Output functions

collect_results(system::System, model::Model, settings::NamedTuple, period_index::Int64=1, scaling::Float64=1.0)

Returns a DataFrame with all the results after the optimization is performed.

Arguments

• system::System: The system object containing the case inputs.
• model::Model: The model being optimized.
• settings::NamedTuple: The settings for the system, including output configurations.
• period_index::Int64: The index of the period to collect results for (default is 1).
• scaling::Float64: The scaling factor for the results.

Returns

• DataFrame: A `DataFrame containing all the outputs from a system.

Example

collect_results(system, model)
198534×12 DataFrame
    Row │ case_name  commodity    commodity_subtype  zone        resource_id                component_id                       type              variable  segment  time   value
        │ Missing    Symbol       Symbol             Symbol      Symbol                     Symbol                             Symbol            Symbol    Int64    Int64  Float64
────────┼─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
      1 │   missing  Biomass      flow               bioherb_SE  SE_BECCS_Electricity_Herb  SE_BECCS_Electricity_Herb_biomas…  BECCSElectricity  flow            1      1  0.0
      2 │   missing  Biomass      flow               bioherb_SE  SE_BECCS_Electricity_Herb  SE_BECCS_Electricity_Herb_biomas…  BECCSElectricity  flow            1      2  0.0
      3 │   missing  Biomass      flow               bioherb_SE  SE_BECCS_Electricity_Herb  SE_BECCS_Electricity_Herb_biomas…  BECCSElectricity  flow            1      3  0.0
      ...

get_optimal_capacity(system::System; scaling::Float64=1.0)

Get the optimal capacity values for all assets/edges in a system.

Arguments

• system::System: The system containing the assets/edges to analyze
• scaling::Float64: The scaling factor for the results.

Returns

• DataFrame: A dataframe containing the optimal capacity values for all assets/edges, with missing columns removed

Example

get_optimal_capacity(system)
153×8 DataFrame
 Row │ commodity    commodity_subtype  zone           resource_id                        component_id                       type              variable  value    
     │ Symbol       Symbol             Symbol         Symbol                             Symbol                             Symbol            Symbol    Float64 
─────┼─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
   1 │ Electricity  capacity           elec_SE        existing_solar_SE                  existing_solar_SE_edge             VRE               capacity   8.5022
   2 │ Electricity  capacity           elec_NE        existing_solar_NE                  existing_solar_NE_edge             VRE               capacity   0.0   
   3 │ Electricity  capacity           elec_NE        existing_wind_NE                   existing_wind_NE_edge              VRE               capacity   3.6545

Helper function to extract discounted costs from the optimization results and return them as a DataFrame.

get_optimal_flow(
    system::System; 
    scaling::Float64=1.0, 
    commodity::Union{AbstractString,Vector{<:AbstractString},Nothing}=nothing, 
    asset_type::Union{AbstractString,Vector{<:AbstractString},Nothing}=nothing
)

Get the optimal flow values for all edges in a system.

Filtering

Results can be filtered by:

• commodity: Specific commodity type(s)
• asset_type: Specific asset type(s)

Pattern Matching

Two types of pattern matching are supported:

1. Parameter-free matching:

   • "ThermalPower" matches any ThermalPower{...} type (i.e. no need to specify parameters inside {})

2. Wildcards using "*":

   • "ThermalPower*" matches ThermalPower{Fuel}, ThermalPowerCCS{Fuel}, etc.
   • "CO2*" matches CO2, CO2Captured, etc.

Arguments

• system::System: The system containing the all edges to output
• scaling::Float64: The scaling factor for the results.
• commodity::Union{AbstractString,Vector{<:AbstractString},Nothing}: The commodity to filter by
• asset_type::Union{AbstractString,Vector{<:AbstractString},Nothing}: The asset type to filter by

Returns

• DataFrame: A dataframe containing the optimal flow values for all edges, with missing columns removed

Example

get_optimal_flow(system)
186984×11 DataFrame
    Row │ commodity    commodity_subtype  zone        resource_id                component_id                       type              variable  segment  time   value     
        │ Symbol       Symbol             Symbol      Symbol                     Symbol                             Symbol            Symbol    Int64    Int64  Float64
────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
      1 │ Biomass      flow               bioherb_SE  SE_BECCS_Electricity_Herb  SE_BECCS_Electricity_Herb_biomas…  BECCSElectricity  flow            1      1  0.0    
      2 │ Biomass      flow               bioherb_SE  SE_BECCS_Electricity_Herb  SE_BECCS_Electricity_Herb_biomas…  BECCSElectricity  flow            1      2  0.0    
      3 │ Biomass      flow               bioherb_SE  SE_BECCS_Electricity_Herb  SE_BECCS_Electricity_Herb_biomas…  BECCSElectricity  flow            1      3  0.0    
      ...
# Filter by commodity
get_optimal_flow(system, commodity="Electricity")
# Filter by commodity and asset type using parameter-free matching
get_optimal_flow(system, commodity="Electricity", asset_type="ThermalPower") # only ThermalPower{Fuel} will be returned
# Filter by commodity and asset type using wildcard matching
get_optimal_flow(system, commodity="Electricity", asset_type="ThermalPower*") # all types starting with ThermalPower (e.g., ThermalPower{Fuel}, ThermalPowerCCS{Fuel}) will be returned)

get_optimal_flow(asset::AbstractAsset, scaling::Float64=1.0)

Get the optimal flow values for all edges in an asset.

