Case Study: SSE Energy Solutions lowers carbon emissions and speeds energy optimization with Databricks

Digitally optimizing energy assets for decarbonization and cost savings

SSE Energy Solutions, a renewable-focused energy company, needed a better way to manage increasingly complex energy assets and improve forecasting, optimization, and carbon reduction efforts. Its existing VM-based machine learning workflow was manually intensive, costly, and not sustainable at the scale required for week-ahead optimization.

With Databricks and its lakehouse architecture, SSE Energy Solutions was able to run weekly optimization jobs more efficiently, schedule multiple runs in parallel, and speed up forecasting. Databricks helped cut a demand-forecasting job from a full day to about two hours, reduce time to release, and save internal resources and costs while improving optimization for CHP systems and supporting lower carbon emissions.

SSE Energy Solutions

Rachel Hassall

Head of Data and Analytics