EPM Folder structure#

The following structure outlines the key components of the EPM repository:

EPM/
│
├── input/                          # Contains input data files required for the model
│   ├── data_eapp/                  # Input data specific to the EAPP region
       ├── config.csv                  # Configuration settings for input processing
│   ├── data_gambia/                # Input data specific to Gambia
       ├── config.csv                  # Configuration settings for input processing
│   ├── data_test_region/           # Input data specific to the SAPP region
       ├── config.csv                  # Configuration settings for input processing
│   
│
├── postprocessing/                 # Scripts and tools for processing and analyzing model outputs
│   ├── static/                     # Static resources used in post-processing
│   └── utils.py                    # Utility functions for post-processing tasks
│
├── engine_base.gms                 # Defines engine run
├── base.gms                        # Specifies base configurations and parameters
├── cplex.opt                       # Options for the CPLEX solver
├── credentials_engine.json         # Stores credentials for engine access
├── generate_demand.gms             # Script for generating demand data
├── generate_report.gms             # Generates reports from model outputs
├── input_readers.gms               # Handles reading and importing input data
├── input_treatment.gms             # Processes and treats input data
├── input_verification.gms          # Verifies the integrity of input data
├── main.gms                        # Main script orchestrating execution
├── output_verification.gms         # Verifies and validates model outputs
└── run_epm.py                      # Python script to execute the model

1. Input folder#

The input/ directory contains all the necessary data and configuration files required to run the model. It is structured into:

General configuration files#

  • config.csv: Defines global configuration parameters for the model.

  • scenarios.csv: Specifies different scenario configurations that can be run.

Data folders#

The model input data is organized into data/ folders. For example, data_eapp/ contains input data for the Eastern Africa Power Pool and data_gambia/ contains input data specific to Gambia.

Each of these folders contains CSV files grouped by data type, including:

  • constraint/: Defines various constraints applied in the model.

  • h2/: Includes hydrogen-related data.

  • load/: Contains electricity demand and load profiles.

  • reserve/: Specifies reserve requirements for system reliability.

  • resources/: Contains information on energy resources and availability.

  • supply/: Defines supply-side parameters, including power plants and generation capacity.

  • trade/: Contains parameters related to cross-border electricity trade.

Some files are located directly in the data/ directory and contain key parameters that are not grouped within a specific subdirectory:

  • pHours.csv: Defines the hourly resolution of the model.

  • pSettings.csv: Contains general model settings and configuration values.

  • y.csv: Defines the time horizon for the simulation.

  • zcmap.csv: Provides zone and country mapping.

A more detailed description of these parameters and their contents is provided in the Input section.

2. Post-processing folder#

The postprocessing/ directory contains scripts and data files used to process and visualize the model outputs.

  • utils.py: The core Python package for post-processing results. It includes functions for generating various graphs and visualizations. The functions available in this package are detailed in the Post-Processing section.

  • static/: Contains CSV files that define characteristics for visualizations, such as:

    • Color schemes

    • Fuel names and mappings

    • Other parameters for customizing plots

For more details on the available functions and configuration options, refer to the Postprocessing section.

3. GAMS model files#

These files define and execute the core GAMS model:

  • main.gms: The main file that runs the model.

  • base.gms: Defines the fundamental model structure.

  • Engine_Base.gms: Used when running the model via GAMS Engine.

  • generate_demand.gms: Generates demand scenarios.

  • generate_report.gms: Creates summary reports from simulation results.

  • input_readers.gms: Reads and formats input files.

  • input_treatment.gms: Processes input data before execution.

  • input_verification.gms: Checks input data consistency.

  • output_verification.gms: Validates model outputs.

4. Solver configuration#

  • cplex.opt: Defines solver settings for CPLEX.

5. Execution scripts#

  • run_epm.py: Python script to launch EPM from a command line or an external script.

6. Output folder#

The output/ directory is not present initially but is generated automatically when simulations are run. Results are stored in subdirectories following this pattern: output/scenario_name/simulations_run_date_hour