Arguments

• asset::AbstractAsset: The asset containing the edges to analyze
• scaling::Float64: The scaling factor for the results.

Returns

• DataFrame: A dataframe containing the optimal flow values for all edges, with missing columns removed

Example

asset = get_asset_by_id(system, :elec_SE)
get_optimal_flow(asset)

get_optimal_flow(edge::AbstractEdge, scaling::Float64=1.0)

Get the optimal flow values for an edge.

Arguments

• edge::AbstractEdge: The edge to analyze
• scaling::Float64: The scaling factor for the results.

Returns

• DataFrame: A dataframe containing the optimal flow values for the edge, with missing columns removed

Example

asset = get_asset_by_id(system, :elec_SE)
elec_edge = asset.elec_edge
get_optimal_flow(elec_edge)

get_optimal_new_capacity(system::System; scaling::Float64=1.0)

Get the optimal new capacity values for all assets/edges in a system.

Arguments

• system::System: The system containing the assets/edges to analyze
• scaling::Float64: The scaling factor for the results.

Returns

• DataFrame: A dataframe containing the optimal new capacity values for all assets/edges, with missing columns removed

Example

get_optimal_new_capacity(system)
153×8 DataFrame
 Row │ commodity    commodity_subtype  zone           resource_id                        component_id                       type              variable      value  
     │ Symbol       Symbol             Symbol         Symbol                             Symbol                             Symbol            Symbol        Float64
─────┼─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
   1 │ Biomass      capacity           bioherb_SE     SE_BECCS_Electricity_Herb          SE_BECCS_Electricity_Herb_biomas…  BECCSElectricity  new_capacity      0.0
   2 │ Biomass      capacity           bioherb_MIDAT  MIDAT_BECCS_Electricity_Herb       MIDAT_BECCS_Electricity_Herb_bio…  BECCSElectricity  new_capacity      0.0
   3 │ Biomass      capacity           bioherb_NE     NE_BECCS_Electricity_Herb          NE_BECCS_Electricity_Herb_biomas…  BECCSElectricity  new_capacity      0.0

get_optimal_retired_capacity(system::System; scaling::Float64=1.0)

Get the optimal retired capacity values for all assets/edges in a system.

Arguments

• system::System: The system containing the assets/edges to analyze
• scaling::Float64: The scaling factor for the results.

Returns

• DataFrame: A dataframe containing the optimal retired capacity values for all assets/edges, with missing columns removed

Example

get_optimal_retired_capacity(system)
153×8 DataFrame
 Row │ commodity    commodity_subtype  zone           resource_id                        component_id                       type              variable      value    
     │ Symbol       Symbol             Symbol         Symbol                             Symbol                             Symbol            Symbol        Float64  
─────┼─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
   1 │ Biomass      capacity           bioherb_SE     SE_BECCS_Electricity_Herb          SE_BECCS_Electricity_Herb_biomas…  BECCSElectricity  retired_capacity  0.0
   2 │ Biomass      capacity           bioherb_MIDAT  MIDAT_BECCS_Electricity_Herb       MIDAT_BECCS_Electricity_Herb_bio…  BECCSElectricity  retired_capacity  0.0
   3 │ Biomass      capacity           bioherb_NE     NE_BECCS_Electricity_Herb          NE_BECCS_Electricity_Herb_biomas…  BECCSElectricity  retired_capacity  0.0

write_capacity(
    file_path::AbstractString, 
    system::System; 
    scaling::Float64=1.0, 
    drop_cols::Vector{AbstractString}=String[], 
    commodity::Union{AbstractString,Vector{AbstractString},Nothing}=nothing, 
    asset_type::Union{AbstractString,Vector{AbstractString},Nothing}=nothing
)

Write the optimal capacity results for all assets/edges in a system to a file. The extension of the file determines the format of the file. Capacity, NewCapacity, and RetiredCapacity are first concatenated and then written to the file.

Filtering

Results can be filtered by:

• commodity: Specific commodity type(s)
• asset_type: Specific asset type(s)

Pattern Matching

Two types of pattern matching are supported:

1. Parameter-free matching:

   • "ThermalPower" matches any ThermalPower{...} type (i.e. no need to specify parameters inside {})

2. Wildcards using "*":

   • "ThermalPower*" matches ThermalPower{Fuel}, ThermalPowerCCS{Fuel}, etc.
   • "CO2*" matches CO2, CO2Captured, etc.

