenter-dark #documenter .docs-sidebar .docs-logo>img.is-3by5{padding-top:166.6666%}html.theme--documenter-dark .image.is-9by16,html.theme--documenter-dark #documenter .docs-sidebar .docs-logo>img.is-9by16{padding-top:177.7777%}html.theme--documenter-dark .image.is-1by2,html.theme--documenter-dark #documenter 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Gets put into the tag.. +function set_theme_from_local_storage() { + // Intialize the theme to null, which means default + var theme = null; + // If the browser supports the localstorage and is not disabled then try to get the + // documenter theme + if(window.localStorage != null) { + // Get the user-picked theme from localStorage. May be `null`, which means the default + // theme. + theme = window.localStorage.getItem("documenter-theme"); + } + // Check if the browser supports user color preference + var darkPreference = false; + // Check if the users preference is for dark color scheme + if(window.matchMedia('(prefers-color-scheme: dark)').matches === true) { + darkPreference = true; + } + // Initialize a few variables for the loop: + // + // - active: will contain the index of the theme that should be active. Note that there + // is no guarantee that localStorage contains sane values. If `active` stays `null` + // we either could not find the theme or it is the default (primary) theme anyway. + // Either way, we then need to stick to the primary theme. + // + // - disabled: style sheets that should be disabled (i.e. all the theme style sheets + // that are not the currently active theme) + var active = null; var disabled = []; var darkTheme = null; + for (var i = 0; i < document.styleSheets.length; i++) { + var ss = document.styleSheets[i]; + // The tag of each style sheet is expected to have a data-theme-name attribute + // which must contain the name of the theme. The names in localStorage much match this. + var themename = ss.ownerNode.getAttribute("data-theme-name"); + // attribute not set => non-theme stylesheet => ignore + if(themename === null) continue; + // To distinguish the default (primary) theme, it needs to have the data-theme-primary + // attribute set. + var isprimary = (ss.ownerNode.getAttribute("data-theme-primary") !== null); + // Check if the theme is primary dark theme + var isDarkTheme = (ss.ownerNode.getAttribute("data-theme-primary-dark") !== null); + // If ss is for dark theme then set the value of darkTheme to the name of the theme + if(isDarkTheme) darkTheme = themename; + // If we find a matching theme (and it's not the default), we'll set active to non-null + if(themename === theme) active = i; + // Store the style sheets of inactive themes so that we could disable them + if(themename !== theme) disabled.push(ss); + } + if(active !== null) { + // If we did find an active theme, we'll (1) add the theme--$(theme) class to + document.getElementsByTagName('html')[0].className = "theme--" + theme; + // and (2) disable all the other theme stylesheets + disabled.forEach(function(ss){ + ss.disabled = true; + }); + } + else if(darkTheme !== null && darkPreference === true) { + // If we did find an active theme, we'll (1) add the theme--$(theme) class to + document.getElementsByTagName('html')[0].className = "theme--" + darkTheme; + // and (2) disable all the other theme stylesheets + disabled.forEach(function(ss){ + if (ss.ownerNode.getAttribute("data-theme-name") !== darkTheme) { + ss.disabled = true; + } + }); + } +} +set_theme_from_local_storage(); diff --git a/v0.24.1/assets/warner.js b/v0.24.1/assets/warner.js new file mode 100644 index 0000000000..5531c8851b --- /dev/null +++ b/v0.24.1/assets/warner.js @@ -0,0 +1,49 @@ +function maybeAddWarning () { + // DOCUMENTER_NEWEST is defined in versions.js, DOCUMENTER_CURRENT_VERSION and DOCUMENTER_STABLE + // in siteinfo.js. + // If either of these are undefined something went horribly wrong, so we abort. + if ( + window.DOCUMENTER_NEWEST === undefined || + window.DOCUMENTER_CURRENT_VERSION === undefined || + window.DOCUMENTER_STABLE === undefined + ) { + return + }; + + // Current version is not a version number, so we can't tell if it's the newest version. Abort. + if (!/v(\d+\.)*\d+/.test(window.DOCUMENTER_CURRENT_VERSION)) { + return + }; + + // Current version is newest version, so no need to add a warning. + if (window.DOCUMENTER_NEWEST === window.DOCUMENTER_CURRENT_VERSION) { + return + }; + + // Add a noindex meta tag (unless one exists) so that search engines don't index this version of the docs. + if (document.body.querySelector('meta[name="robots"]') === null) { + const meta = document.createElement('meta'); + meta.name = 'robots'; + meta.content = 'noindex'; + + document.getElementsByTagName('head')[0].appendChild(meta); + }; + + const div = document.createElement('div'); + div.classList.add('outdated-warning-overlay'); + const closer = document.createElement('button'); + closer.classList.add('outdated-warning-closer', 'delete'); + closer.addEventListener('click', function () { + document.body.removeChild(div); + }); + const href = window.documenterBaseURL + '/../' + window.DOCUMENTER_STABLE; + div.innerHTML = 'This documentation is not for the latest stable release, but for either the development version or an older release.
    Click here to go to the documentation for the latest stable release.'; + div.appendChild(closer); + document.body.appendChild(div); +}; + +if (document.readyState === 'loading') { + document.addEventListener('DOMContentLoaded', maybeAddWarning); +} else { + maybeAddWarning(); +}; diff --git a/v0.24.1/code_base_developer_guide/developer/index.html b/v0.24.1/code_base_developer_guide/developer/index.html new file mode 100644 index 0000000000..8452e09e63 --- /dev/null +++ b/v0.24.1/code_base_developer_guide/developer/index.html @@ -0,0 +1,2 @@ + +Developer Guide · PowerSimulations.jl
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    diff --git a/v0.24.1/code_base_developer_guide/extending_powersimulations/index.html b/v0.24.1/code_base_developer_guide/extending_powersimulations/index.html new file mode 100644 index 0000000000..465af5f007 --- /dev/null +++ b/v0.24.1/code_base_developer_guide/extending_powersimulations/index.html @@ -0,0 +1,36 @@ + +Extending Source Code Functionalities · PowerSimulations.jl
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    Extending Source Code Functionalities

    Enable other recorder events

    Other types of recorder events can be enabled with a possible performance impact. To do this pass in the specific recorder names to be enabled when you call build.

    sim = Simulation(...)
+recorders = [:execution]
+build!(sim; recorders = recorders)
+execute!(sim)

    Now we can examine InitialConditionUpdateEvents for specific steps and stages.

    show_simulation_events(
+    PSI.InitialConditionUpdateEvent,
+    "./output/aggregation/1",
+    x -> x.initial_condition_type == "DeviceStatus";
+    step = 2,
+    stage = 1
+)
+┌─────────────────────────────┬─────────────────────┬────────────────────────┬─────────────────┬─────────────┬─────┬──────────────┐
+│                        name │     simulation_time │ initial_condition_type │     device_type │ device_name │ val │ stage_number │
+├─────────────────────────────┼─────────────────────┼────────────────────────┼─────────────────┼─────────────┼─────┼──────────────┤
+│ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │           DeviceStatus │ ThermalStandard │    Solitude │ 0.0 │            1 │
+│ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │           DeviceStatus │ ThermalStandard │   Park City │ 1.0 │            1 │
+│ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │           DeviceStatus │ ThermalStandard │        Alta │ 1.0 │            1 │
+│ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │           DeviceStatus │ ThermalStandard │    Brighton │ 1.0 │            1 │
+│ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │           DeviceStatus │ ThermalStandard │    Sundance │ 0.0 │            1 │
+└─────────────────────────────┴─────────────────────┴────────────────────────┴─────────────────┴─────────────┴─────┴──────────────┘

    Show the wall time with your events

    Sometimes you might want to see how the events line up with the wall time.

    show_simulation_events(
+    PSI.InitialConditionUpdateEvent,
+    "./output/aggregation/1",
+    x -> x.initial_condition_type == "DeviceStatus";
+    step = 2,
+    stage = 1,
+    wall_time = true
+)
+┌─────────────────────────┬─────────────────────────────┬─────────────────────┬────────────────────────┬─────────────────┬─────────────┬─────┬──────────────┐
+│               timestamp │                        name │     simulation_time │ initial_condition_type │     device_type │ device_name │ val │ stage_number │
+├─────────────────────────┼─────────────────────────────┼─────────────────────┼────────────────────────┼─────────────────┼─────────────┼─────┼──────────────┤
+│ 2020-04-07T15:08:32.711 │ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │           DeviceStatus │ ThermalStandard │    Solitude │ 0.0 │            1 │
+│ 2020-04-07T15:08:32.711 │ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │           DeviceStatus │ ThermalStandard │   Park City │ 1.0 │            1 │
+│ 2020-04-07T15:08:32.711 │ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │           DeviceStatus │ ThermalStandard │        Alta │ 1.0 │            1 │
+│ 2020-04-07T15:08:32.711 │ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │           DeviceStatus │ ThermalStandard │    Brighton │ 1.0 │            1 │
+│ 2020-04-07T15:08:32.711 │ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │           DeviceStatus │ ThermalStandard │    Sundance │ 0.0 │            1 │
+└─────────────────────────┴─────────────────────────────┴─────────────────────┴────────────────────────┴─────────────────┴─────────────┴─────┴──────────────┘
    diff --git a/v0.24.1/code_base_developer_guide/troubleshooting/index.html b/v0.24.1/code_base_developer_guide/troubleshooting/index.html new file mode 100644 index 0000000000..88b66f4701 --- /dev/null +++ b/v0.24.1/code_base_developer_guide/troubleshooting/index.html @@ -0,0 +1,2 @@ + +Troubleshooting · PowerSimulations.jl diff --git a/v0.24.1/formulation_library/Branch/index.html b/v0.24.1/formulation_library/Branch/index.html new file mode 100644 index 0000000000..1e0c01807b --- /dev/null +++ b/v0.24.1/formulation_library/Branch/index.html @@ -0,0 +1,2 @@ + +Branch · PowerSimulations.jl
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    PowerSystems.Branch Formulations

    Valid DeviceModels for subtypes of Branch include the following:

    Valid DeviceModelDevice TypeFormulation
    DeviceModel(TModelHVDCLine, LossLessLine)TModelHVDCLineLossLessLine
    DeviceModel(PhaseShiftingTransformer, PhaseAngleControl)PhaseShiftingTransformerPhaseAngleControl
    DeviceModel(TwoTerminalHVDCLine, HVDCTwoTerminalDispatch)TwoTerminalHVDCLineHVDCTwoTerminalDispatch
    DeviceModel(TwoTerminalVSCDCLine, HVDCTwoTerminalDispatch)TwoTerminalVSCDCLineHVDCTwoTerminalDispatch
    DeviceModel(TwoTerminalHVDCLine, HVDCTwoTerminalLossless)TwoTerminalHVDCLineHVDCTwoTerminalLossless
    DeviceModel(TwoTerminalVSCDCLine, HVDCTwoTerminalLossless)TwoTerminalVSCDCLineHVDCTwoTerminalLossless
    DeviceModel(TwoTerminalHVDCLine, HVDCTwoTerminalUnbounded)TwoTerminalHVDCLineHVDCTwoTerminalUnbounded
    DeviceModel(TwoTerminalVSCDCLine, HVDCTwoTerminalUnbounded)TwoTerminalVSCDCLineHVDCTwoTerminalUnbounded
    DeviceModel(Line, StaticBranch)LineStaticBranch
    DeviceModel(MonitoredLine, StaticBranch)MonitoredLineStaticBranch
    DeviceModel(PhaseShiftingTransformer, StaticBranch)PhaseShiftingTransformerStaticBranch
    DeviceModel(TapTransformer, StaticBranch)TapTransformerStaticBranch
    DeviceModel(Transformer2W, StaticBranch)Transformer2WStaticBranch
    DeviceModel(TwoTerminalHVDCLine, StaticBranch)TwoTerminalHVDCLineStaticBranch
    DeviceModel(TwoTerminalVSCDCLine, StaticBranch)TwoTerminalVSCDCLineStaticBranch
    DeviceModel(Line, StaticBranchBounds)LineStaticBranchBounds
    DeviceModel(MonitoredLine, StaticBranchBounds)MonitoredLineStaticBranchBounds
    DeviceModel(PhaseShiftingTransformer, StaticBranchBounds)PhaseShiftingTransformerStaticBranchBounds
    DeviceModel(TapTransformer, StaticBranchBounds)TapTransformerStaticBranchBounds
    DeviceModel(Transformer2W, StaticBranchBounds)Transformer2WStaticBranchBounds
    DeviceModel(TwoTerminalHVDCLine, StaticBranchBounds)TwoTerminalHVDCLineStaticBranchBounds
    DeviceModel(TwoTerminalVSCDCLine, StaticBranchBounds)TwoTerminalVSCDCLineStaticBranchBounds
    DeviceModel(Line, StaticBranchUnbounded)LineStaticBranchUnbounded
    DeviceModel(MonitoredLine, StaticBranchUnbounded)MonitoredLineStaticBranchUnbounded
    DeviceModel(PhaseShiftingTransformer, StaticBranchUnbounded)PhaseShiftingTransformerStaticBranchUnbounded
    DeviceModel(TapTransformer, StaticBranchUnbounded)TapTransformerStaticBranchUnbounded
    DeviceModel(Transformer2W, StaticBranchUnbounded)Transformer2WStaticBranchUnbounded
    DeviceModel(TwoTerminalHVDCLine, StaticBranchUnbounded)TwoTerminalHVDCLineStaticBranchUnbounded
    DeviceModel(TwoTerminalVSCDCLine, StaticBranchUnbounded)TwoTerminalVSCDCLineStaticBranchUnbounded

    StaticBranch

    StaticBranchBounds

    StaticBranchUnbounded

    HVDCTwoTerminalLossless

    HVDCTwoTerminalDispatch

    HVDCTwoTerminalUnbounded

    diff --git a/v0.24.1/formulation_library/General/index.html b/v0.24.1/formulation_library/General/index.html new file mode 100644 index 0000000000..6535950541 --- /dev/null +++ b/v0.24.1/formulation_library/General/index.html @@ -0,0 +1,8 @@ + +General · PowerSimulations.jl
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    Formulations

    Modeling formulations are created by dispatching on abstract subtypes of PowerSimulations.AbstractDeviceFormulation

    FixedOutput

    Variables:

    No variables are created for DeviceModel(<:DeviceType, FixedOutput)

    Static Parameters:

    • ThermalGen:
      • $Pg^\text{max}$ = PowerSystems.get_max_active_power(device)
      • $Qg^\text{max}$ = PowerSystems.get_max_reactive_power(device)
    • Storage:
      • $Pg^\text{max}$ = PowerSystems.get_max_active_power(device)
      • $Qg^\text{max}$ = PowerSystems.get_max_reactive_power(device)

    Time Series Parameters:

    Device TypeParameterDefault Time Series Name
    RenewableGenReactivePowerTimeSeriesParametermax_active_power
    RenewableGenActivePowerTimeSeriesParametermax_active_power

    Objective:

    No objective terms are created for DeviceModel(<:DeviceType, FixedOutput)

    Expressions:

    Adds the active and reactive parameters listed for specific device types above to the respective active and reactive power balance expressions created by the selected Network Formulations

    Constraints:

    No constraints are created for DeviceModel(<:DeviceType, FixedOutput)

    VariableCost Options

    PowerSimulations can represent variable costs using a variety of different methods depending on the data available in each device. The following describes the objective function terms that are populated for each variable cost option.

    Scalar VariableCost

    variable_cost <: Float64: creates a fixed marginal cost term in the objective function

    \[\begin{aligned} +& \text{min} \sum_{t} C * G_t +\end{aligned}\]

    Polynomial VariableCost

    variable_cost <: Tuple{Float64, Float64}: creates a polynomial cost term in the objective function where

    • $C_g$=variable_cost[1]
    • $C_g^\prime$=variable_cost[2]

    \[\begin{aligned} +& \text{min} \sum_{t} C * G_t + C^\prime * G_t^2 +\end{aligned}\]

    Piecewise Linear VariableCost

    variable_cost <: Vector{Tuple{Float64, Float64}}: creates a piecewise linear cost term in the objective function

    TODO: add formulation

    ___

    StorageManagementCost

    Adds an objective function cost term according to:

    \[\begin{aligned} +& \text{min} \sum_{t} \quad [E^{surplus}_t * C^{penalty} - E^{shortage}_t * C^{value}] +\end{aligned}\]

    Impact of different cost configurations:

    The following table describes all possible configuration of the StorageManagementCost with the target constraint in hydro or storage device models. Cases 1(a) & 2(a) will have no impact of the models operations and the target constraint will be rendered useless. In most cases that have no energy target and a non-zero value for $C^{value}$, if this cost is too high ($C^{value} >> 0$) or too low ($C^{value} <<0$) can result in either the model holding on to stored energy till the end or the model not storing any energy in the device. This is caused by the fact that when energy target is zero, we have $E_t = - E^{shortage}_t$, and $- E^{shortage}_t * C^{value}$ in the objective function is replaced by $E_t * C^{value}$, thus resulting in $C^{value}$ to be seen as the cost of stored energy.

    CaseEnergy TargetEnergy Shortage CostEnergy Value / Energy Surplus costEffect
    Case 1(a)$\hat{E}=0$$C^{penalty}=0$$C^{value}=0$no change
    Case 1(b)$\hat{E}=0$$C^{penalty}=0$$C^{value}<0$penalty for storing energy
    Case 1(c)$\hat{E}=0$$C^{penalty}>0$$C^{value}=0$no penalties or incentives applied
    Case 1(d)$\hat{E}=0$$C^{penalty}=0$$C^{value}>0$incentive for storing energy
    Case 1(e)$\hat{E}=0$$C^{penalty}>0$$C^{value}<0$penalty for storing energy
    Case 1(f)$\hat{E}=0$$C^{penalty}>0$$C^{value}>0$incentive for storing energy
    Case 2(a)$\hat{E}>0$$C^{penalty}=0$$C^{value}=0$no change
    Case 2(b)$\hat{E}>0$$C^{penalty}=0$$C^{value}<0$penalty on energy storage in excess of target
    Case 2(c)$\hat{E}>0$$C^{penalty}>0$$C^{value}=0$penalty on energy storage short of target
    Case 2(d)$\hat{E}>0$$C^{penalty}=0$$C^{value}>0$incentive on excess energy
    Case 2(e)$\hat{E}>0$$C^{penalty}>0$$C^{value}<0$penalty on both excess/shortage of energy
    Case 2(f)$\hat{E}>0$$C^{penalty}>0$$C^{value}>0$penalty for shortage, incentive for excess energy
    diff --git a/v0.24.1/formulation_library/Load/index.html b/v0.24.1/formulation_library/Load/index.html new file mode 100644 index 0000000000..ca55f78961 --- /dev/null +++ b/v0.24.1/formulation_library/Load/index.html @@ -0,0 +1,10 @@ + +Load · PowerSimulations.jl
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    PowerSystems.ElectricLoad Formulations

    Valid DeviceModels for subtypes of ElectricLoad include the following:

    Valid DeviceModelDevice TypeFormulation
    DeviceModel(InterruptiblePowerLoad, PowerLoadDispatch)InterruptiblePowerLoadPowerLoadDispatch
    DeviceModel(PowerLoad, PowerLoadDispatch)PowerLoadPowerLoadDispatch
    DeviceModel(PowerSystems.ExponentialLoad, PowerLoadDispatch)PowerSystems.ExponentialLoadPowerLoadDispatch
    DeviceModel(StandardLoad, PowerLoadDispatch)StandardLoadPowerLoadDispatch
    DeviceModel(InterruptiblePowerLoad, PowerLoadInterruption)InterruptiblePowerLoadPowerLoadInterruption
    DeviceModel(PowerLoad, PowerLoadInterruption)PowerLoadPowerLoadInterruption
    DeviceModel(PowerSystems.ExponentialLoad, PowerLoadInterruption)PowerSystems.ExponentialLoadPowerLoadInterruption
    DeviceModel(StandardLoad, PowerLoadInterruption)StandardLoadPowerLoadInterruption
    DeviceModel(InterruptiblePowerLoad, StaticPowerLoad)InterruptiblePowerLoadStaticPowerLoad
    DeviceModel(FixedAdmittance, StaticPowerLoad)FixedAdmittanceStaticPowerLoad
    DeviceModel(PowerSystems.SwitchedAdmittance, StaticPowerLoad)PowerSystems.SwitchedAdmittanceStaticPowerLoad
    DeviceModel(PowerLoad, StaticPowerLoad)PowerLoadStaticPowerLoad
    DeviceModel(PowerSystems.ExponentialLoad, StaticPowerLoad)PowerSystems.ExponentialLoadStaticPowerLoad
    DeviceModel(StandardLoad, StaticPowerLoad)StandardLoadStaticPowerLoad

    StaticPowerLoad

    Variables:

    No variables are created

    Time Series Parameters:

    ParameterDefault Time Series Name
    ReactivePowerTimeSeriesParametermax_active_power
    ActivePowerTimeSeriesParametermax_active_power

    Expressions:

    Subtracts the parameters listed above from the respective active and reactive power balance expressions created by the selected Network Formulations

    Constraints:

    No constraints are created

    PowerLoadInterruption

    Variables:

    Time Series Parameters:

    ParameterDefault Time Series Name
    ReactivePowerTimeSeriesParametermax_active_power
    ActivePowerTimeSeriesParametermax_active_power

    Objective:

    Creates an objective function term based on the VariableCost Options where the quantity term is defined as $Pg$.

    Expressions:

    • Adds $Pg$ and $Qg$ terms and to the respective active and reactive power balance expressions created by the selected Network Formulations
    • Subtracts the time series parameters listed above terms from the respective active and reactive power balance expressions created by the selected Network Formulations

    Constraints:

    $Pg$ and $Qg$ represent the "unserved" active and reactive power loads

    \[\begin{aligned} +& Pg_t \le ActivePowerTimeSeriesParameter_t\\ +& Pg_t - u_t ActivePowerTimeSeriesParameter_t \le 0 \\ +& Qg_t \le ReactivePowerTimeSeriesParameter_t\\ +& Qg_t - u_t ReactivePowerTimeSeriesParameter_t\le 0 +\end{aligned}\]

    PowerLoadDispatch

    Variables:

    Time Series Parameters:

    ParameterDefault Time Series Name
    ReactivePowerTimeSeriesParametermax_active_power
    ActivePowerTimeSeriesParametermax_active_power

    Objective:

    Creates an objective function term based on the VariableCost Options where the quantity term is defined as $Pg$.

    Expressions:

    • Adds $Pg$ and $Qg$ terms and to the respective active and reactive power balance expressions created by the selected Network Formulations
    • Subtracts the time series parameters listed above terms from the respective active and reactive power balance expressions created by the selected Network Formulations

    Constraints:

    $Pg$ and $Qg$ represent the "unserved" active and reactive power loads

    \[\begin{aligned} +& Pg_t \le ActivePowerTimeSeriesParameter_t\\ +& Qg_t \le ReactivePowerTimeSeriesParameter_t\\ +\end{aligned}\]

    diff --git a/v0.24.1/formulation_library/Network/index.html b/v0.24.1/formulation_library/Network/index.html new file mode 100644 index 0000000000..5f589a46d7 --- /dev/null +++ b/v0.24.1/formulation_library/Network/index.html @@ -0,0 +1,2 @@ + +Network · PowerSimulations.jl diff --git a/v0.24.1/formulation_library/README/index.html b/v0.24.1/formulation_library/README/index.html new file mode 100644 index 0000000000..dcc08e24c2 --- /dev/null +++ b/v0.24.1/formulation_library/README/index.html @@ -0,0 +1,2 @@ + +Formulation documentation guide · PowerSimulations.jl
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    Formulation documentation guide

    Formulation documentation should roughly follow the template established by RenewableGen.md

    Auto generated items

    • Valid DeviceModel table: just change the device category in the filter function
    • Time Series Parameters: just change the device category and formulation in the get_default_time_series_names method call

    Linked items

    • Formulations in the Valid DeviceModel table must have a docstring in src/core/formulations.jl
    • The Formulation in the @docs block must have a docstring in src/core/formulations.jl
    • The Variables must have docstrings in src/core/variables.jl
    • The Time Series Parameters must have docstrings in src/core/parameters.jl
    diff --git a/v0.24.1/formulation_library/RenewableGen/index.html b/v0.24.1/formulation_library/RenewableGen/index.html new file mode 100644 index 0000000000..61f9a1ad1e --- /dev/null +++ b/v0.24.1/formulation_library/RenewableGen/index.html @@ -0,0 +1,9 @@ + +Renewable Generation · PowerSimulations.jl
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    PowerSystems.RenewableGen Formulations

    Valid DeviceModels for subtypes of RenewableGen include the following:

    Valid DeviceModelDevice TypeFormulation
    DeviceModel(RenewableDispatch, FixedOutput)RenewableDispatchFixedOutput
    DeviceModel(RenewableFix, FixedOutput)RenewableFixFixedOutput
    DeviceModel(RenewableDispatch, RenewableConstantPowerFactor)RenewableDispatchRenewableConstantPowerFactor
    DeviceModel(RenewableFix, RenewableConstantPowerFactor)RenewableFixRenewableConstantPowerFactor
    DeviceModel(RenewableDispatch, RenewableFullDispatch)RenewableDispatchRenewableFullDispatch
    DeviceModel(RenewableFix, RenewableFullDispatch)RenewableFixRenewableFullDispatch

    RenewableFullDispatch

    Variables:

    Static Parameters:

    • $Pg^\text{min}$ = PowerSystems.get_active_power_limits(device).min
    • $Qg^\text{min}$ = PowerSystems.get_reactive_power_limits(device).min
    • $Qg^\text{max}$ = PowerSystems.get_reactive_power_limits(device).max

    Time Series Parameters:

    ParameterDefault Time Series Name
    ReactivePowerTimeSeriesParametermax_active_power
    ActivePowerTimeSeriesParametermax_active_power

    Objective:

    Creates an objective function term based on the VariableCost Options where the quantity term is defined as $- Pg_t$ to incentivize generation from RenewableGen devices.

    Expressions:

    Adds $Pg$ and $Qg$ terms to the respective active and reactive power balance expressions created by the selected Network Formulations

    Constraints:

    \[\begin{aligned} +& Pg^\text{min} \le Pg_t \le ActivePowerTimeSeriesParameter_t \\ +& Qg^\text{min} \le Qg_t \le Qg^\text{max} +\end{aligned}\]

    RenewableConstantPowerFactor

    Variables:

    Static Parameters:

    • $Pg^\text{min}$ = PowerSystems.get_active_power_limits(device).min
    • $Qg^\text{min}$ = PowerSystems.get_reactive_power_limits(device).min
    • $Qg^\text{max}$ = PowerSystems.get_reactive_power_limits(device).max
    • $pf$ = PowerSystems.get_power_factor(device)

    Time Series Parameters:

    ParameterDefault Time Series Name
    ReactivePowerTimeSeriesParametermax_active_power
    ActivePowerTimeSeriesParametermax_active_power

    Objective:

    Creates an objective function term based on the VariableCost Options where the quantity term is defined as $- Pg_t$ to incentivize generation from RenewableGen devices.

