Functions for Writing the Different Results/Outputs to Separate Files
Write Status
Dolphyn.write_status
— Methodwrite_status(path::AbstractString, inputs::Dict, EP::Model)
Function for writing the final solve status of the optimization problem solved.
Write Costs
Dolphyn.write_costs
— Methodwrite_costs(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
Function for writing the costs pertaining to the objective function (fixed, variable O&M etc.).
Write Emissions
Dolphyn.write_emissions
— Methodwrite_emissions(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
Function for reporting time-dependent CO$_2$ emissions by zone.
Write Capacities
Write Capacity Values
Write Capacity Reserve
Write Charge Values
Dolphyn.write_charge
— Methodwrite_charge(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
Function for writing the charging energy values of the different storage technologies.
Write Charge Costs
Write Non-Served Energy
Dolphyn.write_nse
— Methodwrite_nse(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
Function for reporting non-served energy for every model zone, time step and cost-segment.
Write Storage
Write Storage Dual
Write Long Duration Storage
Write Power
Dolphyn.write_power
— Methodwrite_power(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
Function for writing the different values of power generated by the different technologies in operation.
Write Power Balance
Write Unit Commitment
Write Curtailment
Dolphyn.write_curtailment
— Methodwrite_curtailment(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
Function for writing the curtailment values of the different variable renewable resources.
Write Network Expansion
Write Network Flow
Write Network Losses
Write Prices
Write Reliability
Write Reserves
Write Energy Revenue
Write Subsidy Revenue
Write Capacity Revenue
Dolphyn.write_reserve_margin_revenue
— Methodwrite_reserve_margin_revenue(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
Function for reporting the capacity revenue earned by each generator listed in the input file. GenX will print this file only when capacity reserve margin is modeled and the shadow price can be obtained form the solver. Each row corresponds to a generator, and each column starting from the 6th to the second last is the total revenue from each capacity reserve margin constraint. The revenue is calculated as the capacity contribution of each time steps multiplied by the shadow price, and then the sum is taken over all modeled time steps. The last column is the total revenue received from all capacity reserve margin constraints. As a reminder, GenX models the capacity reserve margin (aka capacity market) at the time-dependent level, and each constraint either stands for an overall market or a locality constraint.
Write Energy Share Requirement Revenue
Dolphyn.write_esr_revenue
— Methodwrite_esr_revenue(path::AbstractString, inputs::Dict, setup::Dict, dfPower::DataFrame, dfESR::DataFrame)
Function for reporting the renewable/clean credit revenue earned by each generator listed in the input file. GenX will print this file only when RPS/CES is modeled and the shadow price can be obtained form the solver. Each row corresponds to a generator, and each column starting from the 6th to the second last is the total revenue earned from each RPS constraint. The revenue is calculated as the total annual generation (if elgible for the corresponding constraint) multiplied by the RPS/CES price. The last column is the total revenue received from all constraint. The unit is $.