AI tool predicts energy generation at wind farms
Researchers from CeADAR, Ireland’s national centre for Applied Data Analytics & AI, have developed a system which uses artificial intelligence to accurately predict the amount of renewable energy that will be produced at wind farms.
The new tool, FREMI (Forecasting Renewable Energy with Machine Intelligence) is a collaborative project between CeADAR and SSE Airtricity.
The €370,000 project took 18 months to complete and was funded by the SEAI National Energy Research Development and Demonstration (RD&D) programme.
FREMI is accurate, scalable, reliable, and maintainable, and has already been deployed 21 SSE Airtricity wind farms around Ireland which are owned and operated by its sister company, SSE Renewables.
FREMI will also allow energy traders to comply with new market rules imposed by the Integrated Single Electricity Market (ISEM), the wholesale electricity market for the island of Ireland. As part of ISEM, renewable energy generators must accurately forecast the energy they generate a day in advance of it generating and going to market.
Renewable energy generators have a large amount of data about the historical operations of their wind farms. This valuable data is combined with forecasts of meteorological conditions to accurately predict wind energy production a day ahead of the energy being generated.
The more accurate the predictions, the less uncertainty in the level of wind energy that will be available to the grid, making this technology more economically competitive and reliable. This in turn helps accelerate the transition to a green energy landscape, by reducing carbon emissions and ultimately reducing the cost of energy.
The project was led by Dr Ricardo Simon Carbajo from CeADAR, and David Noronha, project director at SSE Airtricity and was supported by SSE’s head of energy markets David Graham.
A range of data scientists were involved in the project including Dr David Haughton, Andres Suarez-Cetrulo and Lauren Burnham-King from CeADAR, and Derek Aherne and Noelle Doody from SSE Airtricity.
“This is cutting-edge applied research in deep learning with real application in an energy market setting which provides a real tangible impact to the energy sector, contributing to lower costs of energy and the decarbonisation plan,” said Dr Carbajo said. “Both SSE Airtricity and CeADAR have a close collaborative relationship and are looking to develop further projects in this area, specifically now due to the importance of the European Green Deal and the fast adoption of renewable energy.”
David Noronha, Project Director at SSE Airtricity, said: “At SSE Airtricity, we’ve a proud history of collaboration with CeADAR and this latest project is another great example of how energy companies can benefit from applied data and AI. FREMI has helped us to take another big step towards meeting our goal of net-zero by 2050 and will also have added benefits for the entire energy chain, including customers.”
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