Add new resource type: CCS with solvent storage

CHANGELOG.md

@@ -11,12 +11,20 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Fusion plant optional features for thermal plants (#743).
 - Support for reusing the same Gurobi environment for multiple solves when 
 number of concurrent Gurobi uses is limited (#783).
+- Additional long-duration storage constraints to bound state of charge in 
+non-representative periods (#781).
 
 ### Changed
 - The `charge.csv` and `storage.csv` files now include only resources with 
 charge and storage variables (#760 and #763).
 - Deduplicated docs on optimized scheduled maintenance for thermal resources (#745).
 
+### Fixed
+- Add constraint to ensure that electricity charged from the grid cannot exceed 
+the charging capacity of the storage component in VRE_STOR (#770).
+- Update `getproperty` function for vectors of resources to ensure compatibility 
+with Julia v1.11 (#785).
+
 ## [0.4.1] - 2024-08-20
 
 ### Added

Project.toml

@@ -1,7 +1,7 @@
 name = "GenX"
 uuid = "5d317b1e-30ec-4ed6-a8ce-8d2d88d7cfac"
 authors = ["Bonaldo, Luca", "Chakrabarti, Sambuddha", "Cheng, Fangwei", "Ding, Yifu", "Jenkins, Jesse D.", "Luo, Qian", "Macdonald, Ruaridh", "Mallapragada, Dharik", "Manocha, Aneesha", "Mantegna, Gabe ", "Morris, Jack", "Patankar, Neha", "Pecci, Filippo", "Schwartz, Aaron", "Schwartz, Jacob", "Schivley, Greg", "Sepulveda, Nestor", "Xu, Qingyu", "Zhou, Justin"]
-version = "0.4.1-dev.9"
+version = "0.4.1-dev.13"
 
 [deps]
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"

docs/src/Tutorials/Tutorial_1_configuring_settings.md

@@ -9,7 +9,7 @@ GenX is easy to customize to fit a variety of problems. In this tutorial, we sho
 There are 21 settings available to edit in GenX, found in the file `genx_settings.yml`. These settings are described at the [Model settings parameters
 ](@ref) page of the documentation. The file is located in the `settings` folder in the working directory. To change the location of the file, edit the `settings_path` variable in `Run.jl` within your directory.
 
-Most settings are set as either 0 or 1, which correspond to whether or not to include a specific feature. For example, to use `TimeDomainReduction`, you would set its parameter to 0 within `genx_settings.yml`. If you would like to run GenX without it, you would set its parameter to 1.
+Most settings are set as either 0 or 1, which correspond to whether or not to include a specific feature. For example, to use `TimeDomainReduction`, you would set its parameter to 1 within `genx_settings.yml`. If you would like to run GenX without it, you would set its parameter to 0.
 
 Other settings, such as `CO2Cap`, have more options corresponding to integers, while some settings such as `ModelingtoGenerateAlternativeSlack` take a numerical input directly (in this case, the slack value). Two settings, `Solver` and `TimeDomainReductionFolder` take in text as input. To learn more about different solvers, read [here](https://github.com/GenXProject/GenX.jl/blob/main/docs/src/User_Guide/solver_configuration.md). For `TimeDomainReductionFolder`, specify the name of the directory you wish to see the results in. For a more comprehensive description of the input options, see the documentation linked above.
 

