CeADAR and SSE partner to produce new AI tool which predicts energy generation at wind farms.
CeADAR, Ireland’s Centre for Applied AI, has developed a new system which utilises Artificial Intelligence to accurately predict the amount of renewable energy that will be produced at wind farms.
Currently it is not possible to accurately predict the amount of energy that will be generated making the new tool the first of its kind in the renewable energy industry.
This new AI tool was developed during a partnership project, called FREMI (Forecasting Renewable Energy with Machine Intelligence) between CeADAR and Ireland’s largest provider of 100% green energy, 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. The tool created by the project will contribute to save energy at national and European level and in turn to create a greener, decarbonised environment.
It is accurate, scalable, reliable, and maintainable, and has already been deployed and is in use by SSE Airtricity at 21 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.
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.
CeADAR’s Dr Ricardo Simon Carbajo, Principal Investigator on the project, says the solution is ‘beyond state of the art’.
“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. 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.”
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.