ENGIE and Google Cloud have signed a new partnership for the development of an artificial intelligence-based energy solution to optimize the value of ENGIE’s wind portfolio on the short-term power markets.
ENGIE and Google Cloud’s AI Services and Industry Solutions (AIIS) will team up to combine both expertise in power markets and AI to develop the solution. This project will facilitate transactions for wind asset developers and create benefits for wind power producers.
The key objective of the AI pilot is to predict how much wind power should be sold on which power market and at what price. This is a challenge due to the complexity of the short-term power markets and the unpredictable nature of wind production. In order to tackle this problem, vast amounts of data from various sources needs to be collected, stored and analyzed. The AI solution leverages a performant and scalable data system and advanced machine learning algorithms to extract value from the data that supports subsequent decisions.
“At Google Cloud, we believe that more accurate data and predictions of wind power production will be valuable to electricity grids, creating benefits for consumers and making wind more competitive with fossil fuels,” says Larry Cochrane, director of global energy solutions at Google Cloud. “We are delighted to work with ENGIE on this project, which can accelerate Europe’s clean energy transition, while laying the groundwork for wind farms around the world to benefit from improved forecasting via Artificial Intelligence.”
“ENGIE’s business entity ‘Global Energy Management & Sales’ has been developing its systems in the last decade to cope with the challenges involved in managing renewables assets,” explains Alexandre Cosquer, member of the executive committee of ENGIE’s business entity Global Energy Management & Sales. “With already a double expertise in risk and data management, we were looking to intensify the renewables development, and to partner up with one of the most superior experts not only in data management but also in Machine Learning technology.”
Image: Sam Cumming on Unsplash