    Expressions:

    Adds $Pg$ and $Qg$ terms to the respective active and reactive power balance expressions created by the selected Network Formulations

    Constraints:

    \[\begin{aligned} +& Pg^\text{min} \le Pg_t \le ActivePowerTimeSeriesParameter_t \\ +& Qg^\text{min} \le Qg_t \le Qg^\text{max} \\ +& Qg_t = pf * Pg_t +\end{aligned}\]

    diff --git a/v0.24.1/formulation_library/Service/index.html b/v0.24.1/formulation_library/Service/index.html new file mode 100644 index 0000000000..0b1f404b77 --- /dev/null +++ b/v0.24.1/formulation_library/Service/index.html @@ -0,0 +1,2 @@ + +PowerSystems.Service Formulations · PowerSimulations.jl diff --git a/v0.24.1/formulation_library/ThermalGen/index.html b/v0.24.1/formulation_library/ThermalGen/index.html new file mode 100644 index 0000000000..1c70dd85b2 --- /dev/null +++ b/v0.24.1/formulation_library/ThermalGen/index.html @@ -0,0 +1,2 @@ + +Thermal Generation · PowerSimulations.jl
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    ThermalGen Formulations

    Valid DeviceModels for subtypes of ThermalGen include the following:

    Valid DeviceModelDevice TypeFormulation
    DeviceModel(ThermalMultiStart, FixedOutput)ThermalMultiStartFixedOutput
    DeviceModel(ThermalStandard, FixedOutput)ThermalStandardFixedOutput
    DeviceModel(ThermalMultiStart, ThermalBasicDispatch)ThermalMultiStartThermalBasicDispatch
    DeviceModel(ThermalStandard, ThermalBasicDispatch)ThermalStandardThermalBasicDispatch
    DeviceModel(ThermalMultiStart, ThermalCompactDispatch)ThermalMultiStartThermalCompactDispatch
    DeviceModel(ThermalStandard, ThermalCompactDispatch)ThermalStandardThermalCompactDispatch
    DeviceModel(ThermalMultiStart, ThermalDispatchNoMin)ThermalMultiStartThermalDispatchNoMin
    DeviceModel(ThermalStandard, ThermalDispatchNoMin)ThermalStandardThermalDispatchNoMin
    DeviceModel(ThermalMultiStart, ThermalStandardDispatch)ThermalMultiStartThermalStandardDispatch
    DeviceModel(ThermalStandard, ThermalStandardDispatch)ThermalStandardThermalStandardDispatch
    DeviceModel(ThermalMultiStart, ThermalBasicCompactUnitCommitment)ThermalMultiStartThermalBasicCompactUnitCommitment
    DeviceModel(ThermalStandard, ThermalBasicCompactUnitCommitment)ThermalStandardThermalBasicCompactUnitCommitment
    DeviceModel(ThermalMultiStart, ThermalCompactUnitCommitment)ThermalMultiStartThermalCompactUnitCommitment
    DeviceModel(ThermalStandard, ThermalCompactUnitCommitment)ThermalStandardThermalCompactUnitCommitment
    DeviceModel(ThermalMultiStart, ThermalMultiStartUnitCommitment)ThermalMultiStartThermalMultiStartUnitCommitment
    DeviceModel(ThermalMultiStart, ThermalBasicUnitCommitment)ThermalMultiStartThermalBasicUnitCommitment
    DeviceModel(ThermalStandard, ThermalBasicUnitCommitment)ThermalStandardThermalBasicUnitCommitment
    DeviceModel(ThermalMultiStart, ThermalStandardUnitCommitment)ThermalMultiStartThermalStandardUnitCommitment
    DeviceModel(ThermalStandard, ThermalStandardUnitCommitment)ThermalStandardThermalStandardUnitCommitment

    ThermalBasicDispatch

    TODO

    ThermalCompactDispatch

    TODO

    ThermalDispatchNoMin

    TODO

    ThermalStandardDispatch

    TODO

    ThermalBasicCompactUnitCommitment

    TODO

    ThermalCompactUnitCommitment

    TODO

    ThermalMultiStartUnitCommitment

    TODO

    ThermalBasicUnitCommitment

    TODO

    ThermalStandardUnitCommitment

    TODO

    diff --git a/v0.24.1/get_test_data.jl b/v0.24.1/get_test_data.jl new file mode 100644 index 0000000000..2c99e65808 --- /dev/null +++ b/v0.24.1/get_test_data.jl @@ -0,0 +1,41 @@ +using Cbc +using PowerSimulations +using PowerSystems +using DataStructures +using InfrastructureSystems +const IS = InfrastructureSystems +const PSI = PowerSimulations +const PSY = PowerSystems + +include("../../../test/test_utils/get_test_data.jl") + +abstract type TestOpProblem <: PSI.DefaultDecisionProblem end + +system = build_c_sys5_re(; add_reserves = true) +solver = optimizer_with_attributes(Cbc.Optimizer) + +devices = Dict{Symbol, DeviceModel}( + :Generators => DeviceModel(ThermalStandard, ThermalBasicDispatch), + :Loads => DeviceModel(PowerLoad, StaticPowerLoad), +) +branches = Dict{Symbol, DeviceModel}( + :L => DeviceModel(Line, StaticLine), + :T => DeviceModel(Transformer2W, StaticBranch), + :TT => DeviceModel(TapTransformer, StaticBranch), +); +services = Dict{Symbol, ServiceModel}(); + +template = PSI.ProblemTemplate(CopperPlatePowerModel, devices, branches, services); + +operation_problem = PSI.DecisionModel(TestOpProblem, template, system; optimizer = solver); + +set_services_template!( + operation_problem, + Dict( + :Reserve => ServiceModel(VariableReserve{ReserveUp}, RangeReserve), + :Down_Reserve => ServiceModel(VariableReserve{ReserveDown}, RangeReserve), + ), +) + +op_results = solve!(operation_problem) +re_results = PSI.run_economic_dispatch(system; optimizer = solver, use_parameters = true) diff --git a/v0.24.1/index.html b/v0.24.1/index.html new file mode 100644 index 0000000000..be72dd5a47 --- /dev/null +++ b/v0.24.1/index.html @@ -0,0 +1,2 @@ + +Welcome Page · PowerSimulations.jl
    Edit on GitHub

    PowerSimulations.jl

    Overview

    PowerSimulations.jl is a power system operations simulation tool developed as a flexible and open source software for quasi-static power systems simulations including Production Cost Models. PowerSimulations.jl tackles the issues of developing a simulation model in a modular way providing tools for the formulation of decision models and emulation models that can be solved independently or in an interconnected fashion.

    PowerSimulations.jl supports the workflows to develop simulations by separating the development of operations models and simulation models.

    • Operation Models: Optimization model used to find the solution of an operation problem.
    • Simulations Models: Defined the requirements to find solutions to a sequence of operation problems in a way that resembles the procedures followed by operators.

    The most common Simulation Model is the solution of a Unit Commitment and Economic Dispatch sequence of problems. This model is used in commercial Production Cost Modeling tools, but it has a limited scope of analysis.

    How the documentation is structured

    PowerSimulations.jl documentation and code are organized according to the needs of different users depending on their skillset and requirements. In broad terms there are three categories:

    • Modeler: Users that want to solve an operations problem or run a simulation using the existing models in PowerSimulations.jl. For instance, answer questions about the change in operation costs in future fuel mixes. Check the formulations library page to choose a modeling strategy that fits your needs.

    • Model Developer: Users that want to develop custom models and workflows for the simulation of a power system operation. For instance, study the impacts of an stochastic optimization problem over a deterministic.

    • Code Base Developers: Users that want to add new core functionalities or fix bugs in the core capabilities of PowerSimulations.jl.

    PowerSimulations.jl is an active project under development, and we welcome your feedback, suggestions, and bug reports.

    Note: PowerSimulations.jl uses the data model implemented in PowerSystems.jl to construct optimization models. In most cases, you need to add PowerSystems.jl to your scripts.

    Installation

    The latest stable release of PowerSimulations can be installed using the Julia package manager with

    ] add PowerSimulations

    For the current development version, "checkout" this package with

    ] add PowerSimulations#main

    An appropriate optimization solver is required for running PowerSimulations models. Refer to JuMP.jl solver's page to select the most appropriate for the application of interest.

    PowerSystems has been developed as part of the Scalable Integrated Infrastructure Planning (SIIP) initiative at the U.S. Department of Energy's National Renewable Energy Laboratory (NREL).

    diff --git a/v0.24.1/model_developer_guide/structure_of_operation_problem/index.html b/v0.24.1/model_developer_guide/structure_of_operation_problem/index.html new file mode 100644 index 0000000000..a931ee28c2 --- /dev/null +++ b/v0.24.1/model_developer_guide/structure_of_operation_problem/index.html @@ -0,0 +1,26 @@ + +Operation Problem Structure · PowerSimulations.jl
    Edit on GitHub

    Structure of an operations problem model

    In most cases operation problem models are optimization models. Although in PowerSimulations.jl it is possible to define arbitrary problems that can reflect heuristic decision rules, this is not the common case. This page focuses on explaining the structure of operations problems that employ an optimization problem and solver.

    The first aspect to consider when thinking about developing a model compatible with PowerSimulations.jl is that although we support all of JuMP.jl objects, you need to employ anonymous constraints and variables in JuMP and register the constraints, variables and other optimization objects into PowerSimulations.jl's optimization container. Otherwise the features to use your problem in the simulation like the coordination with other problems and post processing won't work.

    Info

    The requirements for the simulation of Power Systems operations are more strict than solving an optimization problem once with just JuMP.jl. The requirements imposed by PowerSimulations.jl to integrate your models in a simulation are designed to help with other complex operations that go beyond JuMP.jl scope.

    Warning

    All the code in this page is considered "pseudo-code". Copy-paste will likely not work out of the box. You need to develop the internals of the functions correctly for the examples below to work.

    Registering a variable in the model

    To register a variable in the model, the developer must first allocate the container into the optimization container and then populate it. For example, it require start the build function as follows:

    Info

    We recommend calling import PowerSimulations and defining the constant CONST PSI = PowerSimulations to make it easier to read the code and determine which package is responsible for defining the functions.

        function PSI.build_model!(model::PSI.DecisionModel{MyCustomModel})
+        container = PSI.get_optimization_container(model)
+        PSI.set_time_steps!(container, 1:24)
+
+        # Create the container for the variable
+        variable = PSI.add_variable_container!(
+            container,
+            PSI.ActivePowerVariable(), # <- This variable is defined in PowerSimulations but the user can define their own
+            PSY.ThermalGeneration, # <- Device type for the variable. Can be from PSY or custom defined
+            devices_names, # <- First container dimension
+            time_steps, # <- Second container dimension
+        )
+
+        # Iterate over the devices and time to store the JuMP variables into the container.
+        for t in time_steps, d in devices
+            name = PSY.get_name(d)
+            variable[name, t] = JuMP.@variable(get_jump_model(container))
+            # It is possible to use PSY getter functions to retrieve data from the generators
+            # Any other variable property can be specified inside this loop.
+            JuMP.set_upper_bound(variable[name, t], UB_DATA) # <- Optional
+            JuMP.set_lower_bound(variable[name, t], LB_DATA) # <- Optional
+        end
+
+    return
+    end
    diff --git a/v0.24.1/model_developer_guide/troubleshooting/index.html b/v0.24.1/model_developer_guide/troubleshooting/index.html new file mode 100644 index 0000000000..72f0b6e4af --- /dev/null +++ b/v0.24.1/model_developer_guide/troubleshooting/index.html @@ -0,0 +1,2 @@ + +Troubleshooting · PowerSimulations.jl diff --git a/v0.24.1/modeler_guide/debugging_infeasible_models/index.html b/v0.24.1/modeler_guide/debugging_infeasible_models/index.html new file mode 100644 index 0000000000..0e906608cd --- /dev/null +++ b/v0.24.1/modeler_guide/debugging_infeasible_models/index.html @@ -0,0 +1,2 @@ + +Debugging infeasible models · PowerSimulations.jl diff --git a/v0.24.1/modeler_guide/definitions/index.html b/v0.24.1/modeler_guide/definitions/index.html new file mode 100644 index 0000000000..2a6a6ec388 --- /dev/null +++ b/v0.24.1/modeler_guide/definitions/index.html @@ -0,0 +1,2 @@ + +Definitions · PowerSimulations.jl
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    Definitions

    D

    • Decision Problem: A decision problem calculates the desired system operation based on forecasts of uncertain inputs and information about the state of the system. The output of a decision problem represents the policies used to drive the set-points of the system's devices, like generators or switches, and depends on the purpose of the problem. See the Decision Model Tutorial to learn more about solving individual problems.

    • Device Formulation: The model of a device that is incorporated into a large system optimization models. For instance, the storage device model used inside of a Unit Commitment (UC) problem. A device model needs to follow some requirements to be integrated into operation problems.

    E

    • Emulation Problem: An emulation problem is used to mimic the system's behavior subject to an incoming decision and the realization of a forecasted inputs. The solution of the emulator produces outputs representative of the system performance when operating subject the policies resulting from the decision models.

    H

    I

    • Interval: The amount of time between updates to the decision problem. For instance, Day-Ahead problems usually have a 24-hour intervals and Real-Time problems have 5-minute intervals. Check the time Time Series Data Section in PowerSystems.jl

    R

    • Resolution: The amount of time between timesteps in a simulation. For instance 1-hour or 5-minutes. In Julia these are defined using the syntax Hour(1) and Minute(5). Check the time Time Series Data Section in PowerSystems.jl
    diff --git a/v0.24.1/modeler_guide/logging/index.html b/v0.24.1/modeler_guide/logging/index.html new file mode 100644 index 0000000000..0aa099ef7c --- /dev/null +++ b/v0.24.1/modeler_guide/logging/index.html @@ -0,0 +1,11 @@ + +Logging · PowerSimulations.jl
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    Logging

    PowerSimulations.jl will output many log messages when building systems and running simulations. You may want to customize what gets logged to the console and, optionally, a file.

    By default all log messages of level Logging.Info or higher will get displayed to the console. When you run a simulation a simulation-specific logger will take over and log its messages to a file in the logs directory in the simulation output directory. When finished it will relinquish control back to the global logger.

    Configuring the global logger

    To configure the global logger in a Jupyter Notebook or REPL you may configure your own logger with the Julia Logging standard library or use the convenience function provided by PowerSimulations. This example will log messages of level Logging.Error to console and Logging.Info and higher to the file power-simulations.log in the current directory.

    import Logging
+using PowerSimulations
+logger = configure_logging(
+    console_level = Logging.Error,
+    file_level = Logging.Info,
+    filename = "power-simulations.log"
+)

    Configuring the simulation logger

    You can configure the logging level used by the simulation logger when you call build!(simulation). Here is an example that increases logging verbosity:

    import Logging
+using PowerSimulations
+simulation = Simulation(...)
+build!(simulation, console_level = Logging.Info, file_level = Logging.Debug)

    The log file will be located at <your-output-path>/<simulation-name>/<run-output-dir>/logs/simulation.log.

    Solver logs

    You can configure logging for the solver you use. Refer to the solver documentation. PowerSimulations does not redirect or intercept prints to stdout or stderr from other libraries.

    Recorder events

    PowerSimulations uses the InfrastructureSystems.Recorder to store simulation events in a log file. Refer to this link for more information.

    diff --git a/v0.24.1/modeler_guide/modeling_faq/index.html b/v0.24.1/modeler_guide/modeling_faq/index.html new file mode 100644 index 0000000000..db97f7fb0c --- /dev/null +++ b/v0.24.1/modeler_guide/modeling_faq/index.html @@ -0,0 +1,2 @@ + +Modeling FAQ · PowerSimulations.jl
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    Modeling FAQ

    How do I reduce the amount of print on my REPL?

    The print to the REPL is controlled with the logging. Check the Logging documentation page to see how to reduce the print out

    How do I print the optimizer logs to see the solution process?

    When specifying the DecisionModel or EmulationModel pass the keyword print_optimizer_log = true

    diff --git a/v0.24.1/modeler_guide/parallel_simulations/index.html b/v0.24.1/modeler_guide/parallel_simulations/index.html new file mode 100644 index 0000000000..df54a90b9e --- /dev/null +++ b/v0.24.1/modeler_guide/parallel_simulations/index.html @@ -0,0 +1,105 @@ + +Parallel Simulations · PowerSimulations.jl
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    Parallel Simulations

    This section contains instructions to:

    Run a Simulation in Parallel on a local computer

    This page describes how to split a simulation into partitions, run each partition in parallel, and then join the results.

    Setup

    Create a Julia script to build and run simulations. It must meet the requirements below. A full example is in the PowerSimulations repository in test/run_partitioned_simulation.jl.

    • Call using PowerSimulations.

    • Implement a build function that matches the signature below. It must construct a Simulation, call build!, and then return the Simulation instance. It must throw an exception if the build fails.

    function build_simulation(
+    output_dir::AbstractString,
+    simulation_name::AbstractString,
+    partitions::SimulationPartitions,
+    index::Union{Nothing, Integer}=nothing,
+)

    Here is example code to construct the Simulation with these parameters:

        sim = Simulation(
+        name=simulation_name,
+        steps=partitions.num_steps,
+        models=models,
+        sequence=sequence,
+        simulation_folder=output_dir,
+    )
+    status = build!(sim; partitions=partitions, index=index, serialize=isnothing(index))
+    if status != PSI.BuildStatus.BUILT
+        error("Failed to build simulation: status=$status")
+    end
    • Implement an execute function that matches the signature below. It must throw an exception if the execute fails.
    function execute_simulation(sim, args...; kwargs...)
+    status = execute!(sim)
+    if status != PSI.RunStatus.SUCCESSFUL
+        error("Simulation failed to execute: status=$status")
+    end
+end

    Execution

    After loading your script, call the function run_parallel_simulation as shown below.

    This example splits a year-long simulation into weekly partitions for a total of 53 individual jobs and then runs them four at a time.

    julia> include("my_simulation.jl")
+julia> run_parallel_simulation(
+        build_simulation,
+        execute_simulation,
+        script="my_simulation.jl",
+        output_dir="my_simulation_output",
+        name="my_simulation",
+        num_steps=365,
+        period=7,
+        num_overlap_steps=1,
+        num_parallel_processes=4,
+        exeflags="--project=<path-to-your-julia-environment>",
+    )

    The final results will be in ./my_simulation_otuput/my_simulation

    Note the log files and results for each partition are located in ./my_simulation_otuput/my_simulation/simulation_partitions

    Run a Simulation in Parallel on an HPC

    This page describes how to split a simulation into partitions, run each partition in parallel on HPC compute nodes, and then join the results.

    These steps can be used on a local computer or any HPC supported by the submission software. Some steps may be specific to NREL's HPC Eagle cluster.

    Note: Some instructions are preliminary and will change if functionality is moved to a new Julia package.

    Setup

    1. Create a conda environment and install the Python package NREL-jade: https://nrel.github.io/jade/installation.html. The rest of this page assumes that the environment is called jade.
    2. Activate the environment with conda activate jade.
    3. Locate the path to that conda environment. It will likely be ~/.conda-envs/jade or ~/.conda/envs/jade.
    4. Load the Julia environment that you use to run simulations. Add the packages Conda and PyCall.
    5. Setup Conda to use the existing jade environment by running these commands:
    julia> run(`conda create -n conda_jl python conda`)
+julia> ENV["CONDA_JL_HOME"] = joinpath(ENV["HOME"], ".conda-envs", "jade")  # change this to your path
+pkg> build Conda
    1. Copy the code below into a Julia file called configure_parallel_simulation.jl. This is an interface to Jade through PyCall. It will be used to create a Jade configuration. (It may eventually be moved to a separate package.)
    function configure_parallel_simulation(
+    script::AbstractString,
+    num_steps::Integer,
+    num_period_steps::Integer;
+    num_overlap_steps::Integer=0,
+    project_path=nothing,
+    simulation_name="simulation",
+    config_file="config.json",
+    force=false,
+)
+    partitions = SimulationPartitions(num_steps, num_period_steps, num_overlap_steps)
+    jgc = pyimport("jade.extensions.generic_command")
+    julia_cmd = isnothing(project_path) ? "julia" : "julia --project=$project_path"
+    setup_command = "$julia_cmd $script setup --simulation-name=$simulation_name " *
+    "--num-steps=$num_steps --num-period-steps=$num_period_steps " *
+    "--num-overlap-steps=$num_overlap_steps"
+    teardown_command = "$julia_cmd $script join --simulation-name=$simulation_name"
+    config = jgc.GenericCommandConfiguration(
+        setup_command=setup_command,
+        teardown_command=teardown_command,
+    )
+
+    for i in 1:get_num_partitions(partitions)
+        cmd = "$julia_cmd $script execute --simulation-name=$simulation_name --index=$i"
+        job = jgc.GenericCommandParameters(command=cmd, name="execute-$i")
+        config.add_job(job)
+    end
+
+    config.dump(config_file, indent=2)
+    println("Created Jade configuration in $config_file. " *
+            "Run 'jade submit-jobs [options] $config_file' to execute them.")
+end
    1. Create a Julia script to build and run simulations. It must meet the requirements below. A full example is in the PowerSimulations repository in test/run_partitioned_simulation.jl.

    • Call using PowerSimulations.

    • Implement a build function that matches the signature below. It must construct a Simulation, call build!, and then return the Simulation instance. It must throw an exception if the build fails.

    function build_simulation(
+    output_dir::AbstractString,
+    simulation_name::AbstractString,
+    partitions::SimulationPartitions,
+    index::Union{Nothing, Integer}=nothing,
+)

    Here is example code to construct the Simulation with these parameters:

        sim = Simulation(
+        name=simulation_name,
+        steps=partitions.num_steps,
+        models=models,
+        sequence=sequence,
+        simulation_folder=output_dir,
+    )
+    status = build!(sim; partitions=partitions, index=index, serialize=isnothing(index))
+    if status != PSI.BuildStatus.BUILT
+        error("Failed to build simulation: status=$status")
+    end
    • Implement an execute function that matches the signature below. It must throw an exception if the execute fails.
    function execute_simulation(sim, args...; kwargs...)
+    status = execute!(sim)
+    if status != PSI.RunStatus.SUCCESSFUL
+        error("Simulation failed to execute: status=$status")
+    end
+end
    • Make the script runnable as a CLI command by including the following code at the bottom of the

    file.

    function main()
+    process_simulation_partition_cli_args(build_simulation, execute_simulation, ARGS...)
+end
+
+if abspath(PROGRAM_FILE) == @__FILE__
+    main()
+end

    Execution

    1. Create a Jade configuration that defines the partitioned simulation jobs. Load your Julia environment.

      This example splits a year-long simulation into weekly partitions for a total of 53 individual jobs.

    julia> include("configure_parallel_simulation.jl")
+julia> num_steps = 365
+julia> period = 7
+julia> num_overlap_steps = 1
+julia> configure_parallel_simulation(
+    "my_simulation.jl",  # this is your build/execute script
+    num_steps,
+    period,
+    num_overlap_steps=1,
+    project_path=".",  # This optionally specifies the Julia project environment to load.
+)
+Created Jade configuration in config.json. Run 'jade submit-jobs [options] config.json' to execute them.

    Exit Julia.

    1. View the configuration for accuracy.
    $ jade config show config.json
    1. Start an interactive session on a debug node. Do not submit the jobs on a login node! The submission step will run a full build of the simulation and that may consume too many CPU and memory resources for the login node.
    $ salloc -t 01:00:00 -N1 --account=<your-account> --partition=debug

    1. Follow the instructions at https://nrel.github.io/jade/tutorial.html to submit the jobs. The example below will configure Jade to run each partition on its own compute node. Depending on the compute and memory constraints of your simulation, you may be able to pack more jobs on each node.

      Adjust the walltime as necessary.

    $ jade config hpc -c hpc_config.toml -t slurm  --walltime=04:00:00 -a <your-account>
+$ jade submit-jobs config.json --per-node-batch-size=1 -o output

    If you are unsure about how much memory and CPU resources your simulation consumes, add these options:

    $ jade submit-jobs config.json --per-node-batch-size=1 -o output --resource-monitor-type periodic --resource-monitor-interval 3

    Jade will create HTML plots of the resource utilization in output/stats. You may be able to customize --per-node-batch-size and --num-processes to finish the simulations more quickly.

    1. Jade will run a final command to join the simulation partitions into one unified file. You can load the results as you normally would.
    julia> results = SimulationResults("<output-dir>/job-outputs/<simulation-name>")

    Note the log files and results for each partition are located in <output-dir>/job-outputs/<simulation-name>/simulation_partitions

    diff --git a/v0.24.1/modeler_guide/problem_templates/index.html b/v0.24.1/modeler_guide/problem_templates/index.html new file mode 100644 index 0000000000..a46a0d72c7 --- /dev/null +++ b/v0.24.1/modeler_guide/problem_templates/index.html @@ -0,0 +1,254 @@ + +Operations ProblemTemplates · PowerSimulations.jl
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    Operations ProblemTemplates

    Templates are used to specify the modeling properties of the devices and network that are going to he used to specify a problem. A ProblemTemplate is just a collection of DeviceModels that allows the user to specify the formulations of each set of devices (by device type) independently so that the modeler can adjust the level of detail according to the question of interest and the available data. For more information about valid DeviceModels and their mathematical representations, check out the Formulation Library.

    Building a ProblemTemplate

    You can build a ProblemTemplate by adding a NetworkModel, DeviceModels, and ServiceModels.

    template = ProblemTemplate()
+set_network_model!(template, NetworkModel(CopperPlatePowerModel))
+set_device_model!(template, PowerLoad, StaticPowerLoad)
+set_device_model!(template, ThermalStandard, ThermalBasicUnitCommitment)
+set_service_model!(template, VariableReserve{ReserveUp}, RangeReserve)

    Default Templates

    PowerSimulations.jl provides default templates for common operation problems. You can retrieve a default template and modify it according to your requirements. Currently supported default templates are:

    PowerSimulations.template_economic_dispatch — Function
    template_economic_dispatch(; kwargs...) -> ProblemTemplate
+
    template_economic_dispatch(; kwargs...)

    Creates a ProblemTemplate with default DeviceModels for an Economic Dispatch problem.

    Example

    template = templateeconomicdispatch()

    
+# Accepted Key Words
+- `network::Type{<:PM.AbstractPowerModel}` : override default network model settings
+- `devices::Vector{DeviceModel}` : override default `DeviceModel` settings
+- `services::Vector{ServiceModel}` : override default `ServiceModel` settings
    source
    template_economic_dispatch()
    + + + + + + + + + + + + + + + + + + + +
    Network Model
    Network ModelCopperPlatePowerModel
    Slacksfalse
    PTDFfalse
    DualsNone
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Device Models
    Device TypeFormulationSlacks
    ThermalStandardThermalBasicDispatchfalse
    PowerLoadStaticPowerLoadfalse
    InterruptiblePowerLoadPowerLoadInterruptionfalse
    RenewableFixFixedOutputfalse
    RenewableDispatchRenewableFullDispatchfalse
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Branch Models
    Branch TypeFormulationSlacks
    LineStaticBranchfalse
    TapTransformerStaticBranchfalse
    Transformer2WStaticBranchfalse
    TwoTerminalHVDCLineHVDCTwoTerminalDispatchfalse
    + + + + + + + + + + + + + + + + + + + + + + + + + +
    Service Models
    Service TypeFormulationSlacksAggregated Model
    VariableReserve{ReserveUp}RangeReservefalsetrue
    VariableReserve{ReserveDown}RangeReservefalsetrue
    +
    PowerSimulations.template_unit_commitment — Function
    template_unit_commitment(; kwargs...) -> ProblemTemplate
+
    template_unit_commitment(; kwargs...)

    Creates a ProblemTemplate with default DeviceModels for a Unit Commitment problem.

    Example

    template = templateunitcommitment()

    
+# Accepted Key Words
+- `network::Type{<:PM.AbstractPowerModel}` : override default network model settings
+- `devices::Vector{DeviceModel}` : override default `DeviceModel` settings
+- `services::Vector{ServiceModel}` : override default `ServiceModel` settings
    source
    template_unit_commitment()
    + + + + + + + + + + + + + + + + + + + +
    Network Model
    Network ModelCopperPlatePowerModel
    Slacksfalse
    PTDFfalse
    DualsNone
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Device Models
    Device TypeFormulationSlacks
    ThermalStandardThermalBasicUnitCommitmentfalse
    PowerLoadStaticPowerLoadfalse
    InterruptiblePowerLoadPowerLoadInterruptionfalse
    RenewableFixFixedOutputfalse
    RenewableDispatchRenewableFullDispatchfalse
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Branch Models
    Branch TypeFormulationSlacks
    LineStaticBranchfalse
    TapTransformerStaticBranchfalse
    Transformer2WStaticBranchfalse
    TwoTerminalHVDCLineHVDCTwoTerminalDispatchfalse
    + + + + + + + + + + + + + + + + + + + + + + + + + +
    Service Models
    Service TypeFormulationSlacksAggregated Model
    VariableReserve{ReserveUp}RangeReservefalsetrue
    VariableReserve{ReserveDown}RangeReservefalsetrue
    +
    PowerSimulations.template_agc_reserve_deployment — Function
    template_agc_reserve_deployment(; kwargs...)
+
    template_agc_reserve_deployment(; kwargs...)

    Creates a ProblemTemplate with default DeviceModels for an AGC Reserve Deployment Problem. This model doesn't support customization

    Example

    template = agcreservedeployment()

    source
    using PowerSimulations #hide
+template_agc_reserve_deployment()
    diff --git a/v0.24.1/modeler_guide/psi_structure/index.html b/v0.24.1/modeler_guide/psi_structure/index.html new file mode 100644 index 0000000000..416edc5aa6 --- /dev/null +++ b/v0.24.1/modeler_guide/psi_structure/index.html @@ -0,0 +1,2 @@ + +PowerSimulations.jl Modeling Structure · PowerSimulations.jl
    Edit on GitHub

    PowerSimulations.jl Modeling Structure

    PowerSimulations enables the simulation of a sequence of power systems optimization problems and provides user control over each aspect of the simulation configuration. Specifically:

    What is the difference between a Model and a Problem?

    A "Problem" is an abstract mathematical description of how to represent power system behavior, whereas a "Model" is a concrete representation of a "Problem" applied to a dataset. I.e. once a Problem is populated with data describing all the loads, generators, lines, etc., it becomes a Model.

    diff --git a/v0.24.1/modeler_guide/running_a_simulation/index.html b/v0.24.1/modeler_guide/running_a_simulation/index.html new file mode 100644 index 0000000000..64494e08af --- /dev/null +++ b/v0.24.1/modeler_guide/running_a_simulation/index.html @@ -0,0 +1,2 @@ + +Simulation · PowerSimulations.jl
    Edit on GitHub

    Simulation

    Always try to solve the operations problem first before putting together the simulation

    It is not uncommon that when trying to solve a complex simulation the resulting models are infeasible. This situation can be the result of many factors like the input data, the incorrect specification of the initial conditions for models with time dependencies or a poorly specified model. Therefore, it's highly recommended to run and analyze an Operations Problems that reflect the problems that will be included in a simulation prior to executing a simulation.

