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Rh/psy methods New script for simple CEM #10

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Rh/psy methods New script for simple CEM #10

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c966df3
added simple_cem script
jerrypotts May 30, 2024
d2a5f53
updated to use portfolio structs
jerrypotts May 30, 2024
0aa8a77
added exts for renewable tech
jerrypotts May 30, 2024
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88 changes: 74 additions & 14 deletions scripts/portfolio_test.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,7 @@
const PSY = PowerSystems
const PSIP = PowerSystemsInvestmentsPortfolios

data = PSY._create_system_data_from_kwargs()
#data = PSY._create_system_data_from_kwargs()

#bus = ACBus(nothing)
#discount_rate = 0.07
Expand All @@ -29,17 +29,23 @@
)

t_th_ext = t_th.ext
t_th_ext["capital_cost"] = 50.0
t_th_ext["capital_cost"] = [50.0, 125.0]
t_th_ext["operations_cost"] = [5.0, 2.5]
t_th_ext["variable_cost"] = [1.0, 1.0]
t_th_ext["investment_periods"] = [2030, 2040]
# one option is to repeat these for each investment
t_th_ext["operational_periods"] = [1, 2, 3]
t_th_ext["operational_periods_2"] = [
1, 2, 3, # first investment period

Check warning on line 39 in scripts/portfolio_test.jl

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GitHub Actions / build (1, x86, ubuntu-latest) 

[JuliaFormatter] reported by reviewdog 🐶


Raw Output:
scripts/portfolio_test.jl:39:-    1, 2, 3, # first investment period
scripts/portfolio_test.jl:40:-    4, 5, 6  # second investment period
scripts/portfolio_test.jl:39:+    1,
scripts/portfolio_test.jl:40:+    2,
scripts/portfolio_test.jl:41:+    3, # first investment period
scripts/portfolio_test.jl:42:+    4,
scripts/portfolio_test.jl:43:+    5,
scripts/portfolio_test.jl:44:+    6,  # second investment period
4, 5, 6 # second investment period
]
t_th_ext["investment_operational_periods_map"] = Dict(
2030 => [1, 2, 3],
2040 => [4, 5, 6],
1 => 2030,
2 => 2030,
3 => 2030,
4 => 2040,
5 => 2040,
6 => 2040,
)
t_th_ext["initial_capacity"] = 200.0 # Data in MW
t_th_ext["maximum_capacity"] = 10000.0
Expand All @@ -56,9 +62,30 @@
)

t_th_exp_ext = t_th_exp.ext
t_th_exp_ext["capital_cost"] = 150.0
t_th_exp_ext["capital_cost"] = [150.0, 100.0]
t_th_exp_ext["operations_cost"] = [15.0, 10.0]
t_th_exp_ext["variable_cost"] = [1.0, 1.0]
t_th_exp_ext["investment_periods"] = [2030, 2040]
# one option is to repeat these for each investment
t_th_exp_ext["operational_periods"] = [1, 2, 3]
t_th_exp_ext["operational_periods_2"] = [
1, 2, 3, # first investment period
4, 5, 6 # second investment period
]
t_th_exp_ext["investment_operational_periods_map"] = Dict(
1 => 2030,
2 => 2030,
3 => 2030,
4 => 2040,
5 => 2040,
6 => 2040,
)
t_th_exp_ext["initial_capacity"] = 200.0 # Data in MW
t_th_exp_ext["maximum_capacity"] = 10000.0
t_th_exp_ext["minimum_required_capacity"] = [0.0, 0.0]


# Initial Capacity
# Renewable Technology

t_re = SupplyTechnology{RenewableDispatch}(
name="renewable_tech",
Expand All @@ -71,21 +98,54 @@
)

t_re_ext = t_re.ext
t_re_ext["capital_cost"] = 100.0
t_re_ext["variable_capacity_factor"] = [0.8, 0.6, 0.3]
t_re_ext["capital_cost"] = [100.0, 75.0]
t_re_ext["operations_cost"] = [10.0, 6.5]
t_re_ext["variable_cost"] = [0, 0]
t_re_ext["variable_capacity_factor"] = [0.8, 0.6, 0.3, 0.5, 0.9, 0.4]
t_re_ext["investment_periods"] = [2030, 2040]
# one option is to repeat these for each investment
t_re_ext["operational_periods"] = [1, 2, 3]
t_re_ext["operational_periods_2"] = [
1, 2, 3, # first investment period
4, 5, 6 # second investment period
]
t_re_ext["investment_operational_periods_map"] = Dict(
1 => 2030,
2 => 2030,
3 => 2030,
4 => 2040,
5 => 2040,
6 => 2040,
)
t_re_ext["initial_capacity"] = 200.0 # Data in MW
t_re_ext["maximum_capacity"] = 10000.0
t_re_ext["minimum_required_capacity"] = [0.0, 0.0]