src/case_runners/case_runner.jl

@@ -29,6 +29,7 @@ run_genx_case!("path/to/case", Gurobi.Optimizer)
 ```
 """
 function run_genx_case!(case::AbstractString, optimizer::Any = HiGHS.Optimizer)
+    print_genx_version() # Log the GenX version
     genx_settings = get_settings_path(case, "genx_settings.yml") # Settings YAML file path
     writeoutput_settings = get_settings_path(case, "output_settings.yml") # Write-output settings YAML file path
     mysetup = configure_settings(genx_settings, writeoutput_settings) # mysetup dictionary stores settings and GenX-specific parameters

src/load_inputs/load_resources_data.jl

@@ -522,7 +522,9 @@ function check_retrofit_id(rs::Vector{T}) where {T <: AbstractResource}
     retrofit_options = ids_retrofit_options(rs)
 
     # check that all retrofit_ids for resources that can retrofit and retrofit options match
-    if Set(rs[units_can_retrofit].retrofit_id) != Set(rs[retrofit_options].retrofit_id)
+    can_retrofit_retro_ids = [r.retrofit_id for r in rs[units_can_retrofit]]  # retrofit cluster ids for units that can retrofit
+    retrofit_option_retro_ids = [r.retrofit_id for r in rs[retrofit_options]]  # retrofit cluster ids for retrofit options
+    if Set(can_retrofit_retro_ids) != Set(retrofit_option_retro_ids)
         msg = string("Retrofit IDs for resources that \"can retrofit\" and \"retrofit options\" do not match.\n" *
                      "All retrofitting units must be associated with a retrofit option.")
         push!(warning_strings, msg)

src/model/resources/hydro/hydro_inter_period_linkage.jl

@@ -42,6 +42,43 @@ Finally, the next constraint enforces that the initial storage level for each in
 \quad \forall n \in \mathcal{N}, o \in \mathcal{O}^{LDES}
 \end{aligned}
 ```
+
+**Bound storage inventory in non-representative periods**
+We need additional variables and constraints to ensure that the storage content is within zero and the installed energy capacity in non-representative periods. We introduce
+the variables $\Delta Q^{max,pos}_{o,z,m}$ and $\Delta Q^{max,neg}_{o,z,m}$ that represent the maximum positive and negative storage content variations within the representative
+period $m$, respectively, extracted as:
+
+```math
+\begin{aligned}
+& \Delta Q^{max,pos}_{o,z,m} \geq \Gamma_{o,z,(m-1)\times \tau^{period}+t } - \Gamma_{o,z,(m-1)\times \tau^{period}+1 } \quad \forall o \in \mathcal{O}^{LDES}, z \in \mathcal{Z}, m \in \mathcal{M}, t \in \mathcal{T}
+& \end{aligned}
+```
+
+```math
+\begin{aligned}
+& \Delta Q^{max,neg}_{o,z,m} \leq \Gamma_{o,z,(m-1)\times \tau^{period}+t } - \Gamma_{o,z,(m-1)\times \tau^{period}+1 } \quad \forall o \in \mathcal{O}^{LDES}, z \in \mathcal{Z}, m \in \mathcal{M}, t \in \mathcal{T}
+& \end{aligned}
+```
+
+For every input period $n \in \mathcal{N}$, the maximum storage is computed and constrained to be less than or equal to the installed energy capacity as:
+
+```math
+\begin{aligned}
+&  Q_{o,z,n} \times \left(1-\eta_{o,z}^{loss}\right) - \frac{1}{\eta_{o,z}^{discharge}}\Theta_{o,z,(m-1)\times \tau^{period}+1} + \eta_{o,z}^{charge}\Pi_{o,z,(m-1)\times \tau^{period}+1} + \Delta Q^{max,pos}_{o,z,f(n)} \leq \Delta^{total, energy}_{o,z} \\
+& \forall o \in \mathcal{O}^{LDES}, z \in \mathcal{Z}, n \in \mathcal{N}
+& \end{aligned}
+```
+
+Similarly, the minimum storage content is imposed to be positive in every period of the time horizon:
+
+```math
+\begin{aligned}
+&  Q_{o,z,n} \times \left(1-\eta_{o,z}^{loss}\right) - \frac{1}{\eta_{o,z}^{discharge}}\Theta_{o,z,(m-1)\times \tau^{period}+1} + \eta_{o,z}^{charge}\Pi_{o,z,(m-1)\times \tau^{period}+1} + \Delta Q^{max,neg}_{o,z,f(n)} \geq 0 \\
+& \forall o \in \mathcal{O}^{LDES}, z \in \mathcal{Z}, n \in \mathcal{N}
+& \end{aligned}
+```
+
+Additional details on this approach are available in [Parolin et al., 2024](https://doi.org/10.48550/arXiv.2409.19079).
 """
 function hydro_inter_period_linkage!(EP::Model, inputs::Dict)
     println("Long Duration Storage Module for Hydro Reservoir")
@@ -71,6 +108,12 @@ function hydro_inter_period_linkage!(EP::Model, inputs::Dict)
     # Build up inventory can be positive or negative
     @variable(EP, vdSOC_HYDRO[y in STOR_HYDRO_LONG_DURATION, w = 1:REP_PERIOD])
 