    Check out the Operations Problem Tutorial

    Feedforward

    TODO

    Sequencing

    In a typical simulation pipeline, we want to connect daily (24-hours) day-ahead unit commitment problems, with multiple economic dispatch problems. Usually, our day-ahead unit commitment problem will have an hourly (1-hour) resolution, while the economic dispatch will have a 5-minute resolution.

    Depending on your problem, it is common to use a 2-day look-ahead for unit commitment problems, so in this case, the Day-Ahead problem will have: resolution = Hour(1) with interval = Hour(24) and horizon = 48. In the case of the economic dispatch problem, it is common to use a look-ahead of two hours. Thus, the Real-Time problem will have: resolution = Minute(5), with interval = Minute(5) (we only store the first operating point) and horizon = 24 (24 time steps of 5 minutes are 120 minutes, that is 2 hours).

    diff --git a/v0.24.1/modeler_guide/simulation_recorder/index.html b/v0.24.1/modeler_guide/simulation_recorder/index.html new file mode 100644 index 0000000000..9fc8ad4544 --- /dev/null +++ b/v0.24.1/modeler_guide/simulation_recorder/index.html @@ -0,0 +1,43 @@ + +Simulation Recorder · PowerSimulations.jl
    Edit on GitHub

    Simulation Recorder

    PowerSimulations.jl provides the ability to record structured data as events during a simulation. These events can be post-processed to help debug problems.

    By default only SimulationStepEvent and ProblemExecutionEvent are recorded. Here is an example.

    Suppose a simulation is run in the directory ./output.

    Assume that setup commands have been run:

    using PowerSimulations
+const PSI = PowerSimulations

    Note that for all functions below you can optionally specify a function to filter events. The function must accept the event type and return true or false.

    Show all events of type PSI.SimulationStepEvent

    julia> show_simulation_events(PSI.SimulationStepEvent, "./output/aggregation/1")
+┌─────────────────────┬─────────────────────┬──────┬────────┐
+│                name │     simulation_time │ step │ status │
+├─────────────────────┼─────────────────────┼──────┼────────┤
+│ SimulationStepEvent │ 2024-01-01T00:00:00 │    1 │  start │
+│ SimulationStepEvent │ 2024-01-01T23:00:00 │    1 │   done │
+│ SimulationStepEvent │ 2024-01-01T23:00:00 │    2 │  start │
+│ SimulationStepEvent │ 2024-01-02T23:00:00 │    2 │   done │
+└─────────────────────┴─────────────────────┴──────┴────────┘

    Show events of type PSI.ProblemExecutionEvent for a specific step and stage.

    show_simulation_events(
+    PSI.ProblemExecutionEvent,
+    "./output/aggregation/1",
+    x -> x.step == 1 && x.stage == 2 && x.status == "start"
+)
+┌──────────────────────┬─────────────────────┬──────┬───────┬────────┐
+│                 name │     simulation_time │ step │ stage │ status │
+├──────────────────────┼─────────────────────┼──────┼───────┼────────┤
+│ ProblemExecutionEvent │ 2024-01-01T00:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T00:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T01:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T02:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T03:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T04:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T05:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T06:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T07:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T08:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T09:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T10:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T11:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T12:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T13:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T14:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T15:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T16:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T17:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T18:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T19:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T20:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T21:00:00 │    1 │     2 │  start │
+│ ProblemExecutionEvent │ 2024-01-01T22:00:00 │    1 │     2 │  start │
+└──────────────────────┴─────────────────────┴──────┴───────┴────────┘
    diff --git a/v0.24.1/modeler_guide/tips_and_tricks/index.html b/v0.24.1/modeler_guide/tips_and_tricks/index.html new file mode 100644 index 0000000000..d4cd160829 --- /dev/null +++ b/v0.24.1/modeler_guide/tips_and_tricks/index.html @@ -0,0 +1,2 @@ + +Tips and tricks · PowerSimulations.jl diff --git a/v0.24.1/quick_start_guide/index.html b/v0.24.1/quick_start_guide/index.html new file mode 100644 index 0000000000..2ded833b70 --- /dev/null +++ b/v0.24.1/quick_start_guide/index.html @@ -0,0 +1,2 @@ + +Quick Start Guide · PowerSimulations.jl
    Edit on GitHub

    Quick Start Guide

    Tip

    If you need to develop a dataset for a simulation check the PowerSystems.jl Tutorials on how to parse data and attach time series

