What if algorithms could help the UK’s grid get on track for zero-carbon electricity periods by 2025?
National Grid ESO has announced a new partnership with the Smith Institute to develop a new approach to forecasting day-ahead reserve requirements.
Reserve is the backup power the electricity system needs at times to meet demand.
Currently, ESO sets reserve levels that vary according to electricity demand seen at different times.
These levels are informed by historical generation and adjusted by forecast renewable generation output.
The Smith Institute will develop a machine learning model which will use variables such as temperature and wind forecast data to create more accurate predictions.
The technology will be designed to help National Grid ESO discover potential uncertainties in its forecasting data and set reserve levels more accurately.
The model is forecast to limit the need to keep fossil fuel plants running as backup, reducing carbon dioxide emissions and reducing energy costs.
Isabelle Haigh, Head of National Control for National Grid ESO, said: “As more clean energy connects to Britain’s electricity system, the network is becoming more challenging to operate.
“The more confidence and certainty we have in our forecasts, the more efficiently and securely we’ll be able to balance the country’s supply and demand day to day, minute by minute. Innovative developments like this are crucial if we’re to realise our zero-carbon ambition.”
Rachael Warrington, Executive Mathematical Consultant at the Smith Institute, said: “I’m really excited to be part of creating a new approach that could make a big difference in the energy industry. The way it could help ESO move towards carbon net zero is also a real motivation.”