+    # Maximum positive storage inventory change within subperiod
+	@variable(EP, vdSOC_maxPos_HYDRO[y in STOR_HYDRO_LONG_DURATION, w=1:REP_PERIOD] >= 0)
+
+	# Maximum negative storage inventory change within subperiod
+	@variable(EP, vdSOC_maxNeg_HYDRO[y in STOR_HYDRO_LONG_DURATION, w=1:REP_PERIOD] <= 0)	
+
     ### Constraints ###
 
     # Links last time step with first time step, ensuring position in hour 1 is within eligible change from final hour position
@@ -111,4 +154,27 @@ function hydro_inter_period_linkage!(EP::Model, inputs::Dict)
             r in REP_PERIODS_INDEX],
         vSOC_HYDROw[y,r]==EP[:vS_HYDRO][y, hours_per_subperiod * dfPeriodMap[r, :Rep_Period_Index]] -
                 vdSOC_HYDRO[y, dfPeriodMap[r, :Rep_Period_Index]])
+
+    # Extract maximum storage level variation (positive) within subperiod
+    @constraint(EP, cMaxSoCVarPos_H[y in STOR_HYDRO_LONG_DURATION, w=1:REP_PERIOD, t=2:hours_per_subperiod],
+                    vdSOC_maxPos_HYDRO[y,w] >= EP[:vS_HYDRO][y,hours_per_subperiod*(w-1)+t] - EP[:vS_HYDRO][y,hours_per_subperiod*(w-1)+1])
+
+    # Extract maximum storage level variation (negative) within subperiod
+    @constraint(EP, cMaxSoCVarNeg_H[y in STOR_HYDRO_LONG_DURATION, w=1:REP_PERIOD, t=2:hours_per_subperiod],
+                    vdSOC_maxNeg_HYDRO[y,w] <= EP[:vS_HYDRO][y,hours_per_subperiod*(w-1)+t] - EP[:vS_HYDRO][y,hours_per_subperiod*(w-1)+1])
+
+    # Max storage content within each modeled period cannot exceed installed energy capacity
+    @constraint(EP, cSoCLongDurationStorageMaxInt_H[y in STOR_HYDRO_LONG_DURATION, r in MODELED_PERIODS_INDEX],
+        vSOC_HYDROw[y,r]-(1/efficiency_down(gen[y])*EP[:vP][y,hours_per_subperiod*(dfPeriodMap[r,:Rep_Period_Index]-1)+1])
+        -EP[:vSPILL][y,hours_per_subperiod*(dfPeriodMap[r,:Rep_Period_Index]-1)+1]
+        +inputs["pP_Max"][y,hours_per_subperiod*(dfPeriodMap[r,:Rep_Period_Index]-1)+1]*EP[:eTotalCap][y]
+        +vdSOC_maxPos_HYDRO[y,dfPeriodMap[r,:Rep_Period_Index]] <= hydro_energy_to_power_ratio(gen[y])*EP[:eTotalCap][y])
+
+    # Min storage content within each modeled period cannot be negative
+    @constraint(EP, cSoCLongDurationStorageMinInt_H[y in STOR_HYDRO_LONG_DURATION, r in MODELED_PERIODS_INDEX],
+        vSOC_HYDROw[y,r]-(1/efficiency_down(gen[y])*EP[:vP][y,hours_per_subperiod*(dfPeriodMap[r,:Rep_Period_Index]-1)+1])
+        -EP[:vSPILL][y,hours_per_subperiod*(dfPeriodMap[r,:Rep_Period_Index]-1)+1]
+        +inputs["pP_Max"][y,hours_per_subperiod*(dfPeriodMap[r,:Rep_Period_Index]-1)+1]*EP[:eTotalCap][y]
+        +vdSOC_maxPos_HYDRO[y,dfPeriodMap[r,:Rep_Period_Index]] >= 0)     
+
 end

