ARTIFICIAL intelligence (AI) is being used to improve the accuracy of forecasts needed to run electricity networks.

Glasgow-based technology firm Smarter Grid Solutions (SGS) used two forms of AI to help predict demand and generation in the Electricity Flexibility and Forecasting System (EFFS) project for Western Power Distribution, headquartered in Bristol.

SGS used two techniques known as “long short-term memory” and “extreme gradient boosting” (XGBoost) to make its predictions, which were more effective than the most commonly used load forecasting tool, and techniques used in recent network innovation projects.

The results will be of interest to all other distribution network operators, but particularly to Scottish Power Energy Network’s FUSION project and Scottish and Southern Electricity Network’s TRANSITION project, which are also examining forecasting methods.

They are investigating whether the work for EFFS can be used within their own projects, reducing costs and providing better value for money. SGS’s project used open-source tools to allow the results to be used without the restriction of having to buy proprietary software licences.

Dr Graham Ault, executive director and co-founder of SGS, said: “The results from our forecasting models were very good, especially for the shorter timeframes. The accuracy levels achieved outperformed known forecasting methods used on other recent innovation projects, so these results are really pushing the industry forward.

“XGBoost performed very well and outperformed the other methods in most test cases and applications ... The ‘how to guide’ style of project report and the open source tools will help other companies to embrace the outcomes of this work quickly and then allow them to contribute to this and other important components of flexibility services and the tools required for the wider DSO transition.”

Jenny Woodruff, EFFS project manager at Western Power Distribution, added: “Being able to accurately forecast demand and generation will enable us to identify where and when our network will need flexibility services.

“The more accurate the forecasting, the more efficiently we can purchase and dispatch these services.”