ESM Python Nairobi

Welcome to the ESM Python Nairobi repository! This repository contains resources, and documentation related to Energy System Modelling (ESM) using Python, with a focus on the PyPSA (Python for Power System Analysis) library. These materials were used for the ESM Python Nairobi session.

Directory Structure

• docs/ - Detailed write-ups, slides, and additional resources.
• notebooks/ - Jupyter Notebooks with live examples and tutorials.
  • tutorials/ - Step-by-step guides covering PyPSA fundamentals and applications.
• images/ - Screenshots, event photos, and diagrams used in documentation or notebooks.

Tutorials Overview

The notebooks/tutorials/ directory contains the following guides:

1. 01_getting_started.ipynb: Introduces PyPSA, basic network creation, components, power flow, and visualization.
2. 02_components_basics.ipynb: Covers the core PyPSA components (Bus, Generator, Load, Line, Store, etc.) and their configuration.
3. 03_network_visualization.ipynb: Demonstrates static and interactive network plotting, including geographic maps with cartopy.
4. 04_basic_optimization.ipynb: Explains different optimization types: Power Flow (PF), Linear Optimal Power Flow (LOPF), and Investment Optimization.
5. 05_investment_planning.ipynb: Details multi-period investment planning, costs, discount rates, and capacity expansion.
6. 06_storage_and_balancing.ipynb: Focuses on modelling various storage types (electrical, thermal, hydrogen) and demand-side management.
7. 07_sector_coupling.ipynb: Covers integrating power, heat, transport demand, and hydrogen sectors using coupling technologies.
8. 08_diy_solar_simulation.ipynb: A practical example modelling a small Solar Home System (SHS) with PV and battery.

Getting Started

1. Clone the repository:

   git clone https://github.com/tinegachris/ESM-Python-Nairobi.git
   cd ESM-Python-Nairobi

2. Install dependencies: Ensure you have Python installed. Then, install the required packages using pip:

   pip install -r requirements.txt

3. Run the notebooks: Navigate to the notebooks/tutorials/ directory and launch Jupyter Lab or Jupyter Notebook:

   jupyter notebook

   Then open the desired .ipynb file to start exploring.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit pull requests or open issues.

Questions?

If you have questions about the materials, feel free to raise an issue in this repository.