src/model/resources/resources.jl

@@ -66,9 +66,7 @@ Allows to set the attribute `sym` of an `AbstractResource` object using dot synt
 - `value`: The value to set for the attribute.
 
 """
-Base.setproperty!(r::AbstractResource, sym::Symbol, value) = setindex!(parent(r),
-    value,
-    sym)
+Base.setproperty!(r::AbstractResource, sym::Symbol, value) = setindex!(parent(r), value, sym)
 
 """
     haskey(r::AbstractResource, sym::Symbol)
@@ -106,32 +104,31 @@ end
 """ 
     Base.getproperty(rs::Vector{<:AbstractResource}, sym::Symbol)
 
-Allows to access attributes of a vector of `AbstractResource` objects using dot syntax. If the `sym` is an element of the `resource_types` constant, it returns all resources of that type. Otherwise, it returns the value of the attribute for each resource in the vector.
+Allows to return all resources of a given type of a vector of `AbstractResource` objects using dot syntax.
 
 # Arguments:
 - `rs::Vector{<:AbstractResource}`: The vector of `AbstractResource` objects.
-- `sym::Symbol`: The symbol representing the attribute name or a type from `resource_types`.
+- `sym::Symbol`: The symbol representing the type from `resource_types`.
 
 # Returns:
 - If `sym` is an element of the `resource_types` constant, it returns a vector containing all resources of that type.
-- If `sym` is an attribute name, it returns a vector containing the value of the attribute for each resource.
 
 ## Examples
 ```julia
 julia> vre_gen = gen.Vre;  # gen vector of resources
 julia> typeof(vre_gen)
 Vector{Vre} (alias for Array{Vre, 1})
-julia> vre_gen.zone
+julia> GenX.zone_id.(vre_gen)
 ```
 """
 function Base.getproperty(rs::Vector{<:AbstractResource}, sym::Symbol)
-    # if sym is Type then return a vector resources of that type
+    # if sym is one of the resource types then return a vector resources of that type
     if sym ∈ resource_types
         res_type = eval(sym)
         return Vector{res_type}(rs[isa.(rs, res_type)])
+    else
+        return getfield(rs, sym)
     end
-    # if sym is a field of the resource then return that field for all resources
-    return [getproperty(r, sym) for r in rs]
 end
 
