🛠️ OnSSET

OnSSET is a Geographic Information Systems (GIS)-based electrification planning tool developed to assess the least-cost pathways for universal electricity access. It models spatially explicit scenarios that combine population distribution, infrastructure, and renewable energy data to suggest the most economical electrification options for each settlement. The tool supports both centralized grid extension and decentralized off-grid solutions over medium- and long-term timeframes.

OnSSET is composed of:

• A Python-based modeling core that performs scenario simulations and optimization
• A QGIS plugin suite that helps preprocess spatial data and generate model inputs
• Output CSV files that describe settlement-level electrification strategies and cost metrics
• Visualization tools that help explore, map, and compare results across scenarios

📄 Documentation

Here you will find everything to install and run OnSSET:

Installation Guide for OnSSET This PDF document includes:

• An installation guide for Windows, Linux, and macOS
• How to set up a Python virtual environment and install required libraries
• Instructions for installing QGIS and OnSSET plugins
• Links to the official OnSSET GitHub repository and documentation

Data Configuration Guide for OnSSET This PDF explains:

• How to prepare population clusters and spatial input layers (e.g. roads, grids, solar, wind, nightlights)
• Recommended data sources for GIS layers
• Step-by-step guide to configure the CountrySpecs.xlsx file
• How to define scenario parameters in Python scripts

Output Files in OnSSET This PDF includes:

• Explanation of the different types of output files generated by OnSSET
• Scenario naming conventions and file structures
• Description of how to interpret electrification results and cost metrics
• Linkage with OpenModAfrica scenario naming standards

Description of Output Columns This PDF contains:

• A detailed list of all output columns from OnSSET’s CSV result files
• Units and definitions for each variable (e.g. population, demand, LCOE, investment, distance to grid)
• Guidance on how to interpret values related to demand tiers, grid status, and technology choices

Maps Output Guide This PDF shows:

• How to load and visualize OnSSET outputs in QGIS or ArcGIS
• Steps to create point maps from CSV output
• How to classify, symbolize, and export maps for reporting and presentation

🎥 Step-by-step Video Support

You can find all tutorials on

💡 Additional support

Install OnSSET

To install OnSSET:

• Use the Installation Guide
• Clone the repo from: https://github.com/OnSSET/onsset
• Install dependencies:
  • pip install -e .
  • pip install numpy pandas geopandas matplotlib scikit-learn
• Install QGIS and OnSSET plugins:
  • Population Clustering Plugin
  • GEP Plugin

Run OnSSET

1. Prepare input data layers and CountrySpecs.xlsx
2. Define scenario parameters in runner.py
3. Run the model: python runner.py

❓ Need Help?

Check our Questions & Answers page for common issues and guidance.

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References:
Official repo: https://github.com/OnSSET/onsset
Documentation: https://onsset.readthedocs.io/