    • Tutorial: If you are eager to run your first simulation visit the Solve a Day Ahead Market Scheduling Problem using PowerSimulations.jl tutorial
    diff --git a/v0.24.1/search/index.html b/v0.24.1/search/index.html new file mode 100644 index 0000000000..dc62250b88 --- /dev/null +++ b/v0.24.1/search/index.html @@ -0,0 +1,2 @@ + +Search · PowerSimulations.jl diff --git a/v0.24.1/search_index.js b/v0.24.1/search_index.js new file mode 100644 index 0000000000..a647e5f5c6 --- /dev/null +++ b/v0.24.1/search_index.js @@ -0,0 +1,3 @@ +var documenterSearchIndex = {"docs": +[{"location":"code_base_developer_guide/extending_powersimulations/#Extending-Source-Code-Functionalities","page":"Extending Source Code Functionalities","title":"Extending Source Code Functionalities","text":"","category":"section"},{"location":"code_base_developer_guide/extending_powersimulations/#Enable-other-recorder-events","page":"Extending Source Code Functionalities","title":"Enable other recorder events","text":"","category":"section"},{"location":"code_base_developer_guide/extending_powersimulations/","page":"Extending Source Code Functionalities","title":"Extending Source Code Functionalities","text":"Other types of recorder events can be enabled with a possible performance impact. To do this pass in the specific recorder names to be enabled when you call build.","category":"page"},{"location":"code_base_developer_guide/extending_powersimulations/","page":"Extending Source Code Functionalities","title":"Extending Source Code Functionalities","text":"sim = Simulation(...)\nrecorders = [:execution]\nbuild!(sim; recorders = recorders)\nexecute!(sim)","category":"page"},{"location":"code_base_developer_guide/extending_powersimulations/","page":"Extending Source Code Functionalities","title":"Extending Source Code Functionalities","text":"Now we can examine InitialConditionUpdateEvents for specific steps and stages.","category":"page"},{"location":"code_base_developer_guide/extending_powersimulations/","page":"Extending Source Code Functionalities","title":"Extending Source Code Functionalities","text":"show_simulation_events(\n PSI.InitialConditionUpdateEvent,\n \"./output/aggregation/1\",\n x -> x.initial_condition_type == \"DeviceStatus\";\n step = 2,\n stage = 1\n)\n┌─────────────────────────────┬─────────────────────┬────────────────────────┬─────────────────┬─────────────┬─────┬──────────────┐\n│ name │ simulation_time │ initial_condition_type │ device_type │ device_name │ val │ stage_number │\n├─────────────────────────────┼─────────────────────┼────────────────────────┼─────────────────┼─────────────┼─────┼──────────────┤\n│ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │ DeviceStatus │ ThermalStandard │ Solitude │ 0.0 │ 1 │\n│ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │ DeviceStatus │ ThermalStandard │ Park City │ 1.0 │ 1 │\n│ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │ DeviceStatus │ ThermalStandard │ Alta │ 1.0 │ 1 │\n│ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │ DeviceStatus │ ThermalStandard │ Brighton │ 1.0 │ 1 │\n│ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │ DeviceStatus │ ThermalStandard │ Sundance │ 0.0 │ 1 │\n└─────────────────────────────┴─────────────────────┴────────────────────────┴─────────────────┴─────────────┴─────┴──────────────┘","category":"page"},{"location":"code_base_developer_guide/extending_powersimulations/#Show-the-wall-time-with-your-events","page":"Extending Source Code Functionalities","title":"Show the wall time with your events","text":"","category":"section"},{"location":"code_base_developer_guide/extending_powersimulations/","page":"Extending Source Code Functionalities","title":"Extending Source Code Functionalities","text":"Sometimes you might want to see how the events line up with the wall time.","category":"page"},{"location":"code_base_developer_guide/extending_powersimulations/","page":"Extending Source Code Functionalities","title":"Extending Source Code Functionalities","text":"show_simulation_events(\n PSI.InitialConditionUpdateEvent,\n \"./output/aggregation/1\",\n x -> x.initial_condition_type == \"DeviceStatus\";\n step = 2,\n stage = 1,\n wall_time = true\n)\n┌─────────────────────────┬─────────────────────────────┬─────────────────────┬────────────────────────┬─────────────────┬─────────────┬─────┬──────────────┐\n│ timestamp │ name │ simulation_time │ initial_condition_type │ device_type │ device_name │ val │ stage_number │\n├─────────────────────────┼─────────────────────────────┼─────────────────────┼────────────────────────┼─────────────────┼─────────────┼─────┼──────────────┤\n│ 2020-04-07T15:08:32.711 │ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │ DeviceStatus │ ThermalStandard │ Solitude │ 0.0 │ 1 │\n│ 2020-04-07T15:08:32.711 │ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │ DeviceStatus │ ThermalStandard │ Park City │ 1.0 │ 1 │\n│ 2020-04-07T15:08:32.711 │ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │ DeviceStatus │ ThermalStandard │ Alta │ 1.0 │ 1 │\n│ 2020-04-07T15:08:32.711 │ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │ DeviceStatus │ ThermalStandard │ Brighton │ 1.0 │ 1 │\n│ 2020-04-07T15:08:32.711 │ InitialConditionUpdateEvent │ 2024-01-02T00:00:00 │ DeviceStatus │ ThermalStandard │ Sundance │ 0.0 │ 1 │\n└─────────────────────────┴─────────────────────────────┴─────────────────────┴────────────────────────┴─────────────────┴─────────────┴─────┴──────────────┘","category":"page"},{"location":"modeler_guide/simulation_recorder/#Simulation-Recorder","page":"Simulation Recorder","title":"Simulation Recorder","text":"","category":"section"},{"location":"modeler_guide/simulation_recorder/","page":"Simulation Recorder","title":"Simulation Recorder","text":"PowerSimulations.jl provides the ability to record structured data as events during a simulation. These events can be post-processed to help debug problems.","category":"page"},{"location":"modeler_guide/simulation_recorder/","page":"Simulation Recorder","title":"Simulation Recorder","text":"By default only SimulationStepEvent and ProblemExecutionEvent are recorded. Here is an example.","category":"page"},{"location":"modeler_guide/simulation_recorder/","page":"Simulation Recorder","title":"Simulation Recorder","text":"Suppose a simulation is run in the directory ./output.","category":"page"},{"location":"modeler_guide/simulation_recorder/","page":"Simulation Recorder","title":"Simulation Recorder","text":"Assume that setup commands have been run:","category":"page"},{"location":"modeler_guide/simulation_recorder/","page":"Simulation Recorder","title":"Simulation Recorder","text":"using PowerSimulations\nconst PSI = PowerSimulations","category":"page"},{"location":"modeler_guide/simulation_recorder/","page":"Simulation Recorder","title":"Simulation Recorder","text":"Note that for all functions below you can optionally specify a function to filter events. The function must accept the event type and return true or false.","category":"page"},{"location":"modeler_guide/simulation_recorder/#Show-all-events-of-type-PSI.SimulationStepEvent","page":"Simulation Recorder","title":"Show all events of type PSI.SimulationStepEvent","text":"","category":"section"},{"location":"modeler_guide/simulation_recorder/","page":"Simulation Recorder","title":"Simulation Recorder","text":"julia> show_simulation_events(PSI.SimulationStepEvent, \"./output/aggregation/1\")\n┌─────────────────────┬─────────────────────┬──────┬────────┐\n│ name │ simulation_time │ step │ status │\n├─────────────────────┼─────────────────────┼──────┼────────┤\n│ SimulationStepEvent │ 2024-01-01T00:00:00 │ 1 │ start │\n│ SimulationStepEvent │ 2024-01-01T23:00:00 │ 1 │ done │\n│ SimulationStepEvent │ 2024-01-01T23:00:00 │ 2 │ start │\n│ SimulationStepEvent │ 2024-01-02T23:00:00 │ 2 │ done │\n└─────────────────────┴─────────────────────┴──────┴────────┘","category":"page"},{"location":"modeler_guide/simulation_recorder/#Show-events-of-type-PSI.ProblemExecutionEvent-for-a-specific-step-and-stage.","page":"Simulation Recorder","title":"Show events of type PSI.ProblemExecutionEvent for a specific step and stage.","text":"","category":"section"},{"location":"modeler_guide/simulation_recorder/","page":"Simulation Recorder","title":"Simulation Recorder","text":"show_simulation_events(\n PSI.ProblemExecutionEvent,\n \"./output/aggregation/1\",\n x -> x.step == 1 && x.stage == 2 && x.status == \"start\"\n)\n┌──────────────────────┬─────────────────────┬──────┬───────┬────────┐\n│ name │ simulation_time │ step │ stage │ status │\n├──────────────────────┼─────────────────────┼──────┼───────┼────────┤\n│ ProblemExecutionEvent │ 2024-01-01T00:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T00:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T01:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T02:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T03:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T04:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T05:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T06:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T07:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T08:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T09:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T10:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T11:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T12:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T13:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T14:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T15:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T16:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T17:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T18:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T19:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T20:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T21:00:00 │ 1 │ 2 │ start │\n│ ProblemExecutionEvent │ 2024-01-01T22:00:00 │ 1 │ 2 │ start │\n└──────────────────────┴─────────────────────┴──────┴───────┴────────┘","category":"page"},{"location":"modeler_guide/parallel_simulations/#Parallel-Simulations","page":"Parallel Simulations","title":"Parallel Simulations","text":"","category":"section"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"This section contains instructions to:","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Run a Simulation in Parallel on a local computer\nRun a Simulation in Parallel on an HPC","category":"page"},{"location":"modeler_guide/parallel_simulations/#Run-a-Simulation-in-Parallel-on-a-local-computer","page":"Parallel Simulations","title":"Run a Simulation in Parallel on a local computer","text":"","category":"section"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"This page describes how to split a simulation into partitions, run each partition in parallel, and then join the results.","category":"page"},{"location":"modeler_guide/parallel_simulations/#Setup","page":"Parallel Simulations","title":"Setup","text":"","category":"section"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Create a Julia script to build and run simulations. It must meet the requirements below. A full example is in the PowerSimulations repository in test/run_partitioned_simulation.jl.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Call using PowerSimulations.\nImplement a build function that matches the signature below. It must construct a Simulation, call build!, and then return the Simulation instance. It must throw an exception if the build fails.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"function build_simulation(\n output_dir::AbstractString,\n simulation_name::AbstractString,\n partitions::SimulationPartitions,\n index::Union{Nothing, Integer}=nothing,\n)","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Here is example code to construct the Simulation with these parameters:","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":" sim = Simulation(\n name=simulation_name,\n steps=partitions.num_steps,\n models=models,\n sequence=sequence,\n simulation_folder=output_dir,\n )\n status = build!(sim; partitions=partitions, index=index, serialize=isnothing(index))\n if status != PSI.BuildStatus.BUILT\n error(\"Failed to build simulation: status=$status\")\n end","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Implement an execute function that matches the signature below. It must throw an exception if the execute fails.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"function execute_simulation(sim, args...; kwargs...)\n status = execute!(sim)\n if status != PSI.RunStatus.SUCCESSFUL\n error(\"Simulation failed to execute: status=$status\")\n end\nend","category":"page"},{"location":"modeler_guide/parallel_simulations/#Execution","page":"Parallel Simulations","title":"Execution","text":"","category":"section"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"After loading your script, call the function run_parallel_simulation as shown below.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"This example splits a year-long simulation into weekly partitions for a total of 53 individual jobs and then runs them four at a time.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"julia> include(\"my_simulation.jl\")\njulia> run_parallel_simulation(\n build_simulation,\n execute_simulation,\n script=\"my_simulation.jl\",\n output_dir=\"my_simulation_output\",\n name=\"my_simulation\",\n num_steps=365,\n period=7,\n num_overlap_steps=1,\n num_parallel_processes=4,\n exeflags=\"--project=\",\n )","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"The final results will be in ./my_simulation_otuput/my_simulation","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Note the log files and results for each partition are located in ./my_simulation_otuput/my_simulation/simulation_partitions","category":"page"},{"location":"modeler_guide/parallel_simulations/#Run-a-Simulation-in-Parallel-on-an-HPC","page":"Parallel Simulations","title":"Run a Simulation in Parallel on an HPC","text":"","category":"section"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"This page describes how to split a simulation into partitions, run each partition in parallel on HPC compute nodes, and then join the results.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"These steps can be used on a local computer or any HPC supported by the submission software. Some steps may be specific to NREL's HPC Eagle cluster.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Note: Some instructions are preliminary and will change if functionality is moved to a new Julia package.","category":"page"},{"location":"modeler_guide/parallel_simulations/#Setup-2","page":"Parallel Simulations","title":"Setup","text":"","category":"section"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Create a conda environment and install the Python package NREL-jade: https://nrel.github.io/jade/installation.html. The rest of this page assumes that the environment is called jade.\nActivate the environment with conda activate jade.\nLocate the path to that conda environment. It will likely be ~/.conda-envs/jade or ~/.conda/envs/jade.\nLoad the Julia environment that you use to run simulations. Add the packages Conda and PyCall.\nSetup Conda to use the existing jade environment by running these commands:","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"julia> run(`conda create -n conda_jl python conda`)\njulia> ENV[\"CONDA_JL_HOME\"] = joinpath(ENV[\"HOME\"], \".conda-envs\", \"jade\") # change this to your path\npkg> build Conda","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Copy the code below into a Julia file called configure_parallel_simulation.jl. This is an interface to Jade through PyCall. It will be used to create a Jade configuration. (It may eventually be moved to a separate package.)","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"function configure_parallel_simulation(\n script::AbstractString,\n num_steps::Integer,\n num_period_steps::Integer;\n num_overlap_steps::Integer=0,\n project_path=nothing,\n simulation_name=\"simulation\",\n config_file=\"config.json\",\n force=false,\n)\n partitions = SimulationPartitions(num_steps, num_period_steps, num_overlap_steps)\n jgc = pyimport(\"jade.extensions.generic_command\")\n julia_cmd = isnothing(project_path) ? \"julia\" : \"julia --project=$project_path\"\n setup_command = \"$julia_cmd $script setup --simulation-name=$simulation_name \" *\n \"--num-steps=$num_steps --num-period-steps=$num_period_steps \" *\n \"--num-overlap-steps=$num_overlap_steps\"\n teardown_command = \"$julia_cmd $script join --simulation-name=$simulation_name\"\n config = jgc.GenericCommandConfiguration(\n setup_command=setup_command,\n teardown_command=teardown_command,\n )\n\n for i in 1:get_num_partitions(partitions)\n cmd = \"$julia_cmd $script execute --simulation-name=$simulation_name --index=$i\"\n job = jgc.GenericCommandParameters(command=cmd, name=\"execute-$i\")\n config.add_job(job)\n end\n\n config.dump(config_file, indent=2)\n println(\"Created Jade configuration in $config_file. \" *\n \"Run 'jade submit-jobs [options] $config_file' to execute them.\")\nend","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Create a Julia script to build and run simulations. It must meet the requirements below. A full example is in the PowerSimulations repository in test/run_partitioned_simulation.jl.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Call using PowerSimulations.\nImplement a build function that matches the signature below. It must construct a Simulation, call build!, and then return the Simulation instance. It must throw an exception if the build fails.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"function build_simulation(\n output_dir::AbstractString,\n simulation_name::AbstractString,\n partitions::SimulationPartitions,\n index::Union{Nothing, Integer}=nothing,\n)","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Here is example code to construct the Simulation with these parameters:","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":" sim = Simulation(\n name=simulation_name,\n steps=partitions.num_steps,\n models=models,\n sequence=sequence,\n simulation_folder=output_dir,\n )\n status = build!(sim; partitions=partitions, index=index, serialize=isnothing(index))\n if status != PSI.BuildStatus.BUILT\n error(\"Failed to build simulation: status=$status\")\n end","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Implement an execute function that matches the signature below. It must throw an exception if the execute fails.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"function execute_simulation(sim, args...; kwargs...)\n status = execute!(sim)\n if status != PSI.RunStatus.SUCCESSFUL\n error(\"Simulation failed to execute: status=$status\")\n end\nend","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Make the script runnable as a CLI command by including the following code at the bottom of the","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"file.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"function main()\n process_simulation_partition_cli_args(build_simulation, execute_simulation, ARGS...)\nend\n\nif abspath(PROGRAM_FILE) == @__FILE__\n main()\nend","category":"page"},{"location":"modeler_guide/parallel_simulations/#Execution-2","page":"Parallel Simulations","title":"Execution","text":"","category":"section"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Create a Jade configuration that defines the partitioned simulation jobs. Load your Julia environment.\nThis example splits a year-long simulation into weekly partitions for a total of 53 individual jobs.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"julia> include(\"configure_parallel_simulation.jl\")\njulia> num_steps = 365\njulia> period = 7\njulia> num_overlap_steps = 1\njulia> configure_parallel_simulation(\n \"my_simulation.jl\", # this is your build/execute script\n num_steps,\n period,\n num_overlap_steps=1,\n project_path=\".\", # This optionally specifies the Julia project environment to load.\n)\nCreated Jade configuration in config.json. Run 'jade submit-jobs [options] config.json' to execute them.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Exit Julia.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"View the configuration for accuracy.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"$ jade config show config.json","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Start an interactive session on a debug node. Do not submit the jobs on a login node! The submission step will run a full build of the simulation and that may consume too many CPU and memory resources for the login node.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"$ salloc -t 01:00:00 -N1 --account= --partition=debug","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Follow the instructions at https://nrel.github.io/jade/tutorial.html to submit the jobs. The example below will configure Jade to run each partition on its own compute node. Depending on the compute and memory constraints of your simulation, you may be able to pack more jobs on each node.\nAdjust the walltime as necessary.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"$ jade config hpc -c hpc_config.toml -t slurm --walltime=04:00:00 -a \n$ jade submit-jobs config.json --per-node-batch-size=1 -o output","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"If you are unsure about how much memory and CPU resources your simulation consumes, add these options:","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"$ jade submit-jobs config.json --per-node-batch-size=1 -o output --resource-monitor-type periodic --resource-monitor-interval 3","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Jade will create HTML plots of the resource utilization in output/stats. You may be able to customize --per-node-batch-size and --num-processes to finish the simulations more quickly.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Jade will run a final command to join the simulation partitions into one unified file. You can load the results as you normally would.","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"julia> results = SimulationResults(\"/job-outputs/\")","category":"page"},{"location":"modeler_guide/parallel_simulations/","page":"Parallel Simulations","title":"Parallel Simulations","text":"Note the log files and results for each partition are located in /job-outputs//simulation_partitions","category":"page"},{"location":"quick_start_guide/#Quick-Start-Guide","page":"Quick Start Guide","title":"Quick Start Guide","text":"","category":"section"},{"location":"quick_start_guide/","page":"Quick Start Guide","title":"Quick Start Guide","text":"Julia: If this is your first time using Julia visit our Introduction to Julia and the official Getting started with Julia.\nPackage Installation: If you want to install packages check the Package Manager instructions, or you can refer to the PowerSimulations installation instructions.\nPowerSystems: PowerSystems.jl manages the data and is a fundamental dependency of PowerSimulations.jl. Check the PowerSystems.jl Basics Tutorial and PowerSystems.jl documentation to understand how the inputs to the models are organized.\nDataset Library: If you don't have a data set to start using PowerSimulations.jl check the test systems provided in PowerSystemCaseBuilder.jl","category":"page"},{"location":"quick_start_guide/","page":"Quick Start Guide","title":"Quick Start Guide","text":"tip: Tip\nIf you need to develop a dataset for a simulation check the PowerSystems.jl Tutorials on how to parse data and attach time series","category":"page"},{"location":"quick_start_guide/","page":"Quick Start Guide","title":"Quick Start Guide","text":"Tutorial: If you are eager to run your first simulation visit the Solve a Day Ahead Market Scheduling Problem using PowerSimulations.jl tutorial","category":"page"},{"location":"code_base_developer_guide/troubleshooting/#Troubleshooting-code-development","page":"Troubleshooting","title":"Troubleshooting code development","text":"","category":"section"},{"location":"tutorials/decision_problem/#op_problem_tutorial","page":"Single-step Problem","title":"Operations problems with PowerSimulations.jl","text":"","category":"section"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"Originally Contributed by: Clayton Barrows","category":"page"},{"location":"tutorials/decision_problem/#Introduction","page":"Single-step Problem","title":"Introduction","text":"","category":"section"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"PowerSimulations.jl supports the construction and solution of optimal power system scheduling problems (Operations Problems). Operations problems form the fundamental building blocks for sequential simulations. This example shows how to specify and customize a the mathematics that will be applied to the data with an ProblemTemplate, build and execute an DecisionModel, and access the results.","category":"page"},{"location":"tutorials/decision_problem/#Load-Packages","page":"Single-step Problem","title":"Load Packages","text":"","category":"section"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"using PowerSystems\nusing PowerSimulations\nusing PowerSystemCaseBuilder\nusing HiGHS # solver","category":"page"},{"location":"tutorials/decision_problem/#Data","page":"Single-step Problem","title":"Data","text":"","category":"section"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"note: Note\nPowerSystemCaseBuilder.jl is a helper library that makes it easier to reproduce examples in the documentation and tutorials. Normally you would pass your local files to create the system data instead of calling the function build_system. For more details visit PowerSystemCaseBuilder Documentation","category":"page"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"sys = build_system(PSISystems, \"modified_RTS_GMLC_DA_sys\")","category":"page"},{"location":"tutorials/decision_problem/#Define-a-problem-specification-with-an-ProblemTemplate","page":"Single-step Problem","title":"Define a problem specification with an ProblemTemplate","text":"","category":"section"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"You can create an empty template with:","category":"page"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"template_uc = ProblemTemplate()","category":"page"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"Now, you can add a DeviceModel for each device type to create an assignment between PowerSystems device types and the subtypes of AbstractDeviceFormulation. PowerSimulations has a variety of different AbstractDeviceFormulation subtypes that can be applied to different PowerSystems device types, each dispatching to different methods for populating optimization problem objectives, variables, and constraints. Documentation on the formulation options for various devices can be found in the formulation library docs","category":"page"},{"location":"tutorials/decision_problem/#Branch-Formulations","page":"Single-step Problem","title":"Branch Formulations","text":"","category":"section"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"Here is an example of relatively standard branch formulations. Other formulations allow for selective enforcement of transmission limits and greater control on transformer settings.","category":"page"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"set_device_model!(template_uc, Line, StaticBranch)\nset_device_model!(template_uc, Transformer2W, StaticBranch)\nset_device_model!(template_uc, TapTransformer, StaticBranch)","category":"page"},{"location":"tutorials/decision_problem/#Injection-Device-Formulations","page":"Single-step Problem","title":"Injection Device Formulations","text":"","category":"section"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"Here we define template entries for all devices that inject or withdraw power on the network. For each device type, we can define a distinct AbstractDeviceFormulation. In this case, we're defining a basic unit commitment model for thermal generators, curtailable renewable generators, and fixed dispatch (net-load reduction) formulations for HydroDispatch and RenewableFix devices.","category":"page"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"set_device_model!(template_uc, ThermalStandard, ThermalStandardUnitCommitment)\nset_device_model!(template_uc, RenewableDispatch, RenewableFullDispatch)\nset_device_model!(template_uc, PowerLoad, StaticPowerLoad)\nset_device_model!(template_uc, HydroDispatch, FixedOutput)\nset_device_model!(template_uc, HydroDispatchRunOfRiver, HydroDispatchRunOfRiver)\nset_device_model!(template_uc, RenewableFix, FixedOutput)","category":"page"},{"location":"tutorials/decision_problem/#Service-Formulations","page":"Single-step Problem","title":"Service Formulations","text":"","category":"section"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"We have two VariableReserve types, parameterized by their direction. So, similar to creating DeviceModels, we can create ServiceModels. The primary difference being that DeviceModel objects define how constraints get created, while ServiceModel objects define how constraints get modified.","category":"page"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"set_service_model!(template_uc, VariableReserve{ReserveUp}, RangeReserve)\nset_service_model!(template_uc, VariableReserve{ReserveDown}, RangeReserve)","category":"page"},{"location":"tutorials/decision_problem/#Network-Formulations","page":"Single-step Problem","title":"Network Formulations","text":"","category":"section"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"Finally, we can define the transmission network specification that we'd like to model. For simplicity, we'll choose a copper plate formulation. But there are dozens of specifications available through an integration with PowerModels.jl. Note that many formulations will require appropriate data and may be computationally intractable","category":"page"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"set_network_model!(template_uc, NetworkModel(CopperPlatePowerModel))","category":"page"},{"location":"tutorials/decision_problem/#DecisionModel","page":"Single-step Problem","title":"DecisionModel","text":"","category":"section"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"Now that we have a System and an ProblemTemplate, we can put the two together to create an DecisionModel that we solve.","category":"page"},{"location":"tutorials/decision_problem/#Optimizer","page":"Single-step Problem","title":"Optimizer","text":"","category":"section"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"It's most convenient to define an optimizer instance upfront and pass it into the DecisionModel constructor. For this example, we can use the free HiGHS solver with a relatively relaxed MIP gap (ratioGap) setting to improve speed.","category":"page"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"solver = optimizer_with_attributes(HiGHS.Optimizer, \"mip_rel_gap\" => 0.5)","category":"page"},{"location":"tutorials/decision_problem/#Build-an-DecisionModel","page":"Single-step Problem","title":"Build an DecisionModel","text":"","category":"section"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"The construction of an DecisionModel essentially applies an ProblemTemplate to System data to create a JuMP model.","category":"page"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"problem = DecisionModel(template_uc, sys; optimizer = solver, horizon = 24)\nbuild!(problem, output_dir = mktempdir())","category":"page"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"tip: Tip\nThe principal component of the DecisionModel is the JuMP model. But you can serialize to a file using the following command: serialize_optimization_model(problem, save_path)Keep in mind that if the setting \"storevariablenames\" is set to False then the file won't show the model's names.","category":"page"},{"location":"tutorials/decision_problem/#Solve-an-DecisionModel","page":"Single-step Problem","title":"Solve an DecisionModel","text":"","category":"section"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"solve!(problem)","category":"page"},{"location":"tutorials/decision_problem/#Results-Inspection","page":"Single-step Problem","title":"Results Inspection","text":"","category":"section"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"PowerSimulations collects the DecisionModel results into a ProblemResults struct:","category":"page"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"res = ProblemResults(problem)","category":"page"},{"location":"tutorials/decision_problem/#Optimizer-Stats","page":"Single-step Problem","title":"Optimizer Stats","text":"","category":"section"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"The optimizer summary is included","category":"page"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"get_optimizer_stats(res)","category":"page"},{"location":"tutorials/decision_problem/#Objective-Function-Value","page":"Single-step Problem","title":"Objective Function Value","text":"","category":"section"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"get_objective_value(res)","category":"page"},{"location":"tutorials/decision_problem/#Variable,-Parameter,-Auxillary-Variable,-Dual,-and-Expression-Values","page":"Single-step Problem","title":"Variable, Parameter, Auxillary Variable, Dual, and Expression Values","text":"","category":"section"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"The solution value data frames for variables, parameters, auxillary variables, duals and expressions can be accessed using the read_ methods:","category":"page"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"read_variables(res)","category":"page"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"Or, you can read a single parameter values for parameters that exist in the results.","category":"page"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"list_parameter_names(res)\nread_parameter(res, \"ActivePowerTimeSeriesParameter__RenewableDispatch\")","category":"page"},{"location":"tutorials/decision_problem/#Plotting","page":"Single-step Problem","title":"Plotting","text":"","category":"section"},{"location":"tutorials/decision_problem/","page":"Single-step Problem","title":"Single-step Problem","text":"Take a look at the plotting capabilities in PowerGraphics.jl","category":"page"},{"location":"modeler_guide/tips_and_tricks/#Tips-and-tricks","page":"Tips and tricks","title":"Tips and tricks","text":"","category":"section"},{"location":"formulation_library/ThermalGen/#ThermalGen-Formulations","page":"Thermal Generation","title":"ThermalGen Formulations","text":"","category":"section"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"Valid DeviceModels for subtypes of ThermalGen include the following:","category":"page"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"using PowerSimulations\nusing PowerSystems\nusing DataFrames\nusing Latexify\ncombos = PowerSimulations.generate_device_formulation_combinations()\nfilter!(x -> x[\"device_type\"] <: ThermalGen, combos)\ncombo_table = DataFrame(\n \"Valid DeviceModel\" => [\"`DeviceModel($(c[\"device_type\"]), $(c[\"formulation\"]))`\" for c in combos],\n \"Device Type\" => [\"[$(c[\"device_type\"])](https://nrel-Sienna.github.io/PowerSystems.jl/stable/model_library/generated_$(c[\"device_type\"])/)\" for c in combos],\n \"Formulation\" => [\"[$(c[\"formulation\"])](@ref)\" for c in combos],\n )\nmdtable(combo_table, latex = false)","category":"page"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"","category":"page"},{"location":"formulation_library/ThermalGen/#ThermalBasicDispatch","page":"Thermal Generation","title":"ThermalBasicDispatch","text":"","category":"section"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"ThermalBasicDispatch","category":"page"},{"location":"formulation_library/ThermalGen/#PowerSimulations.ThermalBasicDispatch","page":"Thermal Generation","title":"PowerSimulations.ThermalBasicDispatch","text":"Formulation type to enable basic dispatch without any intertemporal (ramp) constraints\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"TODO","category":"page"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"","category":"page"},{"location":"formulation_library/ThermalGen/#ThermalCompactDispatch","page":"Thermal Generation","title":"ThermalCompactDispatch","text":"","category":"section"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"ThermalCompactDispatch","category":"page"},{"location":"formulation_library/ThermalGen/#PowerSimulations.ThermalCompactDispatch","page":"Thermal Generation","title":"PowerSimulations.ThermalCompactDispatch","text":"Formulation type to enable thermal compact dispatch\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"TODO","category":"page"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"","category":"page"},{"location":"formulation_library/ThermalGen/#ThermalDispatchNoMin","page":"Thermal Generation","title":"ThermalDispatchNoMin","text":"","category":"section"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"ThermalDispatchNoMin","category":"page"},{"location":"formulation_library/ThermalGen/#PowerSimulations.ThermalDispatchNoMin","page":"Thermal Generation","title":"PowerSimulations.ThermalDispatchNoMin","text":"Formulation type to enable basic dispatch without any intertemporal constraints and relaxed minimum generation. may not work with PWL cost definitions\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"TODO","category":"page"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"","category":"page"},{"location":"formulation_library/ThermalGen/#ThermalStandardDispatch","page":"Thermal Generation","title":"ThermalStandardDispatch","text":"","category":"section"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"ThermalStandardDispatch","category":"page"},{"location":"formulation_library/ThermalGen/#PowerSimulations.ThermalStandardDispatch","page":"Thermal Generation","title":"PowerSimulations.ThermalStandardDispatch","text":"Formulation type to enable standard dispatch with a range and enforce intertemporal ramp constraints\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"TODO","category":"page"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"","category":"page"},{"location":"formulation_library/ThermalGen/#ThermalBasicCompactUnitCommitment","page":"Thermal Generation","title":"ThermalBasicCompactUnitCommitment","text":"","category":"section"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"ThermalBasicCompactUnitCommitment","category":"page"},{"location":"formulation_library/ThermalGen/#PowerSimulations.ThermalBasicCompactUnitCommitment","page":"Thermal Generation","title":"PowerSimulations.ThermalBasicCompactUnitCommitment","text":"Formulation type to enable thermal compact commitment without intertemporal (ramp, min on/off time) constraints\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"TODO","category":"page"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"","category":"page"},{"location":"formulation_library/ThermalGen/#ThermalCompactUnitCommitment","page":"Thermal Generation","title":"ThermalCompactUnitCommitment","text":"","category":"section"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"ThermalCompactUnitCommitment","category":"page"},{"location":"formulation_library/ThermalGen/#PowerSimulations.ThermalCompactUnitCommitment","page":"Thermal Generation","title":"PowerSimulations.ThermalCompactUnitCommitment","text":"Formulation type to enable thermal compact commitment\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"TODO","category":"page"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"","category":"page"},{"location":"formulation_library/ThermalGen/#ThermalMultiStartUnitCommitment","page":"Thermal Generation","title":"ThermalMultiStartUnitCommitment","text":"","category":"section"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"ThermalMultiStartUnitCommitment","category":"page"},{"location":"formulation_library/ThermalGen/#PowerSimulations.ThermalMultiStartUnitCommitment","page":"Thermal Generation","title":"PowerSimulations.ThermalMultiStartUnitCommitment","text":"Formulation type to enable pg-lib commitment formulation with startup/shutdown profiles\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"TODO","category":"page"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"","category":"page"},{"location":"formulation_library/ThermalGen/#ThermalBasicUnitCommitment","page":"Thermal Generation","title":"ThermalBasicUnitCommitment","text":"","category":"section"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"ThermalBasicUnitCommitment","category":"page"},{"location":"formulation_library/ThermalGen/#PowerSimulations.ThermalBasicUnitCommitment","page":"Thermal Generation","title":"PowerSimulations.ThermalBasicUnitCommitment","text":"Formulation type to enable basic unit commitment representation without any intertemporal (ramp, min on/off time) constraints\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"TODO","category":"page"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"","category":"page"},{"location":"formulation_library/ThermalGen/#ThermalStandardUnitCommitment","page":"Thermal Generation","title":"ThermalStandardUnitCommitment","text":"","category":"section"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"ThermalStandardUnitCommitment","category":"page"},{"location":"formulation_library/ThermalGen/#PowerSimulations.ThermalStandardUnitCommitment","page":"Thermal Generation","title":"PowerSimulations.ThermalStandardUnitCommitment","text":"Formulation type to enable standard unit commitment with intertemporal constraints and simplified startup profiles\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"TODO","category":"page"},{"location":"formulation_library/ThermalGen/","page":"Thermal Generation","title":"Thermal Generation","text":"","category":"page"},{"location":"tutorials/adding_new_problem_model/#Adding-an-Operations-Problem-Model","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"","category":"section"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"This tutorial will show how to create a custom decision problem model. These cases are the ones where the user want to solve a fully specified problem. Some examples of custom decision models include:","category":"page"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"Solving a custom Security Constrained Unit Commitment Problem\nSolving a market agent utility maximization Problem. See examples of this functionality in HybridSystemsSimulations.jl","category":"page"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"The tutorial follows the usual steps for operational model building. First, build the decision model in isolation and second, integrate it into a simulation. In most cases there will be more than one way of achieving the same objective when it comes to implementing the model. This guide shows a general set of steps and requirements but it is by no means an exhaustive and detailed guide on developing custom decision models.","category":"page"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"warning: Warning\nAll the code in this tutorial is considered \"pseudo-code\". Copy-paste will likely not work out of the box. You need to develop the internals of the functions correctly for the examples below to work.","category":"page"},{"location":"tutorials/adding_new_problem_model/#General-Rules","page":"Adding an Operations Problem Model","title":"General Rules","text":"","category":"section"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"As a general rule you need to understand Julia's terminology such as multiple dispatch, parametric structs and method overloading, among others. Developing custom models for an operational simulation is a highly technical task and requires skilled development. This tutorial also requires good understanding of PowerSystems.jl data structures and features which are covered in the tutorials section of PowerSystems.jl documentation.","category":"page"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"Finally, developing a custom model decision model that will employ an optimization model under the hood requires understanding JuMP.jl.","category":"page"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"Need to employ anonymous constraints and variables in JuMP","category":"page"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"and register the constraints, variables and other optimization objects into PowerSimulations.jl's optimization container. Otherwise the features to use your problem in the simulation like the coordination with other problems and post processing won't work. More on this in the section How to develop your build_model! function below.","category":"page"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"Implement the required methods for your custom decision models. In some cases it will be possible to re-use some of the other methods that exist in PowerSimulations to make life easier for variable addition and constraint creation but this is not required.","category":"page"},{"location":"tutorials/adding_new_problem_model/#Decision-Problem","page":"Adding an Operations Problem Model","title":"Decision Problem","text":"","category":"section"},{"location":"tutorials/adding_new_problem_model/#Step-1:-Define-a-Custom-Decision-Problem","page":"Adding an Operations Problem Model","title":"Step 1: Define a Custom Decision Problem","text":"","category":"section"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"Define a decision problem struct as a subtype of PowerSimulations.DecisionProblem. This requirement will enable a lot of the underlying functionality that relies on multiple dispatch. DecisionProblems are used to parameterize the behavior of DecisionModel objects which are just containers for the parameters, references and the optimization problem.","category":"page"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"It is possible to define a Custom Decision Problem that gives the user full control over the build, solve and execution process since it imposes less requirements on the developer. However, with less requirements there are also less checks and validations performed inside of PowerSimulations which might lead to unexpected errors","category":"page"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"struct MyCustomDecisionProblem <: PSI.DecisionProblem end","category":"page"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"Alternatively, it is possible to define a Custom Decision Problem subtyping from DefaultDecisionProblem which imposes more requirements and structure onto the developer but employs more checks and validations in the process. Be aware that this route will decrease the flexibility of what can be done inside the custom model.","category":"page"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"struct MyCustomDecisionProblem <: PSI.DefaultDecisionProblem end","category":"page"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"Once the problem type is defined, initialize the decision model container with your custom decision problem passing the solver and some of the settings you need for the solution of the problem. For custom problems some of the settings need manual implementation by the developer. Settings availability is also dependent on wether you choose to subtype from PSI.DecisionProblem or PSI.DefaultDecisionProblem","category":"page"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"my_model = DecisionModel{MyCustomDecisionProblem}(\n sys;\n name = \"MyModel\",\n optimizer = optimizer_with_attributes(HiGHS.Optimizer),\n optimizer_solve_log_print = true,\n)","category":"page"},{"location":"tutorials/adding_new_problem_model/#Mandatory-Method-Implementations","page":"Adding an Operations Problem Model","title":"Mandatory Method Implementations","text":"","category":"section"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"build_model!: This method build the JuMP optimization model.","category":"page"},{"location":"tutorials/adding_new_problem_model/#Optional-Method-Overloads","page":"Adding an Operations Problem Model","title":"Optional Method Overloads","text":"","category":"section"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"These methods can be defined optionally for your problem. By default for problems subtyped from DecisionProblem these checks are not executed. If the problems are subtyped from DefaultDecisionProblem these checks are always conducted with PowerSimulations defaults and require compliance with those defaults to pass. In any case, these can be overloaded when necessary depending on the problem requirements.","category":"page"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"validate_template\nvalidate_time_series\nreset!\nsolve_impl!","category":"page"},{"location":"tutorials/adding_new_problem_model/#How-to-develop-your-build_model!-function","page":"Adding an Operations Problem Model","title":"How to develop your build_model! function","text":"","category":"section"},{"location":"tutorials/adding_new_problem_model/#Registering-a-variable-in-the-model","page":"Adding an Operations Problem Model","title":"Registering a variable in the model","text":"","category":"section"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"To register a variable in the model, the developer must first allocate the container into the optimization container and then populate it. For example, it require start the build function as follows:","category":"page"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"info: Info\nWe recommend calling import PowerSimulations and defining the constant CONST PSI = PowerSimulations to make it easier to read the code and determine which package is responsible for defining the functions.","category":"page"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":" function PSI.build_model!(model::PSI.DecisionModel{MyCustomDecisionProblem})\n container = PSI.get_optimization_container(model)\n time_steps = 1:24\n PSI.set_time_steps!(container, time_steps)\n system = PSI.get_system(model)\n\n thermal_gens = PSY.get_components(PSY.ThermalStandard, system)\n thermal_gens_names = PSY.get_name.(thermal_gens)\n\n # Create the container for the variable\n variable = PSI.add_variable_container!(\n container,\n PSI.ActivePowerVariable(), # <- This variable is defined in PowerSimulations but the user can define their own\n PSY.ThermalGeneration, # <- Device type for the variable. Can be from PSY or custom defined\n thermal_gens_names, # <- First container dimension\n time_steps, # <- Second container dimension\n )\n\n # Iterate over the devices and time to store the JuMP variables into the container.\n for t in time_steps, d in thermal_gens_names\n name = PSY.get_name(d)\n variable[name, t] = JuMP.@variable(get_jump_model(container))\n # It is possible to use PSY getter functions to retrieve data from the generators\n JuMP.set_upper_bound(variable[name, t], UB_DATA) # <- Optional\n JuMP.set_lower_bound(variable[name, t], LB_DATA) # <- Optional\n end\n\n # Add More Variables.....\n\n return\n end","category":"page"},{"location":"tutorials/adding_new_problem_model/#Registering-a-constraint-in-the-model","page":"Adding an Operations Problem Model","title":"Registering a constraint in the model","text":"","category":"section"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":"A similar pattern is used to add constraints to the model, in this example the field meta is used to avoid creating unnecessary duplicate constraint types. For instance to reflect upperbound and lowerbound or upwards and downwards constraints. Meta can take any string value except for the _ character.","category":"page"},{"location":"tutorials/adding_new_problem_model/","page":"Adding an Operations Problem Model","title":"Adding an Operations Problem Model","text":" function PSI.build_model!(model::PSI.DecisionModel{MyCustomDecisionProblem})\n container = PSI.get_optimization_container(model)\n time_steps = 1:24\n PSI.set_time_steps!(container, time_steps)\n system = PSI.get_system(model)\n\n # VARIABLE ADDITION CODE\n\n # Constraint additions\n con_ub = PSI.add_constraints_container!(\n container,\n PSI.RangeLimitConstraint(), # <- Constraint Type defined by PSI or your own\n PSY.ThermalGeneration, # <- Device type for variable. Can be PSY or custom\n thermal_gens_names, # <- First container dimension\n time_steps; # <- Second container dimension\n meta = \"ub\" # <- meta allows to reuse a constraint definition for similar constraints. It only requires to be a string\n )\n\n con_lb = PSI.add_constraints_container!(\n container,\n PSI.RangeLimitConstraint(),\n PSY.ThermalGeneration,\n thermal_gens_names, # <- First container dimension\n time_steps; # <- Second container dimension\n meta = \"lb\" # <- meta allows to reuse a constraint definition for similar constraints. It only requires to be a string\n )\n\n # Retrieve a relevant variable from the container if not defined in\n variable = PSI.get_variable(container, PSI.ActivePowerVariable(), PSY.ThermalGeneration)\n for device in devices, t in time_steps\n ci_name = PSY.get_name(device)\n limits = get_min_max_limits(device) # depends on constraint type and formulation type\n con_ub[ci_name, t] =\n JuMP.@constraint(get_jump_model(container), variable[ci_name, t] >= limits.min)\n con_lb[ci_name, t] =\n JuMP.