Decoupled Workflow for Global Sensitivity Analysis Using the Morris Method

[Timon-R]

Changes proposed in this Pull Request

This pull request introduces a generic global sensitivity analysis (GSA) workflow for PyPSA-Eur. It includes a template configuration file (GSA.default.yaml), a script to generate scenario files with parameter samples (prepare_GSA.py), and a script to extract results from completed runs (get_GSA_results.py). The workflow supports the Morris method from SALib and allows users to define uncertain parameters and key output metrics via a YAML interface. It is fully decoupled from the Snakemake pipeline, enabling efficient parameter sampling, result extraction, and later analysis.
Usage instructions are included directly in the GSA.default.yaml file to guide users through setup and execution.

See the SALib documentation for more information on the Morris Method and Global Sensitivity Analysis.

Checklist

• I tested my contribution locally and it works as intended.
• Code and workflow changes are sufficiently documented.
• Changed dependencies are added to envs/environment.yaml. - Only dependency is SALib that can be installed in a separate env
• Changes in configuration options are added in config/config.default.yaml.
• Changes in configuration options are documented in doc/configtables/*.csv.
• Sources of newly added data are documented in doc/data_sources.rst.
• A release note doc/release_notes.rst is added.

[fneum]

Dear @Timon-R; at the moment we need to consolidate the code base and functionality of PyPSA-Eur a bit. And as a first step we would want a more generic PyPSA feature for sampling / GSA (similar to MGA functionality).