Arguments

• file_path::AbstractString: The path to the file where the results will be written
• system::System: The system containing the assets/edges to analyze as well as the settings for the output
• scaling::Float64: The scaling factor for the results
• drop_cols::Vector{AbstractString}: Columns to drop from the DataFrame
• commodity::Union{AbstractString,Vector{AbstractString},Nothing}: The commodity to filter by
• asset_type::Union{AbstractString,Vector{AbstractString},Nothing}: The asset type to filter by

Returns

• nothing: The function returns nothing, but writes the results to the file

Example

write_capacity("capacity.csv", system)
# Filter by commodity
write_capacity("capacity.csv", system, commodity="Electricity")
# Filter by commodity and asset type using parameter-free matching
write_capacity("capacity.csv", system, asset_type="ThermalPower")
# Filter by asset type using wildcard matching
write_capacity("capacity.csv", system, asset_type="ThermalPower*")
# Filter by commodity and asset type
write_capacity("capacity.csv", system, commodity="Electricity", asset_type=["ThermalPower", "Battery"])

write_costs(
    file_path::AbstractString, 
    system::System, 
    model::Union{Model,NamedTuple}; 
    scaling::Float64=1.0, 
    drop_cols::Vector{<:AbstractString}=String[]
)

Write the optimal costs for the system to a file. The extension of the file determines the format of the file.

Arguments

• file_path::AbstractString: The path to the file where the results will be written
• system::System: The system containing the assets/edges to analyze as well as the settings for the output
• model::Union{Model,NamedTuple}: The optimal model after the optimization
• scaling::Float64: The scaling factor for the results
• drop_cols::Vector{<:AbstractString}: Columns to drop from the DataFrame

Returns

• nothing: The function returns nothing, but writes the results to the file

write_flow(
    file_path::AbstractString, 
    system::System; 
    scaling::Float64=1.0, 
    drop_cols::Vector{<:AbstractString}=String[],
    commodity::Union{AbstractString,Vector{<:AbstractString},Nothing}=nothing,
    asset_type::Union{AbstractString,Vector{<:AbstractString},Nothing}=nothing
)

Write the optimal flow results for the system to a file. The extension of the file determines the format of the file.

Filtering

Results can be filtered by:

• commodity: Specific commodity type(s)
• asset_type: Specific asset type(s)

Pattern Matching

Two types of pattern matching are supported:

1. Parameter-free matching:

   • "ThermalPower" matches any ThermalPower{...} type (i.e. no need to specify parameters inside {})

2. Wildcards using "*":

   • "ThermalPower*" matches ThermalPower{Fuel}, ThermalPowerCCS{Fuel}, etc.
   • "CO2*" matches CO2, CO2Captured, etc.

Arguments

• file_path::AbstractString: The path to the file where the results will be written
• system::System: The system containing the edges to analyze as well as the settings for the output
• scaling::Float64: The scaling factor for the results
• drop_cols::Vector{<:AbstractString}: Columns to drop from the DataFrame
• commodity::Union{AbstractString,Vector{<:AbstractString},Nothing}: The commodity to filter by
• asset_type::Union{AbstractString,Vector{<:AbstractString},Nothing}: The asset type to filter by

Returns

• nothing: The function returns nothing, but writes the results to the file

Example

write_flow("flow.csv", system)
# Filter by commodity
write_flow("flow.csv", system, commodity="Electricity")
# Filter by commodity and asset type using parameter-free matching
write_flow("flow.csv", system, commodity="Electricity", asset_type="ThermalPower")
# Filter by commodity and asset type using wildcard matching
write_flow("flow.csv", system, commodity="Electricity", asset_type="ThermalPower*")

write_dataframe(
    file_path::AbstractString, 
    df::AbstractDataFrame, 
    drop_cols::Vector{<:AbstractString}=String[]
)

Write a DataFrame to a file in the appropriate format based on file extension. Supported formats: .csv, .csv.gz, .parquet

Arguments

• file_path::AbstractString: Path where to save the file
• df::AbstractDataFrame: DataFrame to write
• drop_cols::Vector{<:AbstractString}: Columns to drop from the DataFrame

write_results(file_path::AbstractString, system::System, model::Model, settings::NamedTuple, period_index::Int64=1)

Collects all the results as a DataFrame and then writes them to disk after the optimization is performed.

Arguments

• file_path::AbstractString: full path of the file to export.
• system::System: The system object containing the case inputs.
• model::Model: The model being optimized.
• period_index::Int64: The index of the period to collect results for (default is 1).
• settings::NamedTuple: The settings for the system, including output configurations.

Returns

Example

write_results(case_path * "results.csv", system, model) # CSV
write_results(case_path * "results.csv.gz", system, model)  # GZIP
write_results(case_path * "results.parquet", system, model) # PARQUET

Write results when using Monolithic as solution algorithm.

Write results when using Myopic as solution algorithm.

Write results when using Benders as solution algorithm.