@constraint(get_jump_model(container), variable[ci_name, t] >= limits.min)\n end\n\n return\n end","category":"page"},{"location":"formulation_library/Branch/#PowerSystems.Branch-Formulations","page":"Branch","title":"PowerSystems.Branch Formulations","text":"","category":"section"},{"location":"formulation_library/Branch/","page":"Branch","title":"Branch","text":"Valid DeviceModels for subtypes of Branch include the following:","category":"page"},{"location":"formulation_library/Branch/","page":"Branch","title":"Branch","text":"using PowerSimulations\nusing PowerSystems\nusing DataFrames\nusing Latexify\ncombos = PowerSimulations.generate_device_formulation_combinations()\nfilter!(x -> x[\"device_type\"] <: Branch, combos)\ncombo_table = DataFrame(\n \"Valid DeviceModel\" => [\"`DeviceModel($(c[\"device_type\"]), $(c[\"formulation\"]))`\" for c in combos],\n \"Device Type\" => [\"[$(c[\"device_type\"])](https://nrel-Sienna.github.io/PowerSystems.jl/stable/model_library/generated_$(c[\"device_type\"])/)\" for c in combos],\n \"Formulation\" => [\"[$(c[\"formulation\"])](@ref)\" for c in combos],\n )\nmdtable(combo_table, latex = false)","category":"page"},{"location":"formulation_library/Branch/","page":"Branch","title":"Branch","text":"","category":"page"},{"location":"formulation_library/Branch/#StaticBranch","page":"Branch","title":"StaticBranch","text":"","category":"section"},{"location":"formulation_library/Branch/","page":"Branch","title":"Branch","text":"StaticBranch","category":"page"},{"location":"formulation_library/Branch/#PowerSimulations.StaticBranch","page":"Branch","title":"PowerSimulations.StaticBranch","text":"Branch type to add unbounded flow variables and use flow constraints\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/Branch/","page":"Branch","title":"Branch","text":"","category":"page"},{"location":"formulation_library/Branch/#StaticBranchBounds","page":"Branch","title":"StaticBranchBounds","text":"","category":"section"},{"location":"formulation_library/Branch/","page":"Branch","title":"Branch","text":"StaticBranchBounds","category":"page"},{"location":"formulation_library/Branch/#PowerSimulations.StaticBranchBounds","page":"Branch","title":"PowerSimulations.StaticBranchBounds","text":"Branch type to add bounded flow variables and use flow constraints\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/Branch/","page":"Branch","title":"Branch","text":"","category":"page"},{"location":"formulation_library/Branch/#StaticBranchUnbounded","page":"Branch","title":"StaticBranchUnbounded","text":"","category":"section"},{"location":"formulation_library/Branch/","page":"Branch","title":"Branch","text":"StaticBranchUnbounded","category":"page"},{"location":"formulation_library/Branch/#PowerSimulations.StaticBranchUnbounded","page":"Branch","title":"PowerSimulations.StaticBranchUnbounded","text":"Branch type to avoid flow constraints\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/Branch/","page":"Branch","title":"Branch","text":"","category":"page"},{"location":"formulation_library/Branch/#HVDCTwoTerminalLossless","page":"Branch","title":"HVDCTwoTerminalLossless","text":"","category":"section"},{"location":"formulation_library/Branch/","page":"Branch","title":"Branch","text":"HVDCTwoTerminalLossless","category":"page"},{"location":"formulation_library/Branch/#PowerSimulations.HVDCTwoTerminalLossless","page":"Branch","title":"PowerSimulations.HVDCTwoTerminalLossless","text":"Branch type to represent lossless power flow on DC lines\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/Branch/","page":"Branch","title":"Branch","text":"","category":"page"},{"location":"formulation_library/Branch/#HVDCTwoTerminalDispatch","page":"Branch","title":"HVDCTwoTerminalDispatch","text":"","category":"section"},{"location":"formulation_library/Branch/","page":"Branch","title":"Branch","text":"HVDCTwoTerminalDispatch","category":"page"},{"location":"formulation_library/Branch/#PowerSimulations.HVDCTwoTerminalDispatch","page":"Branch","title":"PowerSimulations.HVDCTwoTerminalDispatch","text":"Branch type to represent lossy power flow on DC lines\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/Branch/","page":"Branch","title":"Branch","text":"","category":"page"},{"location":"formulation_library/Branch/#HVDCTwoTerminalUnbounded","page":"Branch","title":"HVDCTwoTerminalUnbounded","text":"","category":"section"},{"location":"formulation_library/Branch/","page":"Branch","title":"Branch","text":"HVDCTwoTerminalUnbounded","category":"page"},{"location":"formulation_library/Branch/#PowerSimulations.HVDCTwoTerminalUnbounded","page":"Branch","title":"PowerSimulations.HVDCTwoTerminalUnbounded","text":"Branch type to avoid flow constraints\n\n\n\n\n\n","category":"type"},{"location":"modeler_guide/problem_templates/#op_problem_template","page":"Operations ProblemTemplates","title":"Operations ProblemTemplates","text":"","category":"section"},{"location":"modeler_guide/problem_templates/","page":"Operations ProblemTemplates","title":"Operations ProblemTemplates","text":"Templates are used to specify the modeling properties of the devices and network that are going to he used to specify a problem. A ProblemTemplate is just a collection of DeviceModels that allows the user to specify the formulations of each set of devices (by device type) independently so that the modeler can adjust the level of detail according to the question of interest and the available data. For more information about valid DeviceModels and their mathematical representations, check out the Formulation Library.","category":"page"},{"location":"modeler_guide/problem_templates/#Building-a-ProblemTemplate","page":"Operations ProblemTemplates","title":"Building a ProblemTemplate","text":"","category":"section"},{"location":"modeler_guide/problem_templates/","page":"Operations ProblemTemplates","title":"Operations ProblemTemplates","text":"You can build a ProblemTemplate by adding a NetworkModel, DeviceModels, and ServiceModels.","category":"page"},{"location":"modeler_guide/problem_templates/","page":"Operations ProblemTemplates","title":"Operations ProblemTemplates","text":"template = ProblemTemplate()\nset_network_model!(template, NetworkModel(CopperPlatePowerModel))\nset_device_model!(template, PowerLoad, StaticPowerLoad)\nset_device_model!(template, ThermalStandard, ThermalBasicUnitCommitment)\nset_service_model!(template, VariableReserve{ReserveUp}, RangeReserve)","category":"page"},{"location":"modeler_guide/problem_templates/#Default-Templates","page":"Operations ProblemTemplates","title":"Default Templates","text":"","category":"section"},{"location":"modeler_guide/problem_templates/","page":"Operations ProblemTemplates","title":"Operations ProblemTemplates","text":"PowerSimulations.jl provides default templates for common operation problems. You can retrieve a default template and modify it according to your requirements. Currently supported default templates are:","category":"page"},{"location":"modeler_guide/problem_templates/","page":"Operations ProblemTemplates","title":"Operations ProblemTemplates","text":"template_economic_dispatch","category":"page"},{"location":"modeler_guide/problem_templates/#PowerSimulations.template_economic_dispatch","page":"Operations ProblemTemplates","title":"PowerSimulations.template_economic_dispatch","text":"template_economic_dispatch(; kwargs...) -> ProblemTemplate\n\n\ntemplate_economic_dispatch(; kwargs...)\n\nCreates a ProblemTemplate with default DeviceModels for an Economic Dispatch problem.\n\nExample\n\ntemplate = templateeconomicdispatch()\n\n\n# Accepted Key Words\n- `network::Type{<:PM.AbstractPowerModel}` : override default network model settings\n- `devices::Vector{DeviceModel}` : override default `DeviceModel` settings\n- `services::Vector{ServiceModel}` : override default `ServiceModel` settings\n\n\n\n\n\n","category":"function"},{"location":"modeler_guide/problem_templates/","page":"Operations ProblemTemplates","title":"Operations ProblemTemplates","text":"using PowerSimulations #hide\ntemplate_economic_dispatch()","category":"page"},{"location":"modeler_guide/problem_templates/","page":"Operations ProblemTemplates","title":"Operations ProblemTemplates","text":"template_unit_commitment","category":"page"},{"location":"modeler_guide/problem_templates/#PowerSimulations.template_unit_commitment","page":"Operations ProblemTemplates","title":"PowerSimulations.template_unit_commitment","text":"template_unit_commitment(; kwargs...) -> ProblemTemplate\n\n\ntemplate_unit_commitment(; kwargs...)\n\nCreates a ProblemTemplate with default DeviceModels for a Unit Commitment problem.\n\nExample\n\ntemplate = templateunitcommitment()\n\n\n# Accepted Key Words\n- `network::Type{<:PM.AbstractPowerModel}` : override default network model settings\n- `devices::Vector{DeviceModel}` : override default `DeviceModel` settings\n- `services::Vector{ServiceModel}` : override default `ServiceModel` settings\n\n\n\n\n\n","category":"function"},{"location":"modeler_guide/problem_templates/","page":"Operations ProblemTemplates","title":"Operations ProblemTemplates","text":"using PowerSimulations #hide\ntemplate_unit_commitment()","category":"page"},{"location":"modeler_guide/problem_templates/","page":"Operations ProblemTemplates","title":"Operations ProblemTemplates","text":"template_agc_reserve_deployment","category":"page"},{"location":"modeler_guide/problem_templates/#PowerSimulations.template_agc_reserve_deployment","page":"Operations ProblemTemplates","title":"PowerSimulations.template_agc_reserve_deployment","text":"template_agc_reserve_deployment(; kwargs...)\n\n\ntemplate_agc_reserve_deployment(; kwargs...)\n\nCreates a ProblemTemplate with default DeviceModels for an AGC Reserve Deployment Problem. This model doesn't support customization\n\nExample\n\ntemplate = agcreservedeployment()\n\n\n\n\n\n","category":"function"},{"location":"modeler_guide/problem_templates/","page":"Operations ProblemTemplates","title":"Operations ProblemTemplates","text":"using PowerSimulations #hide\ntemplate_agc_reserve_deployment()","category":"page"},{"location":"code_base_developer_guide/developer/#Guidelines-for-Developers","page":"Developer Guide","title":"Guidelines for Developers","text":"","category":"section"},{"location":"code_base_developer_guide/developer/","page":"Developer Guide","title":"Developer Guide","text":"In order to contribute to PowerSystems.jl repository please read the following sections of InfrastructureSystems.jl documentation in detail:","category":"page"},{"location":"code_base_developer_guide/developer/","page":"Developer Guide","title":"Developer Guide","text":"Style Guide\nContributing Guidelines","category":"page"},{"location":"code_base_developer_guide/developer/","page":"Developer Guide","title":"Developer Guide","text":"Pull requests are always welcome to fix bugs or add additional modeling capabilities.","category":"page"},{"location":"code_base_developer_guide/developer/","page":"Developer Guide","title":"Developer Guide","text":"All the code contributions need to include tests with a minimum coverage of 70%","category":"page"},{"location":"modeler_guide/modeling_faq/#Modeling-FAQ","page":"Modeling FAQ","title":"Modeling FAQ","text":"","category":"section"},{"location":"modeler_guide/modeling_faq/","page":"Modeling FAQ","title":"Modeling FAQ","text":"question: How do I reduce the amount of print on my REPL?\nThe print to the REPL is controlled with the logging. Check the Logging documentation page to see how to reduce the print out","category":"page"},{"location":"modeler_guide/modeling_faq/","page":"Modeling FAQ","title":"Modeling FAQ","text":"question: How do I print the optimizer logs to see the solution process?\nWhen specifying the DecisionModel or EmulationModel pass the keyword print_optimizer_log = true","category":"page"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"CurrentModule = PowerSimulations\nDocTestSetup = quote\n using PowerSimulations\nend","category":"page"},{"location":"api/PowerSimulations/#API-Reference","page":"API Reference","title":"API Reference","text":"","category":"section"},{"location":"api/PowerSimulations/#Table-of-Contents","page":"API Reference","title":"Table of Contents","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"Device Models\nDecision Models\nEmulation Models\nService Models\nSimulation Models\nVariables\nConstraints\nParameters","category":"page"},{"location":"api/PowerSimulations/#Device-Models","page":"API Reference","title":"Device Models","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"List of structures and methods for Device models","category":"page"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"DeviceModel","category":"page"},{"location":"api/PowerSimulations/#PowerSimulations.DeviceModel","page":"API Reference","title":"PowerSimulations.DeviceModel","text":"DeviceModel(\n ::Type{D},\n ::Type{B},\n feedforwards::Vector{<:AbstractAffectFeedforward}\n use_slacks::Bool,\n duals::Vector{DataType},\n services::Vector{ServiceModel}\n attributes::Dict{String, Any}\n)\n\nEstablishes the model for a particular device specified by type. Uses the keyword argument feedforward to enable passing values between operation model at simulation time\n\nArguments\n\n::Type{D} where D<:PSY.Device: Power System Device Type\n::Type{B} where B<:AbstractDeviceFormulation: Abstract Device Formulation\nfeedforward::Array{<:AbstractAffectFeedforward} = Vector{AbstractAffectFeedforward}() : use to pass parameters between models\nuse_slacks::Bool = false : Add slacks to the device model. Implementation is model dependent and not all models feature slacks\nduals::Vector{DataType} = Vector{DataType}(): use to pass constraint type to calculate the duals. The DataType needs to be a valid ConstraintType\ntime_series_names::Dict{Type{<:TimeSeriesParameter}, String} = get_default_time_series_names(D, B) : use to specify time series names associated to the device`\nattributes::Dict{String, Any} = get_default_attributes(D, B) : use to specify attributes to the device\n\nExample\n\nthermal_gens = DeviceModel(ThermalStandard, ThermalBasicUnitCommitment)\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#Formulations","page":"API Reference","title":"Formulations","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"Refer to the Formulations Page for each Abstract Device Formulation.","category":"page"},{"location":"api/PowerSimulations/#Problem-Templates","page":"API Reference","title":"Problem Templates","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"Refer to the Problem Templates Page for available ProblemTemplates.","category":"page"},{"location":"api/PowerSimulations/#Problem-Templates-2","page":"API Reference","title":"Problem Templates","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"Refer to the Problem Templates Page for available ProblemTemplates.","category":"page"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":" \n ","category":"page"},{"location":"api/PowerSimulations/#Service-Models","page":"API Reference","title":"Service Models","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"List of structures and methods for Service models","category":"page"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"ServiceModel","category":"page"},{"location":"api/PowerSimulations/#PowerSimulations.ServiceModel","page":"API Reference","title":"PowerSimulations.ServiceModel","text":"Establishes the model for a particular services specified by type. Uses the keyword argument use_service_name to assign the model to a service with the same name as the name in the template. Uses the keyword argument feedforward to enable passing values between operation model at simulation time\n\nArguments\n\n-::Type{D}: Power System Service Type -::Type{B}: Abstract Service Formulation\n\nAccepted Key Words\n\nfeedforward::Array{<:AbstractAffectFeedforward} : use to pass parameters between models\nuse_service_name::Bool : use the name as the name for the service\n\nExample\n\nreserves = ServiceModel(PSY.VariableReserve{PSY.ReserveUp}, RangeReserve)\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#Decision-Models","page":"API Reference","title":"Decision Models","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"DecisionModel\nDecisionModel(::Type{M} where {M <: DecisionProblem}, ::ProblemTemplate, ::PSY.System, ::Union{Nothing, JuMP.Model})\nDecisionModel(::AbstractString, ::MOI.OptimizerWithAttributes)\nbuild!(::DecisionModel)\nsolve!(::DecisionModel)","category":"page"},{"location":"api/PowerSimulations/#PowerSimulations.DecisionModel","page":"API Reference","title":"PowerSimulations.DecisionModel","text":"DecisionModel{M}(\n template::ProblemTemplate,\n sys::PSY.System,\n jump_model::Union{Nothing, JuMP.Model}=nothing;\n kwargs...) where {M<:DecisionProblem}\n\nBuild the optimization problem of type M with the specific system and template.\n\nArguments\n\n::Type{M} where M<:DecisionProblem: The abstract operation model type\ntemplate::ProblemTemplate: The model reference made up of transmission, devices, branches, and services.\nsys::PSY.System: the system created using Power Systems\njump_model::Union{Nothing, JuMP.Model}: Enables passing a custom JuMP model. Use with care\nname = nothing: name of model, string or symbol; defaults to the type of template converted to a symbol.\noptimizer::Union{Nothing,MOI.OptimizerWithAttributes} = nothing : The optimizer does not get serialized. Callers should pass whatever they passed to the original problem.\nhorizon::Int = UNSET_HORIZON: Manually specify the length of the forecast Horizon\nwarm_start::Bool = true: True will use the current operation point in the system to initialize variable values. False initializes all variables to zero. Default is true\nsystem_to_file::Bool = true:: True to create a copy of the system used in the model.\ninitialize_model::Bool = true: Option to decide to initialize the model or not.\ninitialization_file::String = \"\": This allows to pass pre-existing initialization values to avoid the solution of an optimization problem to find feasible initial conditions.\ndeserialize_initial_conditions::Bool = false: Option to deserialize conditions\nexport_pwl_vars::Bool = false: True to export all the pwl intermediate variables. It can slow down significantly the build and solve time.\nallow_fails::Bool = false: True to allow the simulation to continue even if the optimization step fails. Use with care.\noptimizer_solve_log_print::Bool = false: Uses JuMP.unset_silent() to print the optimizer's log. By default all solvers are set to MOI.Silent()\ndetailed_optimizer_stats::Bool = false: True to save detailed optimizer stats log.\ncalculate_conflict::Bool = false: True to use solver to calculate conflicts for infeasible problems. Only specific solvers are able to calculate conflicts.\ndirect_mode_optimizer::Bool = false: True to use the solver in direct mode. Creates a JuMP.direct_model.\nstore_variable_names::Bool = false: to store variable names in optimization model. Decreases the build times.\nrebuild_model::Bool = false: It will force the rebuild of the underlying JuMP model with each call to update the model. It increases solution times, use only if the model can't be updated in memory.\ninitial_time::Dates.DateTime = UNSET_INI_TIME: Initial Time for the model solve.\ntime_series_cache_size::Int = IS.TIME_SERIES_CACHE_SIZE_BYTES: Size in bytes to cache for each time array. Default is 1 MiB. Set to 0 to disable.\n\nExample\n\ntemplate = ProblemTemplate(CopperPlatePowerModel, devices, branches, services)\nOpModel = DecisionModel(MockOperationProblem, template, system)\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#PowerSimulations.DecisionModel-Tuple{Type{M} where M<:PowerSimulations.DecisionProblem, ProblemTemplate, System, Union{Nothing, JuMP.Model}}","page":"API Reference","title":"PowerSimulations.DecisionModel","text":"DecisionModel(\n ::Type{M<:PowerSimulations.DecisionProblem},\n template::ProblemTemplate,\n sys::System\n) -> DecisionModel\nDecisionModel(\n ::Type{M<:PowerSimulations.DecisionProblem},\n template::ProblemTemplate,\n sys::System,\n jump_model::Union{Nothing, JuMP.Model};\n kwargs...\n) -> DecisionModel\n\n\nBuild the optimization problem of type M with the specific system and template\n\nArguments\n\n::Type{M} where M<:DecisionProblem: The abstract operation model type\ntemplate::ProblemTemplate: The model reference made up of transmission, devices, branches, and services.\nsys::PSY.System: the system created using Power Systems\njump_model::Union{Nothing, JuMP.Model} = nothing: Enables passing a custom JuMP model. Use with care.\n\nExample\n\ntemplate = ProblemTemplate(CopperPlatePowerModel, devices, branches, services)\nproblem = DecisionModel(MyOpProblemType, template, system, optimizer)\n\n\n\n\n\n","category":"method"},{"location":"api/PowerSimulations/#PowerSimulations.DecisionModel-Tuple{AbstractString, MathOptInterface.OptimizerWithAttributes}","page":"API Reference","title":"PowerSimulations.DecisionModel","text":"DecisionModel(\n directory::AbstractString,\n optimizer::MathOptInterface.OptimizerWithAttributes;\n jump_model,\n system\n) -> Any\n\n\nConstruct an DecisionProblem from a serialized file.\n\nArguments\n\ndirectory::AbstractString: Directory containing a serialized model\njump_model::Union{Nothing, JuMP.Model} = nothing: The JuMP model does not get serialized. Callers should pass whatever they passed to the original problem.\noptimizer::Union{Nothing,MOI.OptimizerWithAttributes} = nothing: The optimizer does not get serialized. Callers should pass whatever they passed to the original problem.\nsystem::Union{Nothing, PSY.System}: Optionally, the system used for the model. If nothing and systofile was set to true when the model was created, the system will be deserialized from a file.\n\n\n\n\n\n","category":"method"},{"location":"api/PowerSimulations/#PowerSimulations.build!-Tuple{DecisionModel}","page":"API Reference","title":"PowerSimulations.build!","text":"build!(\n model::DecisionModel;\n output_dir,\n recorders,\n console_level,\n file_level,\n disable_timer_outputs\n)\n\n\nBuild the Decision Model based on the specified DecisionProblem.\n\nArguments\n\nmodel::DecisionModel{<:DecisionProblem}: DecisionModel object\noutput_dir::String: Output directory for results\nrecorders::Vector{Symbol} = []: recorder names to register\nconsole_level = Logging.Error:\nfile_level = Logging.Info:\ndisable_timer_outputs = false : Enable/Disable timing outputs\n\n\n\n\n\n","category":"method"},{"location":"api/PowerSimulations/#PowerSimulations.solve!-Tuple{DecisionModel}","page":"API Reference","title":"PowerSimulations.solve!","text":"solve!(\n model::DecisionModel;\n export_problem_results,\n console_level,\n file_level,\n disable_timer_outputs,\n serialize,\n kwargs...\n) -> RunStatus\n\n\nDefault solve method for models that conform to the requirements of DecisionModel{<: DecisionProblem}.\n\nThis will call build! on the model if it is not already built. It will forward all keyword arguments to that function.\n\nArguments\n\nmodel::OperationModel = model: operation model\nexport_problem_results::Bool = false: If true, export ProblemResults DataFrames to CSV files. Reduces solution times during simulation.\nconsole_level = Logging.Error:\nfile_level = Logging.Info:\ndisable_timer_outputs = false : Enable/Disable timing outputs\nserialize::Bool = true: If true, serialize the model to a file to allow re-execution later.\n\nExamples\n\nresults = solve!(OpModel)\nresults = solve!(OpModel, export_problem_results = true)\n\n\n\n\n\n","category":"method"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":" \n ","category":"page"},{"location":"api/PowerSimulations/#Emulation-Models","page":"API Reference","title":"Emulation Models","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"EmulationModel\nEmulationModel(::Type{M} where {M <: EmulationProblem}, ::ProblemTemplate, ::PSY.System, ::Union{Nothing, JuMP.Model})\nEmulationModel(::AbstractString, ::MOI.OptimizerWithAttributes)\nbuild!(::EmulationModel)\nrun!(::EmulationModel)","category":"page"},{"location":"api/PowerSimulations/#PowerSimulations.EmulationModel","page":"API Reference","title":"PowerSimulations.EmulationModel","text":"EmulationModel{M}(\n template::ProblemTemplate,\n sys::PSY.System,\n jump_model::Union{Nothing, JuMP.Model}=nothing;\n kwargs...) where {M<:EmulationProblem}\n\nBuild the optimization problem of type M with the specific system and template.\n\nArguments\n\n::Type{M} where M<:EmulationProblem: The abstract Emulation model type\ntemplate::ProblemTemplate: The model reference made up of transmission, devices, branches, and services.\nsys::PSY.System: the system created using Power Systems\njump_model::Union{Nothing, JuMP.Model}: Enables passing a custom JuMP model. Use with care\nname = nothing: name of model, string or symbol; defaults to the type of template converted to a symbol.\noptimizer::Union{Nothing,MOI.OptimizerWithAttributes} = nothing : The optimizer does not get serialized. Callers should pass whatever they passed to the original problem.\nwarm_start::Bool = true: True will use the current operation point in the system to initialize variable values. False initializes all variables to zero. Default is true\nsystem_to_file::Bool = true:: True to create a copy of the system used in the model.\ninitialize_model::Bool = true: Option to decide to initialize the model or not.\ninitialization_file::String = \"\": This allows to pass pre-existing initialization values to avoid the solution of an optimization problem to find feasible initial conditions.\ndeserialize_initial_conditions::Bool = false: Option to deserialize conditions\nexport_pwl_vars::Bool = false: True to export all the pwl intermediate variables. It can slow down significantly the build and solve time.\nallow_fails::Bool = false: True to allow the simulation to continue even if the optimization step fails. Use with care.\ncalculate_conflict::Bool = false: True to use solver to calculate conflicts for infeasible problems. Only specific solvers are able to calculate conflicts.\noptimizer_solve_log_print::Bool = false: Uses JuMP.unset_silent() to print the optimizer's log. By default all solvers are set to MOI.Silent()\ndetailed_optimizer_stats::Bool = false: True to save detailed optimizer stats log.\ndirect_mode_optimizer::Bool = false: True to use the solver in direct mode. Creates a JuMP.direct_model.\nstore_variable_names::Bool = false: True to store variable names in optimization model.\nrebuild_model::Bool = false: It will force the rebuild of the underlying JuMP model with each call to update the model. It increases solution times, use only if the model can't be updated in memory.\ninitial_time::Dates.DateTime = UNSET_INI_TIME: Initial Time for the model solve.\ntime_series_cache_size::Int = IS.TIME_SERIES_CACHE_SIZE_BYTES: Size in bytes to cache for each time array. Default is 1 MiB. Set to 0 to disable.\n\nExample\n\ntemplate = ProblemTemplate(CopperPlatePowerModel, devices, branches, services)\nOpModel = EmulationModel(MockEmulationProblem, template, system)\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#PowerSimulations.EmulationModel-Tuple{Type{M} where M<:PowerSimulations.EmulationProblem, ProblemTemplate, System, Union{Nothing, JuMP.Model}}","page":"API Reference","title":"PowerSimulations.EmulationModel","text":"EmulationModel(\n ::Type{M<:PowerSimulations.EmulationProblem},\n template::ProblemTemplate,\n sys::System\n) -> EmulationModel\nEmulationModel(\n ::Type{M<:PowerSimulations.EmulationProblem},\n template::ProblemTemplate,\n sys::System,\n jump_model::Union{Nothing, JuMP.Model};\n kwargs...\n) -> EmulationModel\n\n\nBuild the optimization problem of type M with the specific system and template\n\nArguments\n\n::Type{M} where M<:EmulationProblem: The abstract Emulation model type\ntemplate::ProblemTemplate: The model reference made up of transmission, devices, branches, and services.\nsys::PSY.System: the system created using Power Systems\njump_model::Union{Nothing, JuMP.Model}: Enables passing a custom JuMP model. Use with care\n\nExample\n\ntemplate = ProblemTemplate(CopperPlatePowerModel, devices, branches, services)\nproblem = EmulationModel(MyEmProblemType, template, system, optimizer)\n\n\n\n\n\n","category":"method"},{"location":"api/PowerSimulations/#PowerSimulations.EmulationModel-Tuple{AbstractString, MathOptInterface.OptimizerWithAttributes}","page":"API Reference","title":"PowerSimulations.EmulationModel","text":"EmulationModel(\n directory::AbstractString,\n optimizer::MathOptInterface.OptimizerWithAttributes;\n jump_model,\n system,\n kwargs...\n) -> Any\n\n\nConstruct an EmulationProblem from a serialized file.\n\nArguments\n\ndirectory::AbstractString: Directory containing a serialized model.\noptimizer::MOI.OptimizerWithAttributes: The optimizer does not get serialized. Callers should pass whatever they passed to the original problem.\njump_model::Union{Nothing, JuMP.Model} = nothing: The JuMP model does not get serialized. Callers should pass whatever they passed to the original problem.\nsystem::Union{Nothing, PSY.System}: Optionally, the system used for the model. If nothing and systofile was set to true when the model was created, the system will be deserialized from a file.\n\n\n\n\n\n","category":"method"},{"location":"api/PowerSimulations/#PowerSimulations.build!-Tuple{EmulationModel}","page":"API Reference","title":"PowerSimulations.build!","text":"build!(\n model::EmulationModel;\n executions,\n output_dir,\n recorders,\n console_level,\n file_level,\n disable_timer_outputs\n)\n\n\nImplementation of build for any EmulationProblem\n\n\n\n\n\n","category":"method"},{"location":"api/PowerSimulations/#PowerSimulations.run!-Tuple{EmulationModel}","page":"API Reference","title":"PowerSimulations.run!","text":"run!(\n model::EmulationModel;\n export_problem_results,\n console_level,\n file_level,\n disable_timer_outputs,\n serialize,\n kwargs...\n) -> RunStatus\n\n\nDefault run method for problems that conform to the requirements of EmulationModel{<: EmulationProblem}\n\nThis will call build! on the model if it is not already built. It will forward all keyword arguments to that function.\n\nArguments\n\nmodel::EmulationModel = model: Emulation model\noptimizer::MOI.OptimizerWithAttributes: The optimizer that is used to solve the model\nexecutions::Int: Number of executions for the emulator run\nexport_problem_results::Bool: If true, export ProblemResults DataFrames to CSV files.\noutput_dir::String: Required if the model is not already built, otherwise ignored\nenable_progress_bar::Bool: Enables/Disable progress bar printing\nserialize::Bool: If true, serialize the model to a file to allow re-execution later.\n\nExamples\n\nstatus = run!(model; optimizer = GLPK.Optimizer, executions = 10)\nstatus = run!(model; output_dir = ./model_output, optimizer = GLPK.Optimizer, executions = 10)\n\n\n\n\n\n","category":"method"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":" \n ","category":"page"},{"location":"api/PowerSimulations/#Simulation-Models","page":"API Reference","title":"Simulation Models","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"Refer to the Simulations Page to explanations on how to setup a Simulation, with Sequencing and Feedforwards.","category":"page"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"SimulationModels\nSimulationSequence\nSimulation\nSimulation(::AbstractString, ::Dict)\nbuild!(::Simulation)\nexecute!(::Simulation)","category":"page"},{"location":"api/PowerSimulations/#PowerSimulations.SimulationModels","page":"API Reference","title":"PowerSimulations.SimulationModels","text":"SimulationModels(\n decision_models::Vector{<:DecisionModel},\n emulation_models::Union{Nothing, EmulationModel}\n)\n\nStores the OperationProblem definitions to be used in the simulation. When creating the SimulationModels, the order in which the models are created determines the order on which the simulation is executed.\n\nArguments\n\ndecision_models::Vector{<:DecisionModel}: Vector of decision models.\nemulation_models::Union{Nothing, EmulationModel}: Optional argument to include\n\nan EmulationModel in the Simulation\n\nExample\n\ntemplate_uc = template_unit_commitment()\ntemplate_ed = template_economic_dispatch()\nmy_decision_model_uc = DecisionModel(template_1, sys_uc, optimizer, name = \"UC\")\nmy_decision_model_ed = DecisionModel(template_ed, sys_ed, optimizer, name = \"ED\")\nmodels = SimulationModels(\n decision_models = [\n my_decision_model_uc,\n my_decision_model_ed\n ]\n)\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#PowerSimulations.SimulationSequence","page":"API Reference","title":"PowerSimulations.SimulationSequence","text":"SimulationSequence(\n models::SimulationModels,\n feedforward::Dict{String, Vector{<:AbstractAffectFeedforward}}\n ini_cond_chronology::InitialConditionChronology\n)\n\nConstruct the simulation sequence between decision and emulation models.\n\nArguments\n\nmodels::SimulationModels: Vector of decisions and emulation models.\nfeedforward = Dict{String, Vector{<:AbstractAffectFeedforward}}(): Optional dictionary to specify how information\n\nand variables are exchanged between decision and emulation models.\n\nini_cond_chronology::nitialConditionChronology = InterProblemChronology(): TODO\n\nExample\n\ntemplate_uc = template_unit_commitment()\ntemplate_ed = template_economic_dispatch()\nmy_decision_model_uc = DecisionModel(template_1, sys_uc, optimizer, name = \"UC\")\nmy_decision_model_ed = DecisionModel(template_ed, sys_ed, optimizer, name = \"ED\")\nmodels = SimulationModels(\n decision_models = [\n my_decision_model_uc,\n my_decision_model_ed\n ]\n)\n# The following sequence set the commitment variables (`OnVariable`) for `ThermalStandard` units from UC to ED.\nsequence = SimulationSequence(;\n models = models,\n feedforwards = Dict(\n \"ED\" => [\n SemiContinuousFeedforward(;\n component_type = ThermalStandard,\n source = OnVariable,\n affected_values = [ActivePowerVariable],\n ),\n ],\n ),\n)\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#PowerSimulations.Simulation","page":"API Reference","title":"PowerSimulations.Simulation","text":"Simulation(\n sequence::SimulationSequence,\n name::String,\n steps::Int\n models::SimulationModels,\n simulation_folder::String,\n initial_time::Union{Nothing, Dates.DateTime}\n)\n\nConstruct the Simulation structure to run the sequence of decision and emulation models specified.\n\nArguments\n\n-sequence::SimulationSequence: Simulation sequence that specify how the decision and emulation models will be executed. -name::String: Name of the Simulation -steps::Int: Number of steps on which the sequence of models will be executed -models::SimulationModels: List of Decision and Emulation Models -simulation_folder::String: Folder on which results will be stored -initial_time::Union{Nothing, Dates.DateTime} = nothing: Initial time of which the simulation starts. If nothing it will default to the first timestamp of time series of the system.\n\nExample\n\ntemplate_uc = template_unit_commitment()\ntemplate_ed = template_economic_dispatch()\nmy_decision_model_uc = DecisionModel(template_1, sys_uc, optimizer, name = \"UC\")\nmy_decision_model_ed = DecisionModel(template_ed, sys_ed, optimizer, name = \"ED\")\nmodels = SimulationModels(\n decision_models = [\n my_decision_model_uc,\n my_decision_model_ed\n ]\n)\n# The following sequence set the commitment variables (`OnVariable`) for `ThermalStandard` units from UC to ED.\nsequence = SimulationSequence(;\n models = models,\n feedforwards = Dict(\n \"ED\" => [\n SemiContinuousFeedforward(;\n component_type = ThermalStandard,\n source = OnVariable,\n affected_values = [ActivePowerVariable],\n ),\n ],\n ),\n)\n\nsim = Simulation(\n sequence = sequence,\n name = \"Sim\",\n steps = 5,\n models = models,\n simulation_folder = mktempdir(cleanup=true),\n)\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#PowerSimulations.Simulation-Tuple{AbstractString, Dict}","page":"API Reference","title":"PowerSimulations.Simulation","text":"Simulation(directory::AbstractString, model_info::Dict)\n\n\nConstructs Simulation from a serialized directory. Callers should pass any kwargs here that they passed to the original Simulation.\n\nArguments\n\ndirectory::AbstractString: the directory returned from the call to serialize\nmodel_info::Dict: Two-level dictionary containing model parameters that cannot be serialized. The outer dict should be keyed by the problem name. The inner dict must contain 'optimizer' and may contain 'jump_model'. These should be the same values used for the original simulation.\n\n\n\n\n\n","category":"method"},{"location":"api/PowerSimulations/#PowerSimulations.build!-Tuple{Simulation}","page":"API Reference","title":"PowerSimulations.build!","text":"build!(\n sim::Simulation;\n recorders,\n console_level,\n file_level,\n serialize,\n partitions,\n index\n) -> BuildStatus\n\n\nBuild the Simulation, problems and the related folder structure.\n\nArguments\n\nsim::Simulation: simulation object\nrecorders::Vector{Symbol} = []: recorder names to register\nserialize::Bool = true: serializes the simulation objects in the simulation\nconsole_level = Logging.Error:\nfile_level = Logging.Info:\n\n\n\n\n\n","category":"method"},{"location":"api/PowerSimulations/#PowerSimulations.execute!-Tuple{Simulation}","page":"API Reference","title":"PowerSimulations.execute!","text":"execute!(sim::Simulation; kwargs...) -> RunStatus\n\n\nSolves the simulation model for sequential Simulations.\n\nArguments\n\nsim::Simulation=sim: simulation object created by Simulation()\n\nThe optional keyword argument exports controls exporting of results to CSV files as the simulation runs. Refer to export_results for a description of this argument.\n\nExample\n\nsim = Simulation(\"Test\", 7, problems, \"/Users/folder\")\nexecute!(sim::Simulation; kwargs...)\n\n\n\n\n\n","category":"method"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":" \n ","category":"page"},{"location":"api/PowerSimulations/#Variables","page":"API Reference","title":"Variables","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"For a list of variables for each device refer to its Formulations page.","category":"page"},{"location":"api/PowerSimulations/#Common-Variables","page":"API Reference","title":"Common Variables","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"ActivePowerVariable\nReactivePowerVariable\nPieceWiseLinearCostVariable","category":"page"},{"location":"api/PowerSimulations/#PowerSimulations.ActivePowerVariable","page":"API Reference","title":"PowerSimulations.ActivePowerVariable","text":"Struct to dispatch the creation of Active Power Variables\n\nDocs abbreviation: Pg\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#PowerSimulations.ReactivePowerVariable","page":"API Reference","title":"PowerSimulations.ReactivePowerVariable","text":"Struct to dispatch the creation of Reactive Power Variables\n\nDocs abbreviation: Qg\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#Thermal-Unit-Variables","page":"API Reference","title":"Thermal Unit Variables","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"OnVariable\nStartVariable\nStopVariable\nTimeDurationOn\nTimeDurationOff\nHotStartVariable\nWarmStartVariable\nColdStartVariable\nPowerAboveMinimumVariable","category":"page"},{"location":"api/PowerSimulations/#PowerSimulations.OnVariable","page":"API Reference","title":"PowerSimulations.OnVariable","text":"Struct to dispatch the creation of a binary commitment status variable\n\nDocs abbreviation: u\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#PowerSimulations.PowerAboveMinimumVariable","page":"API Reference","title":"PowerSimulations.PowerAboveMinimumVariable","text":"Struct to dispatch the creation of Active Power Variables above minimum power for Thermal Compact formulations\n\nDocs abbreviation: hatPg\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#Storage-Unit-Variables","page":"API Reference","title":"Storage Unit Variables","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"ReservationVariable","category":"page"},{"location":"api/PowerSimulations/#PowerSimulations.ReservationVariable","page":"API Reference","title":"PowerSimulations.ReservationVariable","text":"Struct to dispatch the creation of binary storage charge reservation variable\n\nDocs abbreviation: r\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#Branches-and-Network-Variables","page":"API Reference","title":"Branches and Network Variables","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"FlowActivePowerVariable\nFlowActivePowerFromToVariable\nFlowActivePowerToFromVariable\nFlowReactivePowerFromToVariable\nFlowReactivePowerToFromVariable\nPhaseShifterAngle\nHVDCLosses\nHVDCFlowDirectionVariable\nVoltageMagnitude\nVoltageAngle","category":"page"},{"location":"api/PowerSimulations/#PowerSimulations.FlowActivePowerVariable","page":"API Reference","title":"PowerSimulations.FlowActivePowerVariable","text":"Struct to dispatch the creation of bidirectional Active Power Flow Variables\n\nDocs abbreviation: P\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#PowerSimulations.FlowActivePowerFromToVariable","page":"API Reference","title":"PowerSimulations.FlowActivePowerFromToVariable","text":"Struct to dispatch the creation of unidirectional Active Power Flow Variables\n\nDocs abbreviation: overrightarrowP\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#PowerSimulations.FlowActivePowerToFromVariable","page":"API Reference","title":"PowerSimulations.FlowActivePowerToFromVariable","text":"Struct to dispatch the creation of unidirectional Active Power Flow Variables\n\nDocs abbreviation: overleftarrowP\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#PowerSimulations.FlowReactivePowerFromToVariable","page":"API Reference","title":"PowerSimulations.FlowReactivePowerFromToVariable","text":"Struct to dispatch the creation of unidirectional Reactive Power Flow Variables\n\nDocs abbreviation: overrightarrowQ\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#PowerSimulations.FlowReactivePowerToFromVariable","page":"API Reference","title":"PowerSimulations.FlowReactivePowerToFromVariable","text":"Struct to dispatch the creation of unidirectional Reactive Power Flow Variables\n\nDocs abbreviation: overleftarrowQ\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#Regulation-and-Services-Variables","page":"API Reference","title":"Regulation and Services Variables","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"ActivePowerReserveVariable\nServiceRequirementVariable\nDeltaActivePowerUpVariable\nDeltaActivePowerDownVariable\nAdditionalDeltaActivePowerUpVariable\nAdditionalDeltaActivePowerDownVariable\nAreaMismatchVariable\nSteadyStateFrequencyDeviation\nSmoothACE\nSystemBalanceSlackUp\nSystemBalanceSlackDown\nReserveRequirementSlack","category":"page"},{"location":"api/PowerSimulations/#PowerSimulations.ActivePowerReserveVariable","page":"API Reference","title":"PowerSimulations.ActivePowerReserveVariable","text":"Struct to dispatch the creation of Active Power Reserve Variables\n\nDocs abbreviation: Pr\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":" \n ","category":"page"},{"location":"api/PowerSimulations/#Constraints","page":"API Reference","title":"Constraints","text":"","category":"section"},{"location":"api/PowerSimulations/#Common-Constraints","page":"API Reference","title":"Common Constraints","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"PieceWiseLinearCostConstraint\n","category":"page"},{"location":"api/PowerSimulations/#Network-Constraints","page":"API Reference","title":"Network Constraints","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"AreaDispatchBalanceConstraint\nAreaParticipationAssignmentConstraint\nBalanceAuxConstraint\nCopperPlateBalanceConstraint\nFrequencyResponseConstraint\nNodalBalanceActiveConstraint\nNodalBalanceReactiveConstraint","category":"page"},{"location":"api/PowerSimulations/#Power-Variable-Limit-Constraints","page":"API Reference","title":"Power Variable Limit Constraints","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"ActivePowerVariableLimitsConstraint\nReactivePowerVariableLimitsConstraint\nActivePowerVariableTimeSeriesLimitsConstraint\nInputActivePowerVariableLimitsConstraint\nOutputActivePowerVariableLimitsConstraint","category":"page"},{"location":"api/PowerSimulations/#Regulation-and-Services-Constraints","page":"API Reference","title":"Regulation and Services Constraints","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"ParticipationAssignmentConstraint\nRegulationLimitsConstraint\nRequirementConstraint\nReserveEnergyCoverageConstraint\nReservePowerConstraint","category":"page"},{"location":"api/PowerSimulations/#Thermal-Unit-Constraints","page":"API Reference","title":"Thermal Unit Constraints","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"ActiveRangeICConstraint\nCommitmentConstraint\nDurationConstraint\nRampConstraint\nRampLimitConstraint\nStartupInitialConditionConstraint\nStartupTimeLimitTemperatureConstraint","category":"page"},{"location":"api/PowerSimulations/#Renewable-Unit-Constraints","page":"API Reference","title":"Renewable Unit Constraints","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"EqualityConstraint\n","category":"page"},{"location":"api/PowerSimulations/#Branches-Constraints","page":"API Reference","title":"Branches Constraints","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"AbsoluteValueConstraint\nFlowLimitFromToConstraint\nFlowLimitToFromConstraint\nFlowRateConstraint\nFlowRateConstraintFromTo\nFlowRateConstraintToFrom\nHVDCDirection\nHVDCLossesAbsoluteValue\nHVDCPowerBalance\nNetworkFlowConstraint\nRateLimitConstraint\nRateLimitConstraintFromTo\nRateLimitConstraintToFrom\nPhaseAngleControlLimit","category":"page"},{"location":"api/PowerSimulations/#Feedforward-Constraints","page":"API Reference","title":"Feedforward Constraints","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"FeedforwardSemiContinousConstraint\nFeedforwardIntegralLimitConstraint\nFeedforwardUpperBoundConstraint\nFeedforwardLowerBoundConstraint\nFeedforwardEnergyTargetConstraint","category":"page"},{"location":"api/PowerSimulations/#Parameters","page":"API Reference","title":"Parameters","text":"","category":"section"},{"location":"api/PowerSimulations/#Time-Series-Parameters","page":"API Reference","title":"Time Series Parameters","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"ActivePowerTimeSeriesParameter\nReactivePowerTimeSeriesParameter\nRequirementTimeSeriesParameter","category":"page"},{"location":"api/PowerSimulations/#PowerSimulations.ActivePowerTimeSeriesParameter","page":"API Reference","title":"PowerSimulations.ActivePowerTimeSeriesParameter","text":"Parameter to define active power time series\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#PowerSimulations.ReactivePowerTimeSeriesParameter","page":"API Reference","title":"PowerSimulations.ReactivePowerTimeSeriesParameter","text":"Parameter to define reactive power time series\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#PowerSimulations.RequirementTimeSeriesParameter","page":"API Reference","title":"PowerSimulations.RequirementTimeSeriesParameter","text":"Paramter to define requirement time series\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#Variable-Value-Parameters","page":"API Reference","title":"Variable Value Parameters","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"UpperBoundValueParameter\nLowerBoundValueParameter\nOnStatusParameter\nEnergyLimitParameter\nFixValueParameter\nEnergyTargetParameter","category":"page"},{"location":"api/PowerSimulations/#PowerSimulations.UpperBoundValueParameter","page":"API Reference","title":"PowerSimulations.UpperBoundValueParameter","text":"Parameter to define variable upper bound\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#PowerSimulations.LowerBoundValueParameter","page":"API Reference","title":"PowerSimulations.LowerBoundValueParameter","text":"Parameter to define variable lower bound\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#PowerSimulations.OnStatusParameter","page":"API Reference","title":"PowerSimulations.OnStatusParameter","text":"Parameter to define unit commitment status\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#PowerSimulations.FixValueParameter","page":"API Reference","title":"PowerSimulations.FixValueParameter","text":"Parameter to FixValueParameter\n\n\n\n\n\n","category":"type"},{"location":"api/PowerSimulations/#Objective-Function-Parameters","page":"API Reference","title":"Objective Function Parameters","text":"","category":"section"},{"location":"api/PowerSimulations/","page":"API Reference","title":"API Reference","text":"CostFunctionParameter","category":"page"},{"location":"api/PowerSimulations/#PowerSimulations.CostFunctionParameter","page":"API Reference","title":"PowerSimulations.CostFunctionParameter","text":"Parameter to define cost function coefficient\n\n\n\n\n\n","category":"type"},{"location":"tutorials/basics_of_developing_models/#Basics-of-Developing-Operation-Models","page":"Basics of Developing Operation Models","title":"Basics of Developing Operation Models","text":"","category":"section"},{"location":"tutorials/basics_of_developing_models/","page":"Basics of Developing Operation Models","title":"Basics of Developing Operation Models","text":"Check the page PowerSimulations Structure for more background on PowerSimulations.jl","category":"page"},{"location":"modeler_guide/definitions/#Definitions","page":"Definitions","title":"Definitions","text":"","category":"section"},{"location":"modeler_guide/definitions/#D","page":"Definitions","title":"D","text":"","category":"section"},{"location":"modeler_guide/definitions/","page":"Definitions","title":"Definitions","text":"Decision Problem: A decision problem calculates the desired system operation based on forecasts of uncertain inputs and information about the state of the system. The output of a decision problem represents the policies used to drive the set-points of the system's devices, like generators or switches, and depends on the purpose of the problem. See the Decision Model Tutorial to learn more about solving individual problems.\nDevice Formulation: The model of a device that is incorporated into a large system optimization models. For instance, the storage device model used inside of a Unit Commitment (UC) problem. A device model needs to follow some requirements to be integrated into operation problems.","category":"page"},{"location":"modeler_guide/definitions/#E","page":"Definitions","title":"E","text":"","category":"section"},{"location":"modeler_guide/definitions/","page":"Definitions","title":"Definitions","text":"Emulation Problem: An emulation problem is used to mimic the system's behavior subject to an incoming decision and the realization of a forecasted inputs. The solution of the emulator produces outputs representative of the system performance when operating subject the policies resulting from the decision models.","category":"page"},{"location":"modeler_guide/definitions/#H","page":"Definitions","title":"H","text":"","category":"section"},{"location":"modeler_guide/definitions/","page":"Definitions","title":"Definitions","text":"Horizon: The number of steps in the look-ahead of a decision problem. For instance, a Day-Ahead problem usually has a 48 step horizon. Check the time Time Series Data Section in PowerSystems.jl","category":"page"},{"location":"modeler_guide/definitions/#I","page":"Definitions","title":"I","text":"","category":"section"},{"location":"modeler_guide/definitions/","page":"Definitions","title":"Definitions","text":"Interval: The amount of time between updates to the decision problem. For instance, Day-Ahead problems usually have a 24-hour intervals and Real-Time problems have 5-minute intervals. Check the time Time Series Data Section in PowerSystems.jl","category":"page"},{"location":"modeler_guide/definitions/#R","page":"Definitions","title":"R","text":"","category":"section"},{"location":"modeler_guide/definitions/","page":"Definitions","title":"Definitions","text":"Resolution: The amount of time between timesteps in a simulation. For instance 1-hour or 5-minutes. In Julia these are defined using the syntax Hour(1) and Minute(5). Check the time Time Series Data Section in PowerSystems.jl","category":"page"},{"location":"modeler_guide/debugging_infeasible_models/#Debugging-infeasible-models","page":"Debugging infeasible models","title":"Debugging infeasible models","text":"","category":"section"},{"location":"modeler_guide/debugging_infeasible_models/","page":"Debugging infeasible models","title":"Debugging infeasible models","text":"Getting infeasible solutions to models is a common occurrence in operations simulations, there are multiple reasons why this can happen. PowerSimulations.jl has several tools to help debug this situation.","category":"page"},{"location":"modeler_guide/debugging_infeasible_models/#Adding-slacks-to-the-model","page":"Debugging infeasible models","title":"Adding slacks to the model","text":"","category":"section"},{"location":"modeler_guide/debugging_infeasible_models/#Getting-the-infeasibility-conflict","page":"Debugging infeasible models","title":"Getting the infeasibility conflict","text":"","category":"section"},{"location":"modeler_guide/psi_structure/#psi_structure","page":"PowerSimulations.jl Modeling Structure","title":"PowerSimulations.jl Modeling Structure","text":"","category":"section"},{"location":"modeler_guide/psi_structure/","page":"PowerSimulations.jl Modeling Structure","title":"PowerSimulations.jl Modeling Structure","text":"PowerSimulations enables the simulation of a sequence of power systems optimization problems and provides user control over each aspect of the simulation configuration. Specifically:","category":"page"},{"location":"modeler_guide/psi_structure/","page":"PowerSimulations.jl Modeling Structure","title":"PowerSimulations.jl Modeling Structure","text":"mathematical formulations can be selected for each component with DeviceModel and ServiceModel\na problem can be defined by creating model entries in a Operations ProblemTemplates\nmodels (DecisionModel or EmulationModel) can be built by applying a ProblemTemplate to a System and can be executed/solved in isolation or as part of a Simulation\nSimulations can be defined and executed by sequencing one or more models and defining how and when data flows between models.","category":"page"},{"location":"modeler_guide/psi_structure/","page":"PowerSimulations.jl Modeling Structure","title":"PowerSimulations.jl Modeling Structure","text":"question: What is the difference between a Model and a Problem?