FREMI (Forecasting Renewable Energy with Machine Intelligence)
This project seeks to increase the accuracy of the current wind turbine forecasting methods and develop and deploy a tool capable of assisting energy traders under the new market rules posed by I-SEM.
€369,830Total Project Costs
2 yrProject Duration
Ireland is arguably considered world leaders in the facilitation of renewables on the grid. The FREMI project brings together the largest developer and operator of renewable generation on the island of Ireland; SSE Airtricity, with leading renowned centre for excellence in advanced data analytics; UCD, CeADAR (Centre for Advanced Data Analytics Research). Through I-SEM the requirement to trade power more intensively and placing a balance responsibility on renewable generators, essentially gives rise to the largest market exposure for SSE of any market participant. FREMI will mitigate this risk through applying advanced data science to enhance the industry's ability to forecast generation and match demand. The significance of 'balance responsibility' cannot be understated, financial exposure is likely to incur significant cost. This places decisive importance on forecasting with highest accuracy. FREMI uses Artificial Intelligence (AI) and will seek to apply state of the art Machine Learning tools to greatly enhance forecasting capabilities. CeADAR involvement will ultimately allow SSE to further optimise its renewable portfolio and with it reduce power prices for the end consumer and achieve even greater levels of decarbonisation. FREMI will take a holistic approach whereby forecasting will not be considered in isolation of plant availability; system demand and localised grid constraints. FREMI will avoid utilities requirement to rapidly respond to alter generation which can be highly inefficient and expensive for energy providers and in turn for the consumer. FREMI can bring the industry closer to maintain a more cost effective and efficient means to participation in I-SEM.
Total Project Cost: €369,830
Funding Agency: SEAI
Year Funded: 2018
Lead Organisation: SSE Airtricity
Partner Organisation(s): University College Dublin
Collaborators: Met Eireann