 """
@@ -255,8 +252,7 @@ julia> findall(r -> max_cap_mwh(r) != 0, gen.Storage)
  50
 ```
 """
-Base.findall(f::Function, rs::Vector{<:AbstractResource}) = resource_id.(filter(r -> f(r),
-    rs))
+Base.findall(f::Function, rs::Vector{<:AbstractResource}) = resource_id.(filter(r -> f(r), rs))
 
 """
     interface(name, default=default_zero, type=AbstractResource)
@@ -531,14 +527,14 @@ const default_zero = 0
 
 # INTERFACE FOR ALL RESOURCES
 resource_name(r::AbstractResource) = r.resource
-resource_name(rs::Vector{T}) where {T <: AbstractResource} = rs.resource
+resource_name(rs::Vector{T}) where {T <: AbstractResource} = resource_name.(rs)
 
 resource_id(r::AbstractResource)::Int64 = r.id
 resource_id(rs::Vector{T}) where {T <: AbstractResource} = resource_id.(rs)
 resource_type_mga(r::AbstractResource) = r.resource_type
 
 zone_id(r::AbstractResource) = r.zone
-zone_id(rs::Vector{T}) where {T <: AbstractResource} = rs.zone
+zone_id(rs::Vector{T}) where {T <: AbstractResource} = zone_id.(rs)
 
 # getter for boolean attributes (true or false) with validation
 function new_build(r::AbstractResource)

src/model/resources/storage/long_duration_storage.jl

@@ -55,7 +55,44 @@ If the capacity reserve margin constraint is enabled, a similar set of constrain
 & \frac{1}{\eta_{o,z}^{discharge}}\Theta^{CRM}_{o,z,(m-1)\times \tau^{period}+1} - \eta_{o,z}^{charge}\Pi^{CRM}_{o,z,(m-1)\times \tau^{period}+1} \quad \forall o \in \mathcal{O}^{LDES}, z \in \mathcal{Z}, m \in \mathcal{M}
 \end{aligned}
 ```
-All other constraints are identical to those used to track the actual state of charge, except with the new variables $Q^{CRM}_{o,z,n}$ and $\Delta Q^{CRM}_{o,z,n}$ used in place of $Q_{o,z,n}$ and $\Delta Q_{o,z,n}$, respectively.
+All other constraints are identical to those used to track the actual state of charge, except with the new variables $Q^{CRM}_{o,z,n}$ and $\Delta Q^{CRM}_{o,z,n}$ used in place of $Q_{o,z,n}$ and $\Delta Q_{o,z,n}$, respectively. \
+
+**Bound storage inventory in non-representative periods**
+We need additional variables and constraints to ensure that the storage content is within zero and the installed energy capacity in non-representative periods. We introduce
+the variables $\Delta Q^{max,pos}_{o,z,m}$ and $\Delta Q^{max,neg}_{o,z,m}$ that represent the maximum positive and negative storage content variations within the representative
+period $m$, respectively, extracted as:
+
+```math
+\begin{aligned}
+& \Delta Q^{max,pos}_{o,z,m} \geq \Gamma_{o,z,(m-1)\times \tau^{period}+t } - \Gamma_{o,z,(m-1)\times \tau^{period}+1 } \quad \forall o \in \mathcal{O}^{LDES}, z \in \mathcal{Z}, m \in \mathcal{M}, t \in \mathcal{T}
+& \end{aligned}
+```
+
+```math
+\begin{aligned}
+& \Delta Q^{max,neg}_{o,z,m} \leq \Gamma_{o,z,(m-1)\times \tau^{period}+t } - \Gamma_{o,z,(m-1)\times \tau^{period}+1 } \quad \forall o \in \mathcal{O}^{LDES}, z \in \mathcal{Z}, m \in \mathcal{M}, t \in \mathcal{T}
+& \end{aligned}
+```
+
+For every input period $n \in \mathcal{N}$, the maximum storage is computed and constrained to be less than or equal to the installed energy capacity as:
+
+```math
+\begin{aligned}
+&  Q_{o,z,n} \times \left(1-\eta_{o,z}^{loss}\right) - \frac{1}{\eta_{o,z}^{discharge}}\Theta_{o,z,(m-1)\times \tau^{period}+1} + \eta_{o,z}^{charge}\Pi_{o,z,(m-1)\times \tau^{period}+1} + \Delta Q^{max,pos}_{o,z,f(n)} \leq \Delta^{total, energy}_{o,z} \\
+& \forall o \in \mathcal{O}^{LDES}, z \in \mathcal{Z}, n \in \mathcal{N}
+& \end{aligned}
+```
+
+Similarly, the minimum storage content is imposed to be positive in every period of the time horizon:
+
+```math
+\begin{aligned}
+&  Q_{o,z,n} \times \left(1-\eta_{o,z}^{loss}\right) - \frac{1}{\eta_{o,z}^{discharge}}\Theta_{o,z,(m-1)\times \tau^{period}+1} + \eta_{o,z}^{charge}\Pi_{o,z,(m-1)\times \tau^{period}+1} + \Delta Q^{max,neg}_{o,z,f(n)} \geq 0 \\
+& \forall o \in \mathcal{O}^{LDES}, z \in \mathcal{Z}, n \in \mathcal{N}
+& \end{aligned}
+```
+
+Additional details on this approach are available in [Parolin et al., 2024](https://doi.org/10.48550/arXiv.2409.19079).
 """
 function long_duration_storage!(EP::Model, inputs::Dict, setup::Dict)
     println("Long Duration Storage Module")
@@ -96,6 +133,12 @@ function long_duration_storage!(EP::Model, inputs::Dict, setup::Dict)
         @variable(EP, vCAPRES_dsoc[y in STOR_LONG_DURATION, w = 1:REP_PERIOD])
     end
 