# Demand side technologies
d_1 = DemandSideTechnology{ElectricLoad}(
name="demand",
available=true,
capital_cost
)


PSIP.add_technology!(p, t_th)
PSIP.add_technology!(p, t_re)
PSIP.add_technology!(p, t_th_exp)


IS.serialize(t)
IS.serialize(t_th)
IS.serialize(t_re)
IS.serialize(t_th_exp)
IS.serialize(p)

get_technologies(x -> (!get_available(x)), SupplyTechnology{ThermalStandard}, p)
#get_technologies(x -> (!get_available(x)), SupplyTechnology{ThermalStandard}, p)

get_technologies(SupplyTechnology{ThermalStandard}, p)
PSIP.remove_technology!(SupplyTechnology{ThermalStandard}, p, "thermal_tech")
#get_technologies(SupplyTechnology{ThermalStandard}, p)
#PSIP.remove_technology!(SupplyTechnology{ThermalStandard}, p, "thermal_tech")

get_available(t)
IS.deserialize(p)
#get_available(t_th)
#get_available(t_re)
#get_available(t_th_exp)
#IS.deserialize(p)
243 changes: 243 additions & 0 deletions scripts/simple_cem.jl
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Original file line number Diff line number Diff line change
@@ -0,0 +1,243 @@
using HiGHS
using JuMP

abstract type GenTech end
abstract type InvestmentModel end
abstract type OperationModel end
abstract type RegionalModel end
abstract type OptimizationModel end
#mutable struct ThermalGen <: GenTech end

# Include simplified portfolio
include("portfolio_test.jl")

#struct to define basic capacity expansion model, broken down into operation and InvestmentModel
struct SimpleInvest <: InvestmentModel end
struct SimpleOp <: OperationModel end

#Defining Model types
inv = SimpleInvest()
op = SimpleOp()

# Defining empty dictionaries for constraints, expressions, variables, etc. How is this done in Sienna?

# investment definitions
build = Dict()
capacity = Dict()
build_nonneg = Dict()
cap_bounds = Dict()
capital_costs = Dict()
fom_costs = Dict()

# operations definitions
dispatch = Dict()
dispatch_lb = Dict()
dispatch_ub = Dict()
dispatch_limit = Dict()
demand_matching = Dict()
vom_costs = Dict()

##################
# Investment variables
##################

function add_variables!(model, T::SupplyTechnology{ThermalStandard}, U::SimpleInvest)
print("Thermal investment variables called \n")
for t in T.ext["investment_periods"]

i = findfirst(==(t), T.ext["investment_periods"])

# Build and capacity variables
build[T.name, t] = JuMP.@variable(model)
capacity[T.name, t] = JuMP.@expression(model, (T.ext["initial_capacity"] + sum( build[T.name,t_p] for t_p in T.ext["investment_periods"] if t_p <= t)))

# Investment and FOM cost calculations
capital_costs[T.name, t] = JuMP.@expression(model, T.ext["capital_cost"][i]*build[T.name, t])
fom_costs[T.name, t] = JuMP.@expression(model, T.ext["operations_cost"][i]*capacity[T.name, t])

end

end

function add_variables!(model, T::SupplyTechnology{RenewableDispatch}, U::SimpleInvest)
print("Renewable investment variables called \n")
for t in T.ext["investment_periods"]

i = findfirst(==(t), T.ext["investment_periods"])

# Build and capacity variables
build[T.name, t] = JuMP.@variable(model)
capacity[T.name, t] = JuMP.@expression(model, (T.ext["initial_capacity"] + sum( build[T.name,t_p] for t_p in T.ext["investment_periods"] if t_p <= t)))

# Investment and FOM cost calculations
capital_costs[T.name, t] = JuMP.@expression(model, T.ext["capital_cost"][i]*build[T.name, t])
fom_costs[T.name, t] = JuMP.@expression(model, T.ext["operations_cost"][i]*capacity[T.name, t])

end

end

############
# Operations variables
############

function add_variables!(model, T::SupplyTechnology{ThermalStandard}, U::SimpleOp)
print("Thermal operation variable called \n")
for t in T.ext["operational_periods_2"]

i = findfirst(==(t), T.ext["operational_periods_2"])

i_mapper = findfirst(==(t_th.ext["investment_operational_periods_map"][t]), t_th.ext["investment_periods"])

#Dispatch Variable
dispatch[T.name, t] = JuMP.@variable(model)

#VOM costs
vom_costs[T.name, t] = JuMP.@expression(model, dispatch[T.name, t]*T.ext["variable_cost"][i_mapper])

end

end

function add_variables!(model, T::SupplyTechnology{RenewableDispatch}, U::SimpleOp)
print("Renewable operation variable called\n")
for t in T.ext["operational_periods_2"]

i = findfirst(==(t), T.ext["operational_periods_2"])

i_mapper = findfirst(==(t_th.ext["investment_operational_periods_map"][t]), t_th.ext["investment_periods"])

