Demand Forecasting
Harnessing AI to help the UK predict demand
We’re developing a state-of-the-art, automated forecasting system powered by machine learning to support the UK’s National Energy Grid Distributor (NGED).
As we transition to a cleaner, renewable energy system, sources of power are becoming smaller and increasingly distributed across the UK. Rooftop solar, electric vehicles and other forms of de-centralised sources make it much more difficult for System Operators to predict electricity demand and ensure everyone's lights stay on.
Working with NGED, we our employing our industry knowledge and leading engineering talent to We are approaching this challenge with an innovative dual-track approach.
The final output of the project will be a robust, operational API-based forecast providing probabilistic predictions for all of NGED’s 1161 primary substations up to 14 days ahead. With this result, NGED will be able to manage grid constraints more effectively, reducing operational costs, and enhancing the UK’s network stability.
Live Service Track
In the first 12 months, we will deliver an operational service of our demand forecast for a pilot group of substations.
Research Track
Our experts will explore novel machine learning techniques to solve the complex problems that industry currently faces when forecasting demand.
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