+    # Maximum positive storage inventory change within subperiod
+	@variable(EP, vdSOC_maxPos[y in STOR_LONG_DURATION, w=1:REP_PERIOD] >= 0)
+
+	# Maximum negative storage inventory change within subperiod
+	@variable(EP, vdSOC_maxNeg[y in STOR_LONG_DURATION, w=1:REP_PERIOD] <= 0)
+
     ### Constraints ###
 
     # Links last time step with first time step, ensuring position in hour 1 is within eligible change from final hour position
@@ -181,4 +224,24 @@ function long_duration_storage!(EP::Model, inputs::Dict, setup::Dict)
                 r in MODELED_PERIODS_INDEX],
             vSOCw[y, r]>=vCAPRES_socw[y, r])
     end
+
+    # Extract maximum storage level variation (positive) within subperiod
+	@constraint(EP, cMaxSoCVarPos[y in STOR_LONG_DURATION, w=1:REP_PERIOD, t=2:hours_per_subperiod],
+                    vdSOC_maxPos[y,w] >= EP[:vS][y,hours_per_subperiod*(w-1)+t] - EP[:vS][y,hours_per_subperiod*(w-1)+1])
+
+    # Extract maximum storage level variation (negative) within subperiod
+    @constraint(EP, cMaxSoCVarNeg[y in STOR_LONG_DURATION, w=1:REP_PERIOD, t=2:hours_per_subperiod],
+                    vdSOC_maxNeg[y,w] <= EP[:vS][y,hours_per_subperiod*(w-1)+t] - EP[:vS][y,hours_per_subperiod*(w-1)+1])
+
+    # Max storage content within each modeled period cannot exceed installed energy capacity
+    @constraint(EP, cSoCLongDurationStorageMaxInt[y in STOR_LONG_DURATION, r in MODELED_PERIODS_INDEX],
+            (1-self_discharge(gen[y]))*vSOCw[y,r]-(1/efficiency_down(gen[y])*EP[:vP][y,hours_per_subperiod*(dfPeriodMap[r,:Rep_Period_Index]-1)+1])
+            +(efficiency_up(gen[y])*EP[:vCHARGE][y,hours_per_subperiod*(dfPeriodMap[r,:Rep_Period_Index]-1)+1])
+            +vdSOC_maxPos[y,dfPeriodMap[r,:Rep_Period_Index]] <= EP[:eTotalCapEnergy][y])
+
+    # Min storage content within each modeled period cannot be negative
+    @constraint(EP, cSoCLongDurationStorageMinInt[y in STOR_LONG_DURATION, r in MODELED_PERIODS_INDEX],
+            (1-self_discharge(gen[y]))*vSOCw[y,r]-(1/efficiency_down(gen[y])*EP[:vP][y,hours_per_subperiod*(dfPeriodMap[r,:Rep_Period_Index]-1)+1])
+            +(efficiency_up(gen[y])*EP[:vCHARGE][y,hours_per_subperiod*(dfPeriodMap[r,:Rep_Period_Index]-1)+1])
+            +vdSOC_maxNeg[y,dfPeriodMap[r,:Rep_Period_Index]] >= 0)
 end