\nA \"Problem\" is an abstract mathematical description of how to represent power system behavior, whereas a \"Model\" is a concrete representation of a \"Problem\" applied to a dataset. I.e. once a Problem is populated with data describing all the loads, generators, lines, etc., it becomes a Model.","category":"page"},{"location":"formulation_library/General/#formulation_library","page":"General","title":"Formulations","text":"","category":"section"},{"location":"formulation_library/General/","page":"General","title":"General","text":"Modeling formulations are created by dispatching on abstract subtypes of PowerSimulations.AbstractDeviceFormulation","category":"page"},{"location":"formulation_library/General/#FixedOutput","page":"General","title":"FixedOutput","text":"","category":"section"},{"location":"formulation_library/General/","page":"General","title":"General","text":"FixedOutput","category":"page"},{"location":"formulation_library/General/#PowerSimulations.FixedOutput","page":"General","title":"PowerSimulations.FixedOutput","text":"Formulation type to augment the power balance constraint expression with a time series parameter\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/General/","page":"General","title":"General","text":"Variables:","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"No variables are created for DeviceModel(<:DeviceType, FixedOutput)","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"Static Parameters:","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"ThermalGen:\nPg^textmax = PowerSystems.get_max_active_power(device)\nQg^textmax = PowerSystems.get_max_reactive_power(device)\nStorage:\nPg^textmax = PowerSystems.get_max_active_power(device)\nQg^textmax = PowerSystems.get_max_reactive_power(device)","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"Time Series Parameters:","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"using PowerSimulations\nusing PowerSystems\nusing DataFrames\nusing Latexify\ncombo_tables = []\nfor t in [RenewableGen, ThermalGen, HydroGen, ElectricLoad]\n combos = PowerSimulations.get_default_time_series_names(t, FixedOutput)\n combo_table = DataFrame(\n \"Parameter\" => map(x -> \"[`$x`](@ref)\", collect(keys(combos))),\n \"Default Time Series Name\" => map(x -> \"`$x`\", collect(values(combos))),\n )\n insertcols!(combo_table, 1, \"Device Type\" => fill(string(t), length(combos)))\n push!(combo_tables, combo_table)\nend\nmdtable(vcat(combo_tables...), latex = false)","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"Objective:","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"No objective terms are created for DeviceModel(<:DeviceType, FixedOutput)","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"Expressions:","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"Adds the active and reactive parameters listed for specific device types above to the respective active and reactive power balance expressions created by the selected Network Formulations","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"Constraints:","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"No constraints are created for DeviceModel(<:DeviceType, FixedOutput)","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"","category":"page"},{"location":"formulation_library/General/#VariableCost-Options","page":"General","title":"VariableCost Options","text":"","category":"section"},{"location":"formulation_library/General/","page":"General","title":"General","text":"PowerSimulations can represent variable costs using a variety of different methods depending on the data available in each device. The following describes the objective function terms that are populated for each variable cost option.","category":"page"},{"location":"formulation_library/General/#Scalar-VariableCost","page":"General","title":"Scalar VariableCost","text":"","category":"section"},{"location":"formulation_library/General/","page":"General","title":"General","text":"variable_cost <: Float64: creates a fixed marginal cost term in the objective function","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"beginaligned\n textmin sum_t C * G_t\nendaligned","category":"page"},{"location":"formulation_library/General/#Polynomial-VariableCost","page":"General","title":"Polynomial VariableCost","text":"","category":"section"},{"location":"formulation_library/General/","page":"General","title":"General","text":"variable_cost <: Tuple{Float64, Float64}: creates a polynomial cost term in the objective function where","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"C_g=variable_cost[1]\nC_g^prime=variable_cost[2]","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"beginaligned\n textmin sum_t C * G_t + C^prime * G_t^2\nendaligned","category":"page"},{"location":"formulation_library/General/#Piecewise-Linear-VariableCost","page":"General","title":"Piecewise Linear VariableCost","text":"","category":"section"},{"location":"formulation_library/General/","page":"General","title":"General","text":"variable_cost <: Vector{Tuple{Float64, Float64}}: creates a piecewise linear cost term in the objective function","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"TODO: add formulation","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"___","category":"page"},{"location":"formulation_library/General/#StorageManagementCost","page":"General","title":"StorageManagementCost","text":"","category":"section"},{"location":"formulation_library/General/","page":"General","title":"General","text":"Adds an objective function cost term according to:","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"beginaligned\n textmin sum_t quad E^surplus_t * C^penalty - E^shortage_t * C^value\nendaligned","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"Impact of different cost configurations:","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"The following table describes all possible configuration of the StorageManagementCost with the target constraint in hydro or storage device models. Cases 1(a) & 2(a) will have no impact of the models operations and the target constraint will be rendered useless. In most cases that have no energy target and a non-zero value for C^value, if this cost is too high (C^value 0) or too low (C^value 0) can result in either the model holding on to stored energy till the end or the model not storing any energy in the device. This is caused by the fact that when energy target is zero, we have E_t = - E^shortage_t, and - E^shortage_t * C^value in the objective function is replaced by E_t * C^value, thus resulting in C^value to be seen as the cost of stored energy.","category":"page"},{"location":"formulation_library/General/","page":"General","title":"General","text":"Case Energy Target Energy Shortage Cost Energy Value / Energy Surplus cost Effect\nCase 1(a) hatE=0 C^penalty=0 C^value=0 no change\nCase 1(b) hatE=0 C^penalty=0 C^value0 penalty for storing energy\nCase 1(c) hatE=0 C^penalty0 C^value=0 no penalties or incentives applied\nCase 1(d) hatE=0 C^penalty=0 C^value0 incentive for storing energy\nCase 1(e) hatE=0 C^penalty0 C^value0 penalty for storing energy\nCase 1(f) hatE=0 C^penalty0 C^value0 incentive for storing energy\nCase 2(a) hatE0 C^penalty=0 C^value=0 no change\nCase 2(b) hatE0 C^penalty=0 C^value0 penalty on energy storage in excess of target\nCase 2(c) hatE0 C^penalty0 C^value=0 penalty on energy storage short of target\nCase 2(d) hatE0 C^penalty=0 C^value0 incentive on excess energy\nCase 2(e) hatE0 C^penalty0 C^value0 penalty on both excess/shortage of energy\nCase 2(f) hatE0 C^penalty0 C^value0 penalty for shortage, incentive for excess energy","category":"page"},{"location":"modeler_guide/logging/#Logging","page":"Logging","title":"Logging","text":"","category":"section"},{"location":"modeler_guide/logging/","page":"Logging","title":"Logging","text":"PowerSimulations.jl will output many log messages when building systems and running simulations. You may want to customize what gets logged to the console and, optionally, a file.","category":"page"},{"location":"modeler_guide/logging/","page":"Logging","title":"Logging","text":"By default all log messages of level Logging.Info or higher will get displayed to the console. When you run a simulation a simulation-specific logger will take over and log its messages to a file in the logs directory in the simulation output directory. When finished it will relinquish control back to the global logger.","category":"page"},{"location":"modeler_guide/logging/#Configuring-the-global-logger","page":"Logging","title":"Configuring the global logger","text":"","category":"section"},{"location":"modeler_guide/logging/","page":"Logging","title":"Logging","text":"To configure the global logger in a Jupyter Notebook or REPL you may configure your own logger with the Julia Logging standard library or use the convenience function provided by PowerSimulations. This example will log messages of level Logging.Error to console and Logging.Info and higher to the file power-simulations.log in the current directory.","category":"page"},{"location":"modeler_guide/logging/","page":"Logging","title":"Logging","text":"import Logging\nusing PowerSimulations\nlogger = configure_logging(\n console_level = Logging.Error,\n file_level = Logging.Info,\n filename = \"power-simulations.log\"\n)","category":"page"},{"location":"modeler_guide/logging/#Configuring-the-simulation-logger","page":"Logging","title":"Configuring the simulation logger","text":"","category":"section"},{"location":"modeler_guide/logging/","page":"Logging","title":"Logging","text":"You can configure the logging level used by the simulation logger when you call build!(simulation). Here is an example that increases logging verbosity:","category":"page"},{"location":"modeler_guide/logging/","page":"Logging","title":"Logging","text":"import Logging\nusing PowerSimulations\nsimulation = Simulation(...)\nbuild!(simulation, console_level = Logging.Info, file_level = Logging.Debug)","category":"page"},{"location":"modeler_guide/logging/","page":"Logging","title":"Logging","text":"The log file will be located at ///logs/simulation.log.","category":"page"},{"location":"modeler_guide/logging/#Solver-logs","page":"Logging","title":"Solver logs","text":"","category":"section"},{"location":"modeler_guide/logging/","page":"Logging","title":"Logging","text":"You can configure logging for the solver you use. Refer to the solver documentation. PowerSimulations does not redirect or intercept prints to stdout or stderr from other libraries.","category":"page"},{"location":"modeler_guide/logging/#Recorder-events","page":"Logging","title":"Recorder events","text":"","category":"section"},{"location":"modeler_guide/logging/","page":"Logging","title":"Logging","text":"PowerSimulations uses the InfrastructureSystems.Recorder to store simulation events in a log file. Refer to this link for more information.","category":"page"},{"location":"formulation_library/RenewableGen/#PowerSystems.RenewableGen-Formulations","page":"Renewable Generation","title":"PowerSystems.RenewableGen Formulations","text":"","category":"section"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Valid DeviceModels for subtypes of RenewableGen include the following:","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"using PowerSimulations\nusing PowerSystems\nusing DataFrames\nusing Latexify\ncombos = PowerSimulations.generate_device_formulation_combinations()\nfilter!(x -> x[\"device_type\"] <: RenewableGen, combos)\ncombo_table = DataFrame(\n \"Valid DeviceModel\" => [\"`DeviceModel($(c[\"device_type\"]), $(c[\"formulation\"]))`\" for c in combos],\n \"Device Type\" => [\"[$(c[\"device_type\"])](https://nrel-Sienna.github.io/PowerSystems.jl/stable/model_library/generated_$(c[\"device_type\"])/)\" for c in combos],\n \"Formulation\" => [\"[$(c[\"formulation\"])](@ref)\" for c in combos],\n )\nmdtable(combo_table, latex = false)","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"","category":"page"},{"location":"formulation_library/RenewableGen/#RenewableFullDispatch","page":"Renewable Generation","title":"RenewableFullDispatch","text":"","category":"section"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"RenewableFullDispatch","category":"page"},{"location":"formulation_library/RenewableGen/#PowerSimulations.RenewableFullDispatch","page":"Renewable Generation","title":"PowerSimulations.RenewableFullDispatch","text":"Formulation type to add injection variables constrained by a maximum injection time series for RenewableGen\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Variables:","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"ActivePowerVariable:\nBounds: [0.0, ]\nDefault initial value: PowerSystems.get_active_power(device)\nReactivePowerVariable:\nBounds: [0.0, ]\nDefault initial value: PowerSystems.get_reactive_power(device)","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Static Parameters:","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Pg^textmin = PowerSystems.get_active_power_limits(device).min\nQg^textmin = PowerSystems.get_reactive_power_limits(device).min\nQg^textmax = PowerSystems.get_reactive_power_limits(device).max","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Time Series Parameters:","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"using PowerSimulations\nusing PowerSystems\nusing DataFrames\nusing Latexify\ncombos = PowerSimulations.get_default_time_series_names(RenewableGen, RenewableFullDispatch)\ncombo_table = DataFrame(\n \"Parameter\" => map(x -> \"[`$x`](@ref)\", collect(keys(combos))),\n \"Default Time Series Name\" => map(x -> \"`$x`\", collect(values(combos))),\n )\nmdtable(combo_table, latex = false)","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Objective:","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Creates an objective function term based on the VariableCost Options where the quantity term is defined as - Pg_t to incentivize generation from RenewableGen devices.","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Expressions:","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Adds Pg and Qg terms to the respective active and reactive power balance expressions created by the selected Network Formulations","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Constraints:","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"beginaligned\n Pg^textmin le Pg_t le ActivePowerTimeSeriesParameter_t \n Qg^textmin le Qg_t le Qg^textmax\nendaligned","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"","category":"page"},{"location":"formulation_library/RenewableGen/#RenewableConstantPowerFactor","page":"Renewable Generation","title":"RenewableConstantPowerFactor","text":"","category":"section"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"RenewableConstantPowerFactor","category":"page"},{"location":"formulation_library/RenewableGen/#PowerSimulations.RenewableConstantPowerFactor","page":"Renewable Generation","title":"PowerSimulations.RenewableConstantPowerFactor","text":"Formulation type to add real and reactive injection variables with constant power factor with maximum real power injections constrained by a time series for RenewableGen\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Variables:","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"ActivePowerVariable:\nBounds: [0.0, ]\nDefault initial value: PowerSystems.get_active_power(device)\nReactivePowerVariable:\nBounds: [0.0, ]\nDefault initial value: PowerSystems.get_reactive_power(device)","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Static Parameters:","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Pg^textmin = PowerSystems.get_active_power_limits(device).min\nQg^textmin = PowerSystems.get_reactive_power_limits(device).min\nQg^textmax = PowerSystems.get_reactive_power_limits(device).max\npf = PowerSystems.get_power_factor(device)","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Time Series Parameters:","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"using PowerSimulations\nusing PowerSystems\nusing DataFrames\nusing Latexify\ncombos = PowerSimulations.get_default_time_series_names(RenewableGen, RenewableConstantPowerFactor)\ncombo_table = DataFrame(\n \"Parameter\" => map(x -> \"[`$x`](@ref)\", collect(keys(combos))),\n \"Default Time Series Name\" => map(x -> \"`$x`\", collect(values(combos))),\n )\nmdtable(combo_table, latex = false)","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Objective:","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Creates an objective function term based on the VariableCost Options where the quantity term is defined as - Pg_t to incentivize generation from RenewableGen devices.","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Expressions:","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Adds Pg and Qg terms to the respective active and reactive power balance expressions created by the selected Network Formulations","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"Constraints:","category":"page"},{"location":"formulation_library/RenewableGen/","page":"Renewable Generation","title":"Renewable Generation","text":"beginaligned\n Pg^textmin le Pg_t le ActivePowerTimeSeriesParameter_t \n Qg^textmin le Qg_t le Qg^textmax \n Qg_t = pf * Pg_t\nendaligned","category":"page"},{"location":"formulation_library/Service/#PowerSystems.Service-Formulations","page":"PowerSystems.Service Formulations","title":"PowerSystems.Service Formulations","text":"","category":"section"},{"location":"formulation_library/Service/","page":"PowerSystems.Service Formulations","title":"PowerSystems.Service Formulations","text":"TODO","category":"page"},{"location":"model_developer_guide/structure_of_operation_problem/#Structure-of-an-operations-problem-model","page":"Operation Problem Structure","title":"Structure of an operations problem model","text":"","category":"section"},{"location":"model_developer_guide/structure_of_operation_problem/","page":"Operation Problem Structure","title":"Operation Problem Structure","text":"In most cases operation problem models are optimization models. Although in PowerSimulations.jl it is possible to define arbitrary problems that can reflect heuristic decision rules, this is not the common case. This page focuses on explaining the structure of operations problems that employ an optimization problem and solver.","category":"page"},{"location":"model_developer_guide/structure_of_operation_problem/","page":"Operation Problem Structure","title":"Operation Problem Structure","text":"The first aspect to consider when thinking about developing a model compatible with PowerSimulations.jl is that although we support all of JuMP.jl objects, you need to employ anonymous constraints and variables in JuMP and register the constraints, variables and other optimization objects into PowerSimulations.jl's optimization container. Otherwise the features to use your problem in the simulation like the coordination with other problems and post processing won't work.","category":"page"},{"location":"model_developer_guide/structure_of_operation_problem/","page":"Operation Problem Structure","title":"Operation Problem Structure","text":"info: Info\nThe requirements for the simulation of Power Systems operations are more strict than solving an optimization problem once with just JuMP.jl. The requirements imposed by PowerSimulations.jl to integrate your models in a simulation are designed to help with other complex operations that go beyond JuMP.jl scope.","category":"page"},{"location":"model_developer_guide/structure_of_operation_problem/","page":"Operation Problem Structure","title":"Operation Problem Structure","text":"warning: Warning\nAll the code in this page is considered \"pseudo-code\". Copy-paste will likely not work out of the box. You need to develop the internals of the functions correctly for the examples below to work.","category":"page"},{"location":"model_developer_guide/structure_of_operation_problem/#Registering-a-variable-in-the-model","page":"Operation Problem Structure","title":"Registering a variable in the model","text":"","category":"section"},{"location":"model_developer_guide/structure_of_operation_problem/","page":"Operation Problem Structure","title":"Operation Problem Structure","text":"To register a variable in the model, the developer must first allocate the container into the optimization container and then populate it. For example, it require start the build function as follows:","category":"page"},{"location":"model_developer_guide/structure_of_operation_problem/","page":"Operation Problem Structure","title":"Operation Problem Structure","text":"info: Info\nWe recommend calling import PowerSimulations and defining the constant CONST PSI = PowerSimulations to make it easier to read the code and determine which package is responsible for defining the functions.","category":"page"},{"location":"model_developer_guide/structure_of_operation_problem/","page":"Operation Problem Structure","title":"Operation Problem Structure","text":" function PSI.build_model!(model::PSI.DecisionModel{MyCustomModel})\n container = PSI.get_optimization_container(model)\n PSI.set_time_steps!(container, 1:24)\n\n # Create the container for the variable\n variable = PSI.add_variable_container!(\n container,\n PSI.ActivePowerVariable(), # <- This variable is defined in PowerSimulations but the user can define their own\n PSY.ThermalGeneration, # <- Device type for the variable. Can be from PSY or custom defined\n devices_names, # <- First container dimension\n time_steps, # <- Second container dimension\n )\n\n # Iterate over the devices and time to store the JuMP variables into the container.\n for t in time_steps, d in devices\n name = PSY.get_name(d)\n variable[name, t] = JuMP.@variable(get_jump_model(container))\n # It is possible to use PSY getter functions to retrieve data from the generators\n # Any other variable property can be specified inside this loop.\n JuMP.set_upper_bound(variable[name, t], UB_DATA) # <- Optional\n JuMP.set_lower_bound(variable[name, t], LB_DATA) # <- Optional\n end\n\n return\n end","category":"page"},{"location":"model_developer_guide/troubleshooting/#Troubleshooting-model-development","page":"Troubleshooting","title":"Troubleshooting model development","text":"","category":"section"},{"location":"formulation_library/README/#Formulation-documentation-guide","page":"Formulation documentation guide","title":"Formulation documentation guide","text":"","category":"section"},{"location":"formulation_library/README/","page":"Formulation documentation guide","title":"Formulation documentation guide","text":"Formulation documentation should roughly follow the template established by RenewableGen.md","category":"page"},{"location":"formulation_library/README/#Auto-generated-items","page":"Formulation documentation guide","title":"Auto generated items","text":"","category":"section"},{"location":"formulation_library/README/","page":"Formulation documentation guide","title":"Formulation documentation guide","text":"Valid DeviceModel table: just change the device category in the filter function\nTime Series Parameters: just change the device category and formulation in the get_default_time_series_names method call","category":"page"},{"location":"formulation_library/README/#Linked-items","page":"Formulation documentation guide","title":"Linked items","text":"","category":"section"},{"location":"formulation_library/README/","page":"Formulation documentation guide","title":"Formulation documentation guide","text":"Formulations in the Valid DeviceModel table must have a docstring in src/core/formulations.jl\nThe Formulation in the @docs block must have a docstring in src/core/formulations.jl\nThe Variables must have docstrings in src/core/variables.jl \nThe Time Series Parameters must have docstrings in src/core/parameters.jl","category":"page"},{"location":"tutorials/pcm_simulation/#pcm_tutorial","page":"Multi-stage Production Cost Simulation","title":"Sequential Simulations with PowerSimulations.jl","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"Originally Contributed by: Clayton Barrows","category":"page"},{"location":"tutorials/pcm_simulation/#Introduction","page":"Multi-stage Production Cost Simulation","title":"Introduction","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"PowerSimulations.jl supports simulations that consist of sequential optimization problems where results from previous problems inform subsequent problems in a variety of ways. This example demonstrates some of these capabilities to represent electricity market clearing. This example is intended to be an extension of the OperationsProblem tutorial.","category":"page"},{"location":"tutorials/pcm_simulation/#Load-Packages","page":"Multi-stage Production Cost Simulation","title":"Load Packages","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"using PowerSystems\nusing PowerSimulations\nconst PSI = PowerSimulations\nusing PowerSystemCaseBuilder\nusing Dates\nusing HiGHS #solver","category":"page"},{"location":"tutorials/pcm_simulation/#Optimizer","page":"Multi-stage Production Cost Simulation","title":"Optimizer","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"It's most convenient to define an optimizer instance upfront and pass it into the DecisionModel constructor. For this example, we can use the free HiGHS solver with a relatively relaxed MIP gap (ratioGap) setting to improve speed.","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"solver = optimizer_with_attributes(HiGHS.Optimizer, \"mip_rel_gap\" => 0.5)","category":"page"},{"location":"tutorials/pcm_simulation/#Hourly-day-ahead-system","page":"Multi-stage Production Cost Simulation","title":"Hourly day-ahead system","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"First, we'll create a System with hourly data to represent day-ahead forecasted wind, solar, and load profiles:","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"sys_DA = build_system(PSISystems, \"modified_RTS_GMLC_DA_sys\")","category":"page"},{"location":"tutorials/pcm_simulation/#Minute-system","page":"Multi-stage Production Cost Simulation","title":"5-Minute system","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"The RTS data also includes 5-minute resolution time series data. So, we can create another System to represent 15 minute ahead forecasted data for a \"real-time\" market:","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"sys_RT = build_system(PSISystems, \"modified_RTS_GMLC_RT_sys\")","category":"page"},{"location":"tutorials/pcm_simulation/#ProblemTemplates-define-stages","page":"Multi-stage Production Cost Simulation","title":"ProblemTemplates define stages","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"Sequential simulations in PowerSimulations are created by defining OperationsProblems that represent stages, and how information flows between executions of a stage and between different stages.","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"Let's start by defining a two stage simulation that might look like a typical day-Ahead and real-time electricity market clearing process.","category":"page"},{"location":"tutorials/pcm_simulation/#Day-ahead-unit-commitment-stage","page":"Multi-stage Production Cost Simulation","title":"Day-ahead unit commitment stage","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"First, we can define a unit commitment template for the day ahead problem. We can use the included UC template, but in this example, we'll replace the ThermalBasicUnitCommitment with the slightly more complex ThermalStandardUnitCommitment for the thermal generators.","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"template_uc = template_unit_commitment()\nset_device_model!(template_uc, ThermalStandard, ThermalStandardUnitCommitment)","category":"page"},{"location":"tutorials/pcm_simulation/#Define-the-reference-model-for-the-real-time-economic-dispatch","page":"Multi-stage Production Cost Simulation","title":"Define the reference model for the real-time economic dispatch","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"In addition to the manual specification process demonstrated in the OperationsProblem example, PSI also provides pre-specified templates for some standard problems:","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"template_ed = template_economic_dispatch(\n network = NetworkModel(StandardPTDFModel, use_slacks = true),\n)","category":"page"},{"location":"tutorials/pcm_simulation/#Define-the-SimulationModels","page":"Multi-stage Production Cost Simulation","title":"Define the SimulationModels","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"DecisionModels define the problems that are executed in the simulation. The actual problem will change as the stage gets updated to represent different time periods, but the formulations applied to the components is constant within a stage. In this case, we want to define two stages with the ProblemTemplates and the Systems that we've already created.","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"models = SimulationModels(\n decision_models = [\n DecisionModel(template_uc, sys_DA, optimizer = solver, name = \"UC\"),\n DecisionModel(template_ed, sys_RT, optimizer = solver, name = \"ED\"),\n ],\n)","category":"page"},{"location":"tutorials/pcm_simulation/#SimulationSequence","page":"Multi-stage Production Cost Simulation","title":"SimulationSequence","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"Similar to an ProblemTemplate, the SimulationSequence provides a template of how to execute a sequential set of operations problems.","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"Let's review some of the SimulationSequence arguments.","category":"page"},{"location":"tutorials/pcm_simulation/#Chronologies","page":"Multi-stage Production Cost Simulation","title":"Chronologies","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"In PowerSimulations, chronologies define where information is flowing. There are two types of chronologies.","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"inter-stage chronologies: Define how information flows between stages. e.g. day-ahead solutions are used to inform economic dispatch problems\nintra-stage chronologies: Define how information flows between multiple executions of a single stage. e.g. the dispatch setpoints of the first period of an economic dispatch problem are constrained by the ramping limits from setpoints in the final period of the previous problem.","category":"page"},{"location":"tutorials/pcm_simulation/#FeedForward","page":"Multi-stage Production Cost Simulation","title":"FeedForward","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"The definition of exactly what information is passed using the defined chronologies is accomplished with FeedForward. Specifically, FeedForward is used to define what to do with information being passed with an inter-stage chronology. Let's define a FeedForward that affects the semi-continuous range constraints of thermal generators in the economic dispatch problems based on the value of the unit-commitment variables.","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"feedforward = Dict(\n \"ED\" => [\n SemiContinuousFeedforward(\n component_type = ThermalStandard,\n source = OnVariable,\n affected_values = [ActivePowerVariable],\n ),\n ],\n)","category":"page"},{"location":"tutorials/pcm_simulation/#Sequencing","page":"Multi-stage Production Cost Simulation","title":"Sequencing","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"The stage problem length, look-ahead, and other details surrounding the temporal Sequencing of stages are controlled using the structure of the time series data in the Systems. So, to define a typical day-ahead - real-time sequence:","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"Day ahead problems should represent 48 hours, advancing 24 hours after each execution (24-hour look-ahead)\nReal time problems should represent 1 hour (12 5-minute periods), advancing 15 min after each execution (15 min look-ahead)","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"We can adjust the time series data to reflect this structure in each System:","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"transform_single_time_series!(sys_DA, 48, Hour(1))\ntransform_single_time_series!(sys_RT, 12, Minute(15))","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"Now we can put it all together to define a SimulationSequence","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"DA_RT_sequence = SimulationSequence(\n models = models,\n ini_cond_chronology = InterProblemChronology(),\n feedforwards = feedforward,\n)","category":"page"},{"location":"tutorials/pcm_simulation/#Simulation","page":"Multi-stage Production Cost Simulation","title":"Simulation","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"Now, we can build and execute a simulation using the SimulationSequence and Stages that we've defined.","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"sim = Simulation(\n name = \"rts-test\",\n steps = 2,\n models = models,\n sequence = DA_RT_sequence,\n simulation_folder = mktempdir(\".\", cleanup = true),\n)","category":"page"},{"location":"tutorials/pcm_simulation/#Build-simulation","page":"Multi-stage Production Cost Simulation","title":"Build simulation","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"build!(sim)","category":"page"},{"location":"tutorials/pcm_simulation/#Execute-simulation","page":"Multi-stage Production Cost Simulation","title":"Execute simulation","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"the following command returns the status of the simulation (0: is proper execution) and stores the results in a set of HDF5 files on disk.","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"execute!(sim, enable_progress_bar = false)","category":"page"},{"location":"tutorials/pcm_simulation/#Results","page":"Multi-stage Production Cost Simulation","title":"Results","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"To access the results, we need to load the simulation result metadata and then make requests to the specific data of interest. This allows you to efficiently access the results of interest without overloading resources.","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"results = SimulationResults(sim);\nuc_results = get_decision_problem_results(results, \"UC\"); # UC stage result metadata\ned_results = get_decision_problem_results(results, \"ED\"); # ED stage result metadata","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"We can read all the result variables","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"read_variables(uc_results)","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"or all the parameters","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"read_parameters(uc_results)","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"We can just list the variable names contained in uc_results:","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"list_variable_names(uc_results)","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"and a number of parameters (this pattern also works for aux_variables, expressions, and duals)","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"list_parameter_names(uc_results)","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"Now we can read the specific results of interest for a specific problem, time window (optional), and set of variables, duals, or parameters (optional)","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"Dict([\n v => read_variable(uc_results, v) for v in [\n \"ActivePowerVariable__RenewableDispatch\",\n \"ActivePowerVariable__HydroDispatch\",\n \"StopVariable__ThermalStandard\",\n ]\n])","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"Or if we want the result of just one variable, parameter, or dual (must be defined in the problem definition), we can use:","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"read_parameter(\n ed_results,\n \"ActivePowerTimeSeriesParameter__RenewableFix\",\n initial_time = DateTime(\"2020-01-01T06:00:00\"),\n count = 5,\n)","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"note that this returns the results of each execution step in a separate dataframe *","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"If you want the realized results (without lookahead periods), you can call read_realized_*:","category":"page"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"read_realized_variables(\n uc_results,\n [\"ActivePowerVariable__ThermalStandard\", \"ActivePowerVariable__RenewableDispatch\"],\n)","category":"page"},{"location":"tutorials/pcm_simulation/#Plotting","page":"Multi-stage Production Cost Simulation","title":"Plotting","text":"","category":"section"},{"location":"tutorials/pcm_simulation/","page":"Multi-stage Production Cost Simulation","title":"Multi-stage Production Cost Simulation","text":"Take a look at the plotting capabilities in PowerGraphics.jl","category":"page"},{"location":"modeler_guide/running_a_simulation/#running_a_simulation","page":"Simulation","title":"Simulation","text":"","category":"section"},{"location":"modeler_guide/running_a_simulation/","page":"Simulation","title":"Simulation","text":"tip: Always try to solve the operations problem first before putting together the simulation\nIt is not uncommon that when trying to solve a complex simulation the resulting models are infeasible. This situation can be the result of many factors like the input data, the incorrect specification of the initial conditions for models with time dependencies or a poorly specified model. Therefore, it's highly recommended to run and analyze an Operations Problems that reflect the problems that will be included in a simulation prior to executing a simulation.","category":"page"},{"location":"modeler_guide/running_a_simulation/","page":"Simulation","title":"Simulation","text":"Check out the Operations Problem Tutorial","category":"page"},{"location":"modeler_guide/running_a_simulation/#Feedforward","page":"Simulation","title":"Feedforward","text":"","category":"section"},{"location":"modeler_guide/running_a_simulation/","page":"Simulation","title":"Simulation","text":"TODO","category":"page"},{"location":"modeler_guide/running_a_simulation/#Sequencing","page":"Simulation","title":"Sequencing","text":"","category":"section"},{"location":"modeler_guide/running_a_simulation/","page":"Simulation","title":"Simulation","text":"In a typical simulation pipeline, we want to connect daily (24-hours) day-ahead unit commitment problems, with multiple economic dispatch problems. Usually, our day-ahead unit commitment problem will have an hourly (1-hour) resolution, while the economic dispatch will have a 5-minute resolution.","category":"page"},{"location":"modeler_guide/running_a_simulation/","page":"Simulation","title":"Simulation","text":"Depending on your problem, it is common to use a 2-day look-ahead for unit commitment problems, so in this case, the Day-Ahead problem will have: resolution = Hour(1) with interval = Hour(24) and horizon = 48. In the case of the economic dispatch problem, it is common to use a look-ahead of two hours. Thus, the Real-Time problem will have: resolution = Minute(5), with interval = Minute(5) (we only store the first operating point) and horizon = 24 (24 time steps of 5 minutes are 120 minutes, that is 2 hours).","category":"page"},{"location":"tutorials/adding_new_device_formulation/#Adding-Device-Formulations","page":"Adding Device Formulations","title":"Adding Device Formulations","text":"","category":"section"},{"location":"formulation_library/Network/#network_formulations","page":"Network","title":"Network Formulations","text":"","category":"section"},{"location":"formulation_library/Network/","page":"Network","title":"Network","text":"TODO","category":"page"},{"location":"formulation_library/Load/#PowerSystems.ElectricLoad-Formulations","page":"Load","title":"PowerSystems.ElectricLoad Formulations","text":"","category":"section"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Valid DeviceModels for subtypes of ElectricLoad include the following:","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"using PowerSimulations\nusing PowerSystems\nusing DataFrames\nusing Latexify\ncombos = PowerSimulations.generate_device_formulation_combinations()\nfilter!(x -> x[\"device_type\"] <: ElectricLoad, combos)\ncombo_table = DataFrame(\n \"Valid DeviceModel\" => [\"`DeviceModel($(c[\"device_type\"]), $(c[\"formulation\"]))`\" for c in combos],\n \"Device Type\" => [\"[$(c[\"device_type\"])](https://nrel-Sienna.github.io/PowerSystems.jl/stable/model_library/generated_$(c[\"device_type\"])/)\" for c in combos],\n \"Formulation\" => [\"[$(c[\"formulation\"])](@ref)\" for c in combos],\n )\nmdtable(combo_table, latex = false)","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"","category":"page"},{"location":"formulation_library/Load/#StaticPowerLoad","page":"Load","title":"StaticPowerLoad","text":"","category":"section"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"StaticPowerLoad","category":"page"},{"location":"formulation_library/Load/#PowerSimulations.StaticPowerLoad","page":"Load","title":"PowerSimulations.StaticPowerLoad","text":"Formulation type to add a time series parameter for non-dispatchable ElectricLoad withdrawls to power balance constraints\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Variables:","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"No variables are created","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Time Series Parameters:","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"using PowerSimulations\nusing PowerSystems\nusing DataFrames\nusing Latexify\ncombos = PowerSimulations.get_default_time_series_names(ElectricLoad, StaticPowerLoad)\ncombo_table = DataFrame(\n \"Parameter\" => map(x -> \"[`$x`](@ref)\", collect(keys(combos))),\n \"Default Time Series Name\" => map(x -> \"`$x`\", collect(values(combos))),\n )\nmdtable(combo_table, latex = false)","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Expressions:","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Subtracts the parameters listed above from the respective active and reactive power balance expressions created by the selected Network Formulations","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Constraints:","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"No constraints are created","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"","category":"page"},{"location":"formulation_library/Load/#PowerLoadInterruption","page":"Load","title":"PowerLoadInterruption","text":"","category":"section"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"PowerLoadInterruption","category":"page"},{"location":"formulation_library/Load/#PowerSimulations.PowerLoadInterruption","page":"Load","title":"PowerSimulations.PowerLoadInterruption","text":"Formulation type to enable (binary) load interruptions\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Variables:","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"ActivePowerVariable:\nBounds: [0.0, ]\nDefault initial value: 0.0\nReactivePowerVariable:\nBounds: [0.0, ]\nDefault initial value: 0.0\nOnVariable:\nBounds: {0,1}\nDefault initial value: 1","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Time Series Parameters:","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"using PowerSimulations\nusing PowerSystems\nusing DataFrames\nusing Latexify\ncombos = PowerSimulations.get_default_time_series_names(ElectricLoad, PowerLoadInterruption)\ncombo_table = DataFrame(\n \"Parameter\" => map(x -> \"[`$x`](@ref)\", collect(keys(combos))),\n \"Default Time Series Name\" => map(x -> \"`$x`\", collect(values(combos))),\n )\nmdtable(combo_table, latex = false)","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Objective:","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Creates an objective function term based on the VariableCost Options where the quantity term is defined as Pg.","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Expressions:","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Adds Pg and Qg terms and to the respective active and reactive power balance expressions created by the selected Network Formulations\nSubtracts the time series parameters listed above terms from the respective active and reactive power balance expressions created by the selected Network Formulations","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Constraints:","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Pg and Qg represent the \"unserved\" active and reactive power loads","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"beginaligned\n Pg_t le ActivePowerTimeSeriesParameter_t\n Pg_t - u_t ActivePowerTimeSeriesParameter_t le 0 \n Qg_t le ReactivePowerTimeSeriesParameter_t\n Qg_t - u_t ReactivePowerTimeSeriesParameter_tle 0\nendaligned","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"","category":"page"},{"location":"formulation_library/Load/#PowerLoadDispatch","page":"Load","title":"PowerLoadDispatch","text":"","category":"section"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"PowerLoadDispatch","category":"page"},{"location":"formulation_library/Load/#PowerSimulations.PowerLoadDispatch","page":"Load","title":"PowerSimulations.PowerLoadDispatch","text":"Formulation type to enable (continuous) load interruption dispatch\n\n\n\n\n\n","category":"type"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Variables:","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"ActivePowerVariable:\nBounds: [0.0, ]\nDefault initial value: PowerSystems.get_active_power(device)\nReactivePowerVariable:\nBounds: [0.0, ]\nDefault initial value: PowerSystems.get_reactive_power(device)","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Time Series Parameters:","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"using PowerSimulations\nusing PowerSystems\nusing DataFrames\nusing Latexify\ncombos = PowerSimulations.get_default_time_series_names(ElectricLoad, PowerLoadDispatch)\ncombo_table = DataFrame(\n \"Parameter\" => map(x -> \"[`$x`](@ref)\", collect(keys(combos))),\n \"Default Time Series Name\" => map(x -> \"`$x`\", collect(values(combos))),\n )\nmdtable(combo_table, latex = false)","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Objective:","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Creates an objective function term based on the VariableCost Options where the quantity term is defined as Pg.","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Expressions:","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Adds Pg and Qg terms and to the respective active and reactive power balance expressions created by the selected Network Formulations\nSubtracts the time series parameters listed above terms from the respective active and reactive power balance expressions created by the selected Network Formulations","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Constraints:","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"Pg and Qg represent the \"unserved\" active and reactive power loads","category":"page"},{"location":"formulation_library/Load/","page":"Load","title":"Load","text":"beginaligned\n Pg_t le ActivePowerTimeSeriesParameter_t\n Qg_t le ReactivePowerTimeSeriesParameter_t\nendaligned","category":"page"},{"location":"#PowerSimulations.jl","page":"Welcome Page","title":"PowerSimulations.jl","text":"","category":"section"},{"location":"","page":"Welcome Page","title":"Welcome Page","text":"CurrentModule = PowerSimulations","category":"page"},{"location":"#Overview","page":"Welcome Page","title":"Overview","text":"","category":"section"},{"location":"","page":"Welcome Page","title":"Welcome Page","text":"PowerSimulations.jl is a power system operations simulation tool developed as a flexible and open source software for quasi-static power systems simulations including Production Cost Models. PowerSimulations.jl tackles the issues of developing a simulation model in a modular way providing tools for the formulation of decision models and emulation models that can be solved independently or in an interconnected fashion.","category":"page"},{"location":"","page":"Welcome Page","title":"Welcome Page","text":"PowerSimulations.jl supports the workflows to develop simulations by separating the development of operations models and simulation models.","category":"page"},{"location":"","page":"Welcome Page","title":"Welcome Page","text":"Operation Models: Optimization model used to find the solution of an operation problem.\nSimulations Models: Defined the requirements to find solutions to a sequence of operation problems in a way that resembles the procedures followed by operators.","category":"page"},{"location":"","page":"Welcome Page","title":"Welcome Page","text":"The most common Simulation Model is the solution of a Unit Commitment and Economic Dispatch sequence of problems. This model is used in commercial Production Cost Modeling tools, but it has a limited scope of analysis.","category":"page"},{"location":"#How-the-documentation-is-structured","page":"Welcome Page","title":"How the documentation is structured","text":"","category":"section"},{"location":"","page":"Welcome Page","title":"Welcome Page","text":"PowerSimulations.jl documentation and code are organized according to the needs of different users depending on their skillset and requirements. In broad terms there are three categories:","category":"page"},{"location":"","page":"Welcome Page","title":"Welcome Page","text":"Modeler: Users that want to solve an operations problem or run a simulation using the existing models in PowerSimulations.jl. For instance, answer questions about the change in operation costs in future fuel mixes. Check the formulations library page to choose a modeling strategy that fits your needs.\nModel Developer: Users that want to develop custom models and workflows for the simulation of a power system operation. For instance, study the impacts of an stochastic optimization problem over a deterministic.\nCode Base Developers: Users that want to add new core functionalities or fix bugs in the core capabilities of PowerSimulations.jl.","category":"page"},{"location":"","page":"Welcome Page","title":"Welcome Page","text":"PowerSimulations.jl is an active project under development, and we welcome your feedback, suggestions, and bug reports.","category":"page"},{"location":"","page":"Welcome Page","title":"Welcome Page","text":"Note: PowerSimulations.jl uses the data model implemented in PowerSystems.jl to construct optimization models. In most cases, you need to add PowerSystems.jl to your scripts.","category":"page"},{"location":"#Installation","page":"Welcome Page","title":"Installation","text":"","category":"section"},{"location":"","page":"Welcome Page","title":"Welcome Page","text":"The latest stable release of PowerSimulations can be installed using the Julia package manager with","category":"page"},{"location":"","page":"Welcome Page","title":"Welcome Page","text":"] add PowerSimulations","category":"page"},{"location":"","page":"Welcome Page","title":"Welcome Page","text":"For the current development version, \"checkout\" this package with","category":"page"},{"location":"","page":"Welcome Page","title":"Welcome Page","text":"] add PowerSimulations#main","category":"page"},{"location":"","page":"Welcome Page","title":"Welcome Page","text":"An appropriate optimization solver is required for running PowerSimulations models. Refer to JuMP.jl solver's page to select the most appropriate for the application of interest.","category":"page"},{"location":"","page":"Welcome Page","title":"Welcome Page","text":"","category":"page"},{"location":"","page":"Welcome Page","title":"Welcome Page","text":"PowerSystems has been developed as part of the Scalable Integrated Infrastructure Planning (SIIP) initiative at the U.S. Department of Energy's National Renewable Energy Laboratory (NREL).","category":"page"}] +} diff --git a/v0.24.1/siteinfo.js b/v0.24.1/siteinfo.js new file mode 100644 index 0000000000..ba2f072bc5 --- /dev/null +++ b/v0.24.1/siteinfo.js @@ -0,0 +1 @@ +var DOCUMENTER_CURRENT_VERSION = "v0.24.1"; diff --git a/v0.24.1/tutorials/adding_new_device_formulation/index.html b/v0.24.1/tutorials/adding_new_device_formulation/index.html new file mode 100644 index 0000000000..fab5051717 --- /dev/null +++ b/v0.24.1/tutorials/adding_new_device_formulation/index.html @@ -0,0 +1,2 @@ + +Adding Device Formulations · PowerSimulations.jl diff --git a/v0.24.1/tutorials/adding_new_problem_model/index.html b/v0.24.1/tutorials/adding_new_problem_model/index.html new file mode 100644 index 0000000000..34a4db66ec --- /dev/null +++ b/v0.24.1/tutorials/adding_new_problem_model/index.html @@ -0,0 +1,76 @@ + +Adding an Operations Problem Model · PowerSimulations.jl
    Edit on GitHub

