EnergyScope Python Library

This section provides a learning-oriented guide to the Python library that interfaces with the EnergyScope model. It includes hands-on tutorials and code examples to help you understand, modify, and extend the model in a programmatic way.

The tutorials are provided as Jupyter notebooks and cover essential tasks such as running the model, choosing datasets, running multiple scenarios, analyzing uncertainty, and adding custom technologies.

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📘 Tutorials

1. Basic Run — Minimal working example to run the model.
2. Choose Datasets — Select and customize input datasets.
3. Multiple Runs — Automate batch simulations.
4. Uncertainty Analysis — Explore parameter sensitivity and scenario uncertainty.
5. Add a New Technology — Extend the model with custom technologies.

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📚 Reference Documentation

• Parameters, variables, sets
• Technologies

These resources provide detailed descriptions of the mathematical and data structures that drive the EnergyScope model.