Elia Energy Forecast

The context

Elia Group operates high-voltage electricity transmission in Belgium and Germany — a project closely followed by the European Commission given its impact on continental grid stability. The challenge: automatically forecasting, via machine learning, energy loss on high-voltage lines (cable wear, weather conditions…) to adjust the power to inject the next day — and hold that commitment down to the megawatt, with no multi-percent margin. The payoff: more certainty for downstream energy suppliers and a more stable grid.

My mission

As Lead Developer .NET, I owned the platform that connects and orchestrates every service in the project: daily data retrieval from a remote datalake, sending it to the machine learning service, retrieving and formatting the forecasts, visualisation (historical vs. forecast, deviations) and automated notifications — all within a strictly-run, English-speaking environment, working closely with the project’s architect.

For professional confidentiality specific to this strategic project, certain details (models, data, precise mechanics) are deliberately not covered here.

What to remember

A highly visible project — followed by the European Commission — at the crossroads of machine learning and modern .NET architecture (Blazor, microservices, DDD, CQRS), with a real energy reliability stake spanning two countries.