config.yml

# Determine the model configuration

# 1) Set overall workflow control parameters
control_parameters:
    rolling_horizon: False
    aggregate_input: False
    countries: ['AT', 'BE', 'CH', 'CZ', 'DE', 'DK1', 'DK2', 'FR', 'NL',
                'NO1', 'NO2', 'NO3', 'NO4', 'NO5', 'PL',
                'SE1', 'SE2', 'SE3', 'SE4', 'IT']
    solver: "gurobi"
    solver_commandline_options: False
    fuel_cost_pathway: "NZE"
    emissions_cost_pathway: "long-term"
    activate_emissions_limit: False
    emissions_pathway: "100_percent_linear"
    activate_demand_response: True
    demand_response_approach: "DLR"
    demand_response_scenario: "50"
    eeg_clusters_per_technology: 20
    save_updated_market_values: True
    save_production_results: True
    save_price_results: True
    write_lp_file: False

# 2) Set model optimization time and frequency
time_parameters:
    start_time: "2030-01-01 00:00:00"
    end_time: "2030-01-02 23:00:00"
    freq: "60min"

# 3) Set input and output data paths
input_output_parameters:
    path_folder_input: "../inputs/"
    path_folder_output: "../results/"

# 4) Set rolling horizon parameters (optional)
rolling_horizon_parameters:
    time_slice_length_wo_overlap_in_hours: 24
    overlap_in_hours: 12

# 5) Set solver command line options (optional)
solver_cmdline_options:
    lpmethod: 4
    preprocessing dual: -1
    solutiontype: 2
    threads: 12
    barrier convergetol: 1.0e-6