EOLES-ResIRF Coupling

The EOLES-ResIRF Coupling model is a tool for studying integrated decarbonization pathways for the residential sector. It relies on coupling Res-IRF4, a technically- and behaviorally-rich model of household energy demand in France, and EOLES, a technology-explicit model of the French energy system. The coupling framework can be used in two different ways. First, it can be used to test exogenous policy portfolio assumptions in the residential sector. Second, it can be used to optimize the value of energy efficiency subsidies, in combination with the energy system.

Installation

Step 1: Git clone the folder in your computer.

git clone https://github.com/celiaescribe/eoles2.git

Step 2: Create a conda environment from the environment.yml file:

• The environment.yml file is in the eoles2 folder.
• Use the terminal and go to the eoles2 folder stored on your computer.
• Type the following command:

conda env create -f env.yml

Note that this step may take a few minutes, as the pyomo package takes time to install.

Step 3: Activate the conda environment:

conda activate eoles

Getting started

Step 1: Installing ResIRF

The coupling requires to have installed the package Res-IRF as well in your environment. To do so, first refer to the Res-IRF project to clone the project in your own computer. Then, go to the corresponding folder, and run the following command (make sure that the eoles environment is activated)

pip install -e .

This allows you to have access to all the functionalities from ResIRF in your environment.

Step 2: Install a solver

Our package relies on the Gurobi solver, used through the pyomo interface. This requires dowloading Gurobi and installing a license. It is also possible to rely on open-source solvers such as CPLEX.

Step 3: Running the coupling

The standard way to run the coupling is to launch the script main_coupling_resirf.py. This requires providing the configurations which you want to run. Examples of configurations can be found in eoles/inputs/xps. Files called base.json provide general configuration parameters. Other json files in a given folder provide specifications for varying configurations. For example, the file eoles/inputs/xps/20231205/biogasS2_capacityN1_demandReference_policyambition.json specifies different parameters for biogas potential, renewable potential, demand scenario and residential policies scenario.

You can run the script as follows:

python main_coupling_resirf.py --cpu 1 --configdir "eoles/inputs/xps/20231205

It is possible to create a folder with different configurations using the scenarios_creation.ipynb notebook.

The command specifies the configuration to use. There are two ways to specify that:

• --configdir "eoles/inputs/xps/20231205: the folder where the configurations are stored
• --configfile: the name of the configuration file to run if you do not want to run all configurations in a given folder (ex: eoles/inputs/xps/20231205/biogasS3_capacityN1_demandReference_policyreference.json)

Note that other parameters are allowed:

• --cpu 1: the number of CPUs to use
• --patterns: specify patterns to select configurations (default: "*.json")
• --exclude-patterns: specify patterns to exclude configurations (default: "base.json")

Step 3: explore outputs

Output files are stored in eoles/outputs.

Results

Lucas Vivier, & Célia Escribe. (2023). Result from How to allocate mitigation efforts between home insulation, fuel switch and fuel decarbonization? Insights from the French residential sector. [Data set]. Zenodo.

Contributing

The development of the EOLES model was initiated by Behrang Shirizadeh and Philippe Quirion. The development of the Res-IRF package was originated by Louis-Gaëtan Giraudet. We rely on the latest version of Res-IRF, developed by Lucas Vivier. The coupling of the two models was developed by Célia Escribe and Lucas Vivier.