PyPSA Basic Training

🎯 This repository contains introductory PyPSA exercises for working with PyPSA basic components to build long-term energy system scenarios (LTES).

Repository Contents

• day1/: Introductory notebooks on single-region systems, storage, and links
• day2/: Notebooks on CO2 management and direct air capture
• data/: Input datasets used in the exercises
• envs/: Conda environment files and pip requirements

🏗️ Getting Started

1) Clone the repository

The local path must not contain spaces.

git clone https://github.com/agoenergy/pypsa-basic-training.git
cd pypsa-basic-training

If needed, install Git first: https://git-scm.com/book/en/v2/Getting-Started-Installing-Git

2) Install Conda

Install Miniconda (recommended) or Anaconda:

• Miniconda: https://docs.conda.io/en/latest/miniconda.html
• Conda install guide: https://docs.conda.io/projects/conda/en/latest/user-guide/install/

3) Create an environment

If you are also doing the PyPSA-SPICE training, install the full environment (envs/environment.yml). You can then use the same environment for both trainings.

# Use this if you also work with PyPSA-SPICE
conda env create -f envs/environment.yml
conda activate hotpot

If you only want to work with these basic training exercises, use the lightweight environment (envs/environment_light.yml).

# Use this for PyPSA basic training only
conda env create -f envs/environment_light.yml
conda activate hotpot-light

4) Start JupyterLab

jupyter lab

Open the notebooks in day1/ and day2/ to begin the training.

Notes

• The full environment includes additional tooling and optional solver integrations.
• If environment creation fails, update Conda and retry:

conda update -n base -c conda-forge conda

Resources

• Training materials: https://cloud.sefep.eu/s/dij8QnG7D5e6egd
• PyPSA documentation: https://docs.pypsa.org/latest/