OnSSET is a bottom-up optimization energy modelling tool that estimates, analyzes, and visualizes the most cost-effective electrification strategy. It incorporates spatially explicit characteristics related to energy — including population density and distribution, proximity to transmission and road networks, nighttime lights, and local renewable energy potential.

OnSSET focuses on assessing and deploying conventional and renewable energy technologies to ensure access to affordable, reliable, sustainable, and modern energy for all.

OnSSET is designed to complement existing energy planning models that do not consider geographical characteristics related to energy. It provides invaluable support to policymakers and decision makers seeking least-cost electrification strategies.

Electrification planning is often dominated by proprietary analytical tools. OnSSET’s open-source and modular structure allows users to build and modify the code according to their own data and requirements, enabling rapid, cost-effective electrification plans. It reduces computational and data needs compared to many existing resource-intensive planning tools.

The model is used extensively by academia, international organizations, and government institutions for electrification planning, policy formulation, and research.

OnSSET provides spatially explicit least-cost electrification options for a given geography, including grid extensions, mini-grids, and standalone systems. It also estimates required investments and newly installed power generation capacity.

The OnSSET manual is available on ReadTheDocs. It provides installation guidance, functional descriptions, and a full walkthrough of geospatial electrification analysis—from GIS preprocessing to running the model and visualizing results.

The OnSSET codebase is written in Python and hosted on GitHub, where anyone can download, use, and contribute to its ongoing development. Contributions, feature requests, and collaboration are encouraged through the OnSSET GitHub repository.