    Adding an Operations Problem Model

    This tutorial will show how to create a custom decision problem model. These cases are the ones where the user want to solve a fully specified problem. Some examples of custom decision models include:

    • Solving a custom Security Constrained Unit Commitment Problem
    • Solving a market agent utility maximization Problem. See examples of this functionality in HybridSystemsSimulations.jl

    The tutorial follows the usual steps for operational model building. First, build the decision model in isolation and second, integrate it into a simulation. In most cases there will be more than one way of achieving the same objective when it comes to implementing the model. This guide shows a general set of steps and requirements but it is by no means an exhaustive and detailed guide on developing custom decision models.

    Warning

    All the code in this tutorial is considered "pseudo-code". Copy-paste will likely not work out of the box. You need to develop the internals of the functions correctly for the examples below to work.

    General Rules

    1. As a general rule you need to understand Julia's terminology such as multiple dispatch, parametric structs and method overloading, among others. Developing custom models for an operational simulation is a highly technical task and requires skilled development. This tutorial also requires good understanding of PowerSystems.jl data structures and features which are covered in the tutorials section of PowerSystems.jl documentation.

    Finally, developing a custom model decision model that will employ an optimization model under the hood requires understanding JuMP.jl.

    1. Need to employ anonymous constraints and variables in JuMP

    and register the constraints, variables and other optimization objects into PowerSimulations.jl's optimization container. Otherwise the features to use your problem in the simulation like the coordination with other problems and post processing won't work. More on this in the section How to develop your build_model! function below.

    1. Implement the required methods for your custom decision models. In some cases it will be possible to re-use some of the other methods that exist in PowerSimulations to make life easier for variable addition and constraint creation but this is not required.

    Decision Problem

    Step 1: Define a Custom Decision Problem

    Define a decision problem struct as a subtype of PowerSimulations.DecisionProblem. This requirement will enable a lot of the underlying functionality that relies on multiple dispatch. DecisionProblems are used to parameterize the behavior of DecisionModel objects which are just containers for the parameters, references and the optimization problem.

    It is possible to define a Custom Decision Problem that gives the user full control over the build, solve and execution process since it imposes less requirements on the developer. However, with less requirements there are also less checks and validations performed inside of PowerSimulations which might lead to unexpected errors

    struct MyCustomDecisionProblem <: PSI.DecisionProblem end

    Alternatively, it is possible to define a Custom Decision Problem subtyping from DefaultDecisionProblem which imposes more requirements and structure onto the developer but employs more checks and validations in the process. Be aware that this route will decrease the flexibility of what can be done inside the custom model.

    struct MyCustomDecisionProblem <: PSI.DefaultDecisionProblem end

    Once the problem type is defined, initialize the decision model container with your custom decision problem passing the solver and some of the settings you need for the solution of the problem. For custom problems some of the settings need manual implementation by the developer. Settings availability is also dependent on wether you choose to subtype from PSI.DecisionProblem or PSI.DefaultDecisionProblem

    my_model = DecisionModel{MyCustomDecisionProblem}(
+    sys;
+    name = "MyModel",
+    optimizer = optimizer_with_attributes(HiGHS.Optimizer),
+     optimizer_solve_log_print = true,
+)

    Mandatory Method Implementations

    1. build_model!: This method build the JuMP optimization model.

    Optional Method Overloads

    These methods can be defined optionally for your problem. By default for problems subtyped from DecisionProblem these checks are not executed. If the problems are subtyped from DefaultDecisionProblem these checks are always conducted with PowerSimulations defaults and require compliance with those defaults to pass. In any case, these can be overloaded when necessary depending on the problem requirements.

    1. validate_template
    2. validate_time_series
    3. reset!
    4. solve_impl!