#Dispatch Variable
dispatch[T.name, t] = JuMP.@variable(model)

#VOM costs
vom_costs[T.name, t] = JuMP.@expression(model, dispatch[T.name, t]*T.ext["variable_cost"][i_mapper])

end

end

############
# Investment constraints
############

function add_constraints!(model, T::SupplyTechnology{ThermalStandard}, U::SimpleInvest)
print("Thermal investment constraints called\n")
for t in T.ext["investment_periods"]

i = findfirst(==(t), T.ext["investment_periods"])

# Build and capacity variable bounds
build_nonneg[T.name, t] = JuMP.@constraint(model, 0 <= build[T.name, t])
cap_bounds[T.name, t] = JuMP.@constraint(model, T.ext["minimum_required_capacity"][i] <= capacity[T.name, t] <= T.ext["maximum_capacity"])

end

end

function add_constraints!(model, T::SupplyTechnology{RenewableDispatch}, U::SimpleInvest)
print("Renewable investment constraints called\n")
for t in T.ext["investment_periods"]

i = findfirst(==(t), T.ext["investment_periods"])

# Build and capacity variable bounds
build_nonneg[T.name, t] = JuMP.@constraint(model, 0 <= build[T.name, t])
cap_bounds[T.name, t] = JuMP.@constraint(model, T.ext["minimum_required_capacity"][i] <= capacity[T.name, t] <= T.ext["maximum_capacity"])

end

end

###########
# Operations Constraints
###########

function add_constraints!(model, T::SupplyTechnology{ThermalStandard}, U::SimpleOp)
print("Thermal operations constraints called\n")
for t in T.ext["operational_periods_2"]

i = findfirst(==(t), T.ext["operational_periods_2"])

i_mapper = findfirst(==(t_th.ext["investment_operational_periods_map"][t]), t_th.ext["investment_periods"])

# Dispatch Variable
dispatch_lb[T.name, t] = JuMP.@constraint(model, 0 <= dispatch[T.name, t])
dispatch_ub[T.name, t] = JuMP.@constraint(model, dispatch[T.name, t] <=
T.capacity_factor*capacity[T.name, T.ext["investment_operational_periods_map"][t]])

end

end

function add_constraints!(model, T::SupplyTechnology{RenewableDispatch}, U::SimpleOp)
print("Renewable operations constraints called\n")
for t in T.ext["operational_periods_2"]

i = findfirst(==(t), T.ext["operational_periods_2"])

i_mapper = findfirst(==(t_th.ext["investment_operational_periods_map"][t]), t_th.ext["investment_periods"])

# Dispatch Variable
dispatch_lb[T.name, t] = JuMP.@constraint(model, 0 <= dispatch[T.name, t])
dispatch_ub[T.name, t] = JuMP.@constraint(model, dispatch[T.name, t] <=
T.ext["variable_capacity_factor"][i]*T.capacity_factor*capacity[T.name, T.ext["investment_operational_periods_map"][t]])

end

end

function add_constraints!(model, U::SimpleOp)
print("system operations constraints called\n")
for t in T_o

demand_matching[t] = JuMP.@constraint(model, loads[t] <= sum(dispatch[g,t] for g in gens))

end

end

#############
# Objective function
#############

function add_objective_function!(model)
JuMP.@objective(model, Min, sum(capital_costs[g, t]+fom_costs[g, t] for g in gens for t in T_i)+weights[t]*sum(vom_costs[g, t] for g in gens for t in T_o))
end

##################
# Running the optimization model
##################

#defining toy data for writing model
loads = Dict(1 => 100, 2 => 150, 3 => 175, 4 => 80, 5=>300, 6=>120)
weights = Dict(1 => 12, 2 => 12, 3 => 12, 4 => 12, 5=>12, 6=>12)

# initialize model
model = JuMP.Model(HiGHS.Optimizer)

# Calling investment variables
add_variables!(model, t_th, inv)
add_variables!(model, t_th_exp, inv)
add_variables!(model, t_re, inv)

# Calling investment constraints
add_constraints!(model, t_th, inv)
add_constraints!(model, t_th_exp, inv)
add_constraints!(model, t_re, inv)

# Calling operation variable definitions
add_variables!(model, t_th, op)
add_variables!(model, t_th_exp, op)
add_variables!(model, t_re, op)

# Calling operation constraint definitions
add_constraints!(model, t_th, op)
add_constraints!(model, t_th_exp, op)
add_constraints!(model, t_re, op)

# Calling demand matching constraints
add_constraints!(model, op)

# Calling objective function
add_objective_function!(model)
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