    How to develop your build_model! function

    Registering a variable in the model

    To register a variable in the model, the developer must first allocate the container into the optimization container and then populate it. For example, it require start the build function as follows:

    Info

    We recommend calling import PowerSimulations and defining the constant CONST PSI = PowerSimulations to make it easier to read the code and determine which package is responsible for defining the functions.

        function PSI.build_model!(model::PSI.DecisionModel{MyCustomDecisionProblem})
+        container = PSI.get_optimization_container(model)
+        time_steps = 1:24
+        PSI.set_time_steps!(container, time_steps)
+        system = PSI.get_system(model)
+
+        thermal_gens = PSY.get_components(PSY.ThermalStandard, system)
+        thermal_gens_names = PSY.get_name.(thermal_gens)
+
+        # Create the container for the variable
+        variable = PSI.add_variable_container!(
+            container,
+            PSI.ActivePowerVariable(), # <- This variable is defined in PowerSimulations but the user can define their own
+            PSY.ThermalGeneration, # <- Device type for the variable. Can be from PSY or custom defined
+            thermal_gens_names, # <- First container dimension
+            time_steps, # <- Second container dimension
+        )
+
+        # Iterate over the devices and time to store the JuMP variables into the container.
+        for t in time_steps, d in thermal_gens_names
+            name = PSY.get_name(d)
+            variable[name, t] = JuMP.@variable(get_jump_model(container))
+            # It is possible to use PSY getter functions to retrieve data from the generators
+            JuMP.set_upper_bound(variable[name, t], UB_DATA) # <- Optional
+            JuMP.set_lower_bound(variable[name, t], LB_DATA) # <- Optional
+        end
+
+        # Add More Variables.....
+
+        return
+    end

    Registering a constraint in the model

    A similar pattern is used to add constraints to the model, in this example the field meta is used to avoid creating unnecessary duplicate constraint types. For instance to reflect upperbound and lowerbound or upwards and downwards constraints. Meta can take any string value except for the _ character.

        function PSI.build_model!(model::PSI.DecisionModel{MyCustomDecisionProblem})
+        container = PSI.get_optimization_container(model)
+        time_steps = 1:24
+        PSI.set_time_steps!(container, time_steps)
+        system = PSI.get_system(model)
+
+        # VARIABLE ADDITION CODE
+
+        # Constraint additions
+        con_ub = PSI.add_constraints_container!(
+            container,
+            PSI.RangeLimitConstraint(), # <- Constraint Type defined by PSI or your own
+            PSY.ThermalGeneration, # <- Device type for variable. Can be PSY or custom
+            thermal_gens_names, # <- First container dimension
+            time_steps; # <- Second container dimension
+            meta = "ub" # <- meta allows to reuse a constraint definition for similar constraints. It only requires to be a string
+            )
+
+        con_lb = PSI.add_constraints_container!(
+            container,
+            PSI.RangeLimitConstraint(),
+            PSY.ThermalGeneration,
+            thermal_gens_names, # <- First container dimension
+            time_steps; # <- Second container dimension
+            meta = "lb" # <- meta allows to reuse a constraint definition for similar constraints. It only requires to be a string
+            )
+
+        # Retrieve a relevant variable from the container if not defined in
+        variable = PSI.get_variable(container, PSI.ActivePowerVariable(), PSY.ThermalGeneration)
+        for device in devices, t in time_steps
+            ci_name = PSY.get_name(device)
+            limits = get_min_max_limits(device) # depends on constraint type and formulation type
+            con_ub[ci_name, t] =
+                JuMP.@constraint(get_jump_model(container), variable[ci_name, t] >= limits.min)
+            con_lb[ci_name, t] =
+                JuMP.@constraint(get_jump_model(container), variable[ci_name, t] >= limits.min)
+        end
+
+        return
+    end
    diff --git a/v0.24.1/tutorials/basics_of_developing_models/index.html b/v0.24.1/tutorials/basics_of_developing_models/index.html new file mode 100644 index 0000000000..ffc4dec512 --- /dev/null +++ b/v0.24.1/tutorials/basics_of_developing_models/index.html @@ -0,0 +1,2 @@ + +Basics of Developing Operation Models · PowerSimulations.jl diff --git a/v0.24.1/tutorials/decision_problem/index.html b/v0.24.1/tutorials/decision_problem/index.html new file mode 100644 index 0000000000..f169e12aef --- /dev/null +++ b/v0.24.1/tutorials/decision_problem/index.html @@ -0,0 +1,336 @@ + +Single-step Problem · PowerSimulations.jl
    Edit on GitHub

    Operations problems with PowerSimulations.jl

    Originally Contributed by: Clayton Barrows

    Introduction

    PowerSimulations.jl supports the construction and solution of optimal power system scheduling problems (Operations Problems). Operations problems form the fundamental building blocks for sequential simulations. This example shows how to specify and customize a the mathematics that will be applied to the data with an ProblemTemplate, build and execute an DecisionModel, and access the results.

    Load Packages

    using PowerSystems
+using PowerSimulations
+using PowerSystemCaseBuilder
+using HiGHS # solver

    Data

    Note

    PowerSystemCaseBuilder.jl is a helper library that makes it easier to reproduce examples in the documentation and tutorials. Normally you would pass your local files to create the system data instead of calling the function build_system. For more details visit PowerSystemCaseBuilder Documentation

    sys = build_system(PSISystems, "modified_RTS_GMLC_DA_sys")
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    System
    PropertyValue
    Name
    Description
    System Units BaseSYSTEM_BASE
    Base Power100.0
    Base Frequency60.0
    Num Components501
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Static Components
    TypeCountHas Static Time SeriesHas Forecasts
    ACBus73falsefalse
    Arc109falsefalse
    Area3truetrue
    FixedAdmittance3truetrue
    HydroDispatch1truetrue
    Line105falsefalse
    LoadZone21falsefalse
    PowerLoad51truetrue
    RenewableDispatch29truetrue
    RenewableFix31truetrue
    TapTransformer15falsefalse
    ThermalStandard54falsefalse
    TwoTerminalHVDCLine1falsefalse
    VariableReserve1truetrue
    VariableReserve4truetrue
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Time Series Summary
    PropertyValue
    Components with time series data123
    Total StaticTimeSeries124
    Total Forecasts124
    Resolution60 minutes
    First initial time2020-01-01T00:00:00
    Last initial time2020-12-30T00:00:00
    Horizon48
    Interval1440 minutes
    Forecast window count365
    +

    Define a problem specification with an ProblemTemplate

    You can create an empty template with:

    template_uc = ProblemTemplate()
    + + + + + + + + + + + + + + + + + + + +
    Network Model
    Network ModelCopperPlatePowerModel
    Slacksfalse
    PTDFfalse
    DualsNone
    + + + + + + + + + + + + +
    Device Models
    Device TypeFormulationSlacks
    +

    Now, you can add a DeviceModel for each device type to create an assignment between PowerSystems device types and the subtypes of AbstractDeviceFormulation. PowerSimulations has a variety of different AbstractDeviceFormulation subtypes that can be applied to different PowerSystems device types, each dispatching to different methods for populating optimization problem objectives, variables, and constraints. Documentation on the formulation options for various devices can be found in the formulation library docs

    Branch Formulations

    Here is an example of relatively standard branch formulations. Other formulations allow for selective enforcement of transmission limits and greater control on transformer settings.

    set_device_model!(template_uc, Line, StaticBranch)
+set_device_model!(template_uc, Transformer2W, StaticBranch)
+set_device_model!(template_uc, TapTransformer, StaticBranch)

    Injection Device Formulations

    Here we define template entries for all devices that inject or withdraw power on the network. For each device type, we can define a distinct AbstractDeviceFormulation. In this case, we're defining a basic unit commitment model for thermal generators, curtailable renewable generators, and fixed dispatch (net-load reduction) formulations for HydroDispatch and RenewableFix devices.

    set_device_model!(template_uc, ThermalStandard, ThermalStandardUnitCommitment)
+set_device_model!(template_uc, RenewableDispatch, RenewableFullDispatch)
+set_device_model!(template_uc, PowerLoad, StaticPowerLoad)
+set_device_model!(template_uc, HydroDispatch, FixedOutput)
+set_device_model!(template_uc, HydroDispatchRunOfRiver, HydroDispatchRunOfRiver)
+set_device_model!(template_uc, RenewableFix, FixedOutput)

    Service Formulations

    We have two VariableReserve types, parameterized by their direction. So, similar to creating DeviceModels, we can create ServiceModels. The primary difference being that DeviceModel objects define how constraints get created, while ServiceModel objects define how constraints get modified.

    set_service_model!(template_uc, VariableReserve{ReserveUp}, RangeReserve)
+set_service_model!(template_uc, VariableReserve{ReserveDown}, RangeReserve)

    Network Formulations

    Finally, we can define the transmission network specification that we'd like to model. For simplicity, we'll choose a copper plate formulation. But there are dozens of specifications available through an integration with PowerModels.jl. Note that many formulations will require appropriate data and may be computationally intractable

    set_network_model!(template_uc, NetworkModel(CopperPlatePowerModel))

    DecisionModel

    Now that we have a System and an ProblemTemplate, we can put the two together to create an DecisionModel that we solve.

    Optimizer

    It's most convenient to define an optimizer instance upfront and pass it into the DecisionModel constructor. For this example, we can use the free HiGHS solver with a relatively relaxed MIP gap (ratioGap) setting to improve speed.

    solver = optimizer_with_attributes(HiGHS.Optimizer, "mip_rel_gap" => 0.5)
    MathOptInterface.OptimizerWithAttributes(HiGHS.Optimizer, Pair{MathOptInterface.AbstractOptimizerAttribute, Any}[MathOptInterface.RawOptimizerAttribute("mip_rel_gap") => 0.5])

    Build an DecisionModel

    The construction of an DecisionModel essentially applies an ProblemTemplate to System data to create a JuMP model.

    problem = DecisionModel(template_uc, sys; optimizer = solver, horizon = 24)
+build!(problem, output_dir = mktempdir())
    BuildStatus.BUILT = 0
    Tip

    The principal component of the DecisionModel is the JuMP model. But you can serialize to a file using the following command:

        serialize_optimization_model(problem, save_path)

    Keep in mind that if the setting "storevariablenames" is set to False then the file won't show the model's names.

    Solve an DecisionModel

    solve!(problem)
    RunStatus.SUCCESSFUL = 0

    Results Inspection

    PowerSimulations collects the DecisionModel results into a ProblemResults struct:

    res = ProblemResults(problem)

    Start: 2020-01-01T00:00:00

    +

    End: 2020-01-01T23:00:00

    +

    Resolution: 60 minutes

    + + + + + + + + + + + +
    PowerSimulations Problem Auxiliary variables Results
    TimeDurationOff__ThermalStandard
    TimeDurationOn__ThermalStandard
    + + + + + + + + + + + +
    PowerSimulations Problem Expressions Results
    ProductionCostExpression__RenewableDispatch
    ProductionCostExpression__ThermalStandard
    + + + + + + + + + + + + + + + + + + + + + + + + + + +
    PowerSimulations Problem Parameters Results
    RequirementTimeSeriesParameter__VariableReserve__ReserveUp__Reg_Up
    RequirementTimeSeriesParameter__VariableReserve__ReserveUp__Spin_Up_R3
    ActivePowerTimeSeriesParameter__PowerLoad
    RequirementTimeSeriesParameter__VariableReserve__ReserveUp__Spin_Up_R2
    ActivePowerTimeSeriesParameter__RenewableDispatch
    RequirementTimeSeriesParameter__VariableReserve__ReserveDown__Reg_Down
    RequirementTimeSeriesParameter__VariableReserve__ReserveUp__Spin_Up_R1
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    PowerSimulations Problem Variables Results
    StartVariable__ThermalStandard
    ActivePowerReserveVariable__VariableReserve__ReserveUp__Spin_Up_R2
    ActivePowerReserveVariable__VariableReserve__ReserveDown__Reg_Down
    ActivePowerReserveVariable__VariableReserve__ReserveUp__Reg_Up
    ActivePowerVariable__RenewableDispatch
    ActivePowerReserveVariable__VariableReserve__ReserveUp__Spin_Up_R3
    ActivePowerReserveVariable__VariableReserve__ReserveUp__Spin_Up_R1
    OnVariable__ThermalStandard
    StopVariable__ThermalStandard
    ActivePowerVariable__ThermalStandard
    +

    Optimizer Stats

    The optimizer summary is included

    get_optimizer_stats(res)
    1×20 DataFrame
    Rowdetailed_statsobjective_valuetermination_statusprimal_statusdual_statussolver_solve_timeresult_counthas_valueshas_dualsobjective_bounddual_objective_valuesolve_timebarrier_iterationssimplex_iterationsnode_counttimed_solve_timetimed_calculate_aux_variablestimed_calculate_dual_variablessolve_bytes_allocsec_in_gc
    BoolFloat64Int64Int64Int64Float64Int64BoolBoolMissingMissingFloat64MissingMissingMissingFloat64Float64Float64Float64Float64
    1false2.35848e6110NaN1falsefalsemissingmissing1.00784missingmissingmissing1.196810.6290410.0007809072.33066e70.0602241

    Objective Function Value

    get_objective_value(res)
    2.358482086492074e6

    Variable, Parameter, Auxillary Variable, Dual, and Expression Values

    The solution value data frames for variables, parameters, auxillary variables, duals and expressions can be accessed using the read_ methods:

    read_variables(res)
    Dict{String, DataFrames.DataFrame} with 10 entries:
+  "ActivePowerReserveVaria… => 24×52 DataFrame…
+  "StartVariable__ThermalS… => 24×55 DataFrame…
+  "ActivePowerVariable__Th… => 24×55 DataFrame…
+  "ActivePowerReserveVaria… => 24×52 DataFrame…
+  "ActivePowerVariable__Re… => 24×30 DataFrame…
+  "ActivePowerReserveVaria… => 24×18 DataFrame…
+  "StopVariable__ThermalSt… => 24×55 DataFrame…
+  "ActivePowerReserveVaria… => 24×17 DataFrame…
+  "OnVariable__ThermalStan… => 24×55 DataFrame…
+  "ActivePowerReserveVaria… => 24×19 DataFrame…

    Or, you can read a single parameter values for parameters that exist in the results.

    list_parameter_names(res)
+read_parameter(res, "ActivePowerTimeSeriesParameter__RenewableDispatch")
    24×30 DataFrame
    RowDateTime122_WIND_1324_PV_3312_PV_1102_PV_1101_PV_1324_PV_2313_PV_2104_PV_1101_PV_2309_WIND_1310_PV_2113_PV_1317_WIND_1314_PV_1324_PV_1103_PV_1303_WIND_1314_PV_2102_PV_2314_PV_3320_PV_1101_PV_3319_PV_1314_PV_4310_PV_1215_PV_1313_PV_1101_PV_4119_PV_1
    DateTimeFloat64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64Float64
    12020-01-01T00:00:00713.20.00.00.00.00.00.00.00.0142.80.00.0795.10.00.00.0480.80.00.00.00.00.00.00.00.00.00.00.00.0
    22020-01-01T01:00:00712.80.00.00.00.00.00.00.00.0139.10.00.0794.40.00.00.0634.90.00.00.00.00.00.00.00.00.00.00.00.0
    32020-01-01T02:00:00708.40.00.00.00.00.00.00.00.0145.30.00.0773.60.00.00.0487.30.00.00.00.00.00.00.00.00.00.00.00.0
    42020-01-01T03:00:00710.70.00.00.00.00.00.00.00.0144.80.00.0767.30.00.00.0432.70.00.00.00.00.00.00.00.00.00.00.00.0
    52020-01-01T04:00:00701.40.00.00.00.00.00.00.00.0137.10.00.0752.20.00.00.0407.90.00.00.00.00.00.00.00.00.00.00.00.0
    62020-01-01T05:00:00682.50.00.00.00.00.00.00.00.098.60.00.0719.40.00.00.0440.20.00.00.00.00.00.00.00.00.00.00.00.0
    72020-01-01T06:00:00614.70.00.00.00.00.00.00.00.062.20.00.0655.30.00.00.0377.30.00.00.00.00.00.00.00.00.00.00.00.0
    82020-01-01T07:00:00517.736.452.230.629.636.462.229.830.447.338.299.4594.647.444.829.8199.346.630.063.847.830.6179.246.438.2127.662.228.827.2
    92020-01-01T08:00:00426.663.497.436.834.863.496.035.037.048.961.4126.2579.161.265.258.4110.667.036.4100.061.437.4248.067.061.4164.695.635.456.6
    102020-01-01T09:00:00274.271.2118.038.036.471.4117.636.638.230.766.8133.2466.869.068.076.63.669.837.6121.869.838.8273.469.866.8172.2116.835.874.8
    112020-01-01T10:00:0093.072.2132.037.836.472.2130.836.638.027.470.2134.2301.470.270.289.82.472.237.4129.070.438.6277.872.270.4173.2128.437.488.2
    122020-01-01T11:00:006.370.6135.237.035.070.6134.235.437.260.969.8135.2110.767.070.298.056.272.436.6128.667.237.6263.272.469.6170.0133.238.691.6
    132020-01-01T12:00:003.867.4131.036.235.467.4129.635.636.420.467.8133.078.967.268.294.091.570.235.8128.267.437.0267.470.267.6169.0128.837.890.6
    142020-01-01T13:00:001.165.2125.435.235.065.2123.635.435.41.667.2126.6107.967.065.881.4103.067.634.8119.667.035.8258.867.667.0161.8122.835.879.2
    152020-01-01T14:00:000.060.2109.631.031.060.4108.031.431.20.063.2110.222.359.462.659.439.764.230.8107.059.431.6227.864.262.8143.2106.831.459.0
    162020-01-01T15:00:000.042.069.020.219.242.065.620.620.22.645.062.824.642.444.825.487.746.220.065.843.420.6151.646.243.882.262.820.427.8
    172020-01-01T16:00:000.90.00.00.00.00.00.00.00.037.90.00.010.80.00.00.092.30.00.00.00.00.00.00.00.00.00.00.00.0
    182020-01-01T17:00:00276.30.00.00.00.00.00.00.00.046.90.00.0243.20.00.00.089.40.00.00.00.00.00.00.00.00.00.00.00.0
    192020-01-01T18:00:00272.90.00.00.00.00.00.00.00.024.00.00.0375.20.00.00.090.40.00.00.00.00.00.00.00.00.00.00.00.0
    202020-01-01T19:00:00345.60.00.00.00.00.00.00.00.024.00.00.0568.40.00.00.081.10.00.00.00.00.00.00.00.00.00.00.00.0
    212020-01-01T20:00:00411.70.00.00.00.00.00.00.00.027.40.00.0636.10.00.00.0172.90.00.00.00.00.00.00.00.00.00.00.00.0
    222020-01-01T21:00:00376.60.00.00.00.00.00.00.00.06.50.00.0719.20.00.00.0326.90.00.00.00.00.00.00.00.00.00.00.00.0
    232020-01-01T22:00:00561.30.00.00.00.00.00.00.00.01.30.00.0734.90.00.00.0256.70.00.00.00.00.00.00.00.00.00.00.00.0
    242020-01-01T23:00:00568.40.00.00.00.00.00.00.00.00.10.00.0729.10.00.00.0141.10.00.00.00.00.00.00.00.00.00.00.00.0

    Plotting

    Take a look at the plotting capabilities in PowerGraphics.jl

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a/v0.24.1/tutorials/jl_q534pA/rts-test/logs/simulation.log b/v0.24.1/tutorials/jl_q534pA/rts-test/logs/simulation.log new file mode 100644 index 0000000000..b6b34c80ef --- /dev/null +++ b/v0.24.1/tutorials/jl_q534pA/rts-test/logs/simulation.log @@ -0,0 +1,106 @@ +┌ Info: 2023-11-01T05:19:08.173 [3091:1]: Building problem UC +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/simulation/simulation.jl:271 +┌ Info: 2023-11-01T05:19:08.216 [3091:1]: Initializing Optimization Container For a DecisionModel +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/decision_model.jl:290 +┌ Info: 2023-11-01T05:19:08.217 [3091:1]: Initializing ModelStoreParams +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/decision_model.jl:296 +┌ Info: 2023-11-01T05:19:08.217 [3091:1]: Instantiating Network Model +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/decision_model.jl:305 +┌ Info: 2023-11-01T05:19:08.218 [3091:1]: Validating connectivity with depth first search (network traversal) +└ @ PowerNetworkMatrices /home/runner/.julia/packages/PowerNetworkMatrices/jxG9P/src/system_utils.jl:12 +┌ Warning: 2023-11-01T05:19:08.218 [3091:1]: No reference bus in the subnetwork associated with bus 101. References buses will be assigned arbitrarily +└ @ PowerNetworkMatrices /home/runner/.julia/packages/PowerNetworkMatrices/jxG9P/src/common.jl:293 +┌ Info: 2023-11-01T05:19:08.218 [3091:1]: Make Initial Conditions Model +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/operation_model_interface.jl:188 +┌ Warning: 2023-11-01T05:19:08.411 [3091:1]: Overwriting ("", Symbol("VariableReserve{ReserveUp}")) existing model +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/core/service_model.jl:113 +┌ Warning: 2023-11-01T05:19:08.412 [3091:1]: Overwriting ("", Symbol("VariableReserve{ReserveUp}")) existing model +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/core/service_model.jl:113 +┌ Warning: 2023-11-01T05:19:08.413 [3091:1]: Overwriting ("", Symbol("VariableReserve{ReserveUp}")) existing model +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/core/service_model.jl:113 +┌ Warning: 2023-11-01T05:19:11.095 [3091:1]: CopperPlatePowerModel models with HVDC ignores inter-area losses +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/devices_models/device_constructors/branch_constructor.jl:645 +┌ Info: 2023-11-01T05:19:11.299 [3091:1]: Solving Initialization Model for UC +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/operation_model_interface.jl:202 +┌ Info: 2023-11-01T05:19:11.747 [3091:1]: Serialized initial conditions to ./jl_q534pA/rts-test/problems/UC/initial_conditions.bin +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/operation_model_interface.jl:211 +┌ Warning: 2023-11-01T05:19:14.104 [3091:1]: CopperPlatePowerModel models with HVDC ignores inter-area losses +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/devices_models/device_constructors/branch_constructor.jl:645 +┌ Info: 2023-11-01T05:19:14.378 [3091:1]: Solving UC with optimizer = HiGHS +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/operation_model_interface.jl:304 +┌ Info: 2023-11-01T05:19:14.514 [3091:1]: Variable bounds range is [0.0 8.47] +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/operation_model_interface.jl:265 +┌ Info: 2023-11-01T05:19:14.719 [3091:1]: Constraint coefficient bounds range is [-0.5666599999999999 4380.0] +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/operation_model_interface.jl:275 +┌ Info: 2023-11-01T05:19:14.719 [3091:1]: Constraint right-hand-side bounds [0.06 48.0] +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/operation_model_interface.jl:284 +┌ Info: 2023-11-01T05:19:14.719 [3091:1]: Building problem ED +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/simulation/simulation.jl:271 +┌ Info: 2023-11-01T05:19:14.742 [3091:1]: Initializing Optimization Container For a DecisionModel +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/decision_model.jl:290 +┌ Info: 2023-11-01T05:19:14.799 [3091:1]: Initializing ModelStoreParams +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/decision_model.jl:296 +┌ Info: 2023-11-01T05:19:14.818 [3091:1]: Instantiating Network Model +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/decision_model.jl:305 +┌ Info: 2023-11-01T05:19:14.818 [3091:1]: PTDF Matrix not provided. Calculating using PowerNetworkMatrices.PTDF +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/core/network_model.jl:92 +┌ Info: 2023-11-01T05:19:15.083 [3091:1]: Make Initial Conditions Model +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/operation_model_interface.jl:188 +┌ Info: 2023-11-01T05:19:15.083 [3091:1]: No initial conditions in the model +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/operation_model_interface.jl:133 +┌ Info: 2023-11-01T05:19:26.903 [3091:1]: Solving ED with optimizer = HiGHS +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/operation_model_interface.jl:304 +┌ Info: 2023-11-01T05:19:27.106 [3091:1]: Variable bounds range is [0.0 8.47] +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/operation_model_interface.jl:265 +┌ Info: 2023-11-01T05:19:27.745 [3091:1]: Constraint coefficient bounds range is [-0.5666599999999999 1.0e6] +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/operation_model_interface.jl:275 +┌ Info: 2023-11-01T05:19:27.745 [3091:1]: Constraint right-hand-side bounds [1.0 -5.0] +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/operation_model_interface.jl:284 +┌ Info: 2023-11-01T05:19:35.517 [3091:1]: Serialized simulation name = rts-test +│ directory = ./jl_q534pA/rts-test/simulation_files +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/simulation/simulation.jl:1082 +┌ Info: 2023-11-01T05:19:35.556 [3091:1]: Serialized time series data to ./jl_q534pA/rts-test/problems/UC/system-c357737a-cb08-43c5-9e15-7cb8cebb0813_time_series_storage.h5. +└ @ InfrastructureSystems /home/runner/.julia/packages/InfrastructureSystems/swXsu/src/time_series_storage.jl:98 +┌ Info: 2023-11-01T05:19:35.697 [3091:1]: Serialized System to ./jl_q534pA/rts-test/problems/UC/system-c357737a-cb08-43c5-9e15-7cb8cebb0813.json +└ @ PowerSystems /home/runner/.julia/packages/PowerSystems/eHeD3/src/base.jl:299 +┌ Info: 2023-11-01T05:19:35.707 [3091:1]: Serialized System metadata to ./jl_q534pA/rts-test/problems/UC/system-c357737a-cb08-43c5-9e15-7cb8cebb0813_metadata.json +└ @ PowerSystems /home/runner/.julia/packages/PowerSystems/eHeD3/src/base.jl:324 +┌ Info: 2023-11-01T05:19:35.715 [3091:1]: Serialized OperationModel to +│ bin_file_name = ./jl_q534pA/rts-test/problems/UC/model.bin +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/operation_model_serialization.jl:67 +┌ Info: 2023-11-01T05:19:35.813 [3091:1]: Serialized time series data to ./jl_q534pA/rts-test/problems/ED/system-22d25ccd-8958-4fb1-98f7-63d4ba82edf1_time_series_storage.h5. +└ @ InfrastructureSystems /home/runner/.julia/packages/InfrastructureSystems/swXsu/src/time_series_storage.jl:98 +┌ Info: 2023-11-01T05:19:35.957 [3091:1]: Serialized System to ./jl_q534pA/rts-test/problems/ED/system-22d25ccd-8958-4fb1-98f7-63d4ba82edf1.json +└ @ PowerSystems /home/runner/.julia/packages/PowerSystems/eHeD3/src/base.jl:299 +┌ Info: 2023-11-01T05:19:35.960 [3091:1]: Serialized System metadata to ./jl_q534pA/rts-test/problems/ED/system-22d25ccd-8958-4fb1-98f7-63d4ba82edf1_metadata.json +└ @ PowerSystems /home/runner/.julia/packages/PowerSystems/eHeD3/src/base.jl:324 +┌ Info: 2023-11-01T05:19:36.159 [3091:1]: Serialized OperationModel to +│ bin_file_name = ./jl_q534pA/rts-test/problems/ED/model.bin +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/operation/operation_model_serialization.jl:67 +┌ Info: 2023-11-01T05:19:40.546 [3091:1]: Initialize store cache +│ get_min_flush_size(store.cache) = 1048576 +│ get_max_size(store.cache) = 1073741824 +└ @ PowerSimulations /home/runner/work/PowerSimulations.jl/PowerSimulations.jl/src/simulation/hdf_simulation_store.jl:249 +┌ Info: 2023-11-01T05:21:48.546 [3091:1]: +│ ──────────────────────────────────────────────────────────────────────────────── +│ Time Allocations +│ ─────────────────────── ──────────────────────── +│ Tot / % measured: 131s / 100.0% 2.66GiB / 100.0% +│ +│ Section ncalls time %tot avg alloc %tot avg +│ ──────────────────────────────────────────────────────────────────────────────── +│ Execute Simulation 1 131s 100.0% 131s 2.66GiB 100.0% 2.66GiB +│ Execute ED 192 106s 80.9% 553ms 1.93GiB 72.7% 10.3MiB +│ Solve ED 192 89.7s 68.4% 467ms 595MiB 21.8% 3.10MiB +│ Update State 192 7.08s 5.4% 36.9ms 468MiB 17.2% 2.44MiB +│ Update ED 192 7.02s 5.4% 36.6ms 413MiB 15.2% 2.15MiB +│ Parameter Up... 192 6.79s 5.2% 35.4ms 409MiB 15.0% 2.13MiB +│ Ini Cond Upd... 192 119μs 0.0% 618ns 0.00B 0.0% 0.00B +│ Execute UC 2 15.8s 12.0% 7.90s 474MiB 17.4% 237MiB +│ Solve UC 2 10.3s 7.8% 5.14s 153MiB 5.6% 76.5MiB 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