WindAI is a wind analysis and predictor tool to aid offshore wind farms in reducing maintenance costs without reducing output performance. Offshore wind farms are in an environment of high-velocity winds. When a turbine adjusts to wind movements, it does so by reacting to change. These adjustments can create pressure on turbine mechanisms resulting in more maintenance costs. WindAI solves this problem by using EO data to make predictions on wind patterns. WindAI then optimises adjustments made to the turbine using in-turbine data references. Machine learning is used to ensure that the optimised adjustments do not affect the performance output of the turbine to increase the overall profitability of the wind farm. WindAI uses Sentinel 4 and 5 data, which support the climate change and atmospheric monitoring data services. New offshore wind instalments for EU in 2017 reached EUR 22.3 billion.

WindAI – Wind farm overview and turbine details section, © WindAI Ltd.


Customer benefits

Offshore wind farm owners are able to optimise their maintenance costs through selected and refined turbine adjustments. WindAI will ensure that the regulatory and contractual agreements are met through the system by reporting all analysis captured. Overall, WindAI aims to increase the overall profitability of the wind farm.



“By combining a range of different data sets and Artificial Intelligence, WindAI are developing a ground-breaking solution that will improve the efficiency of renewable wind energy by optimising wind pattern predictions. Our judges found this idea innovative in its visualisation and usability and considered it a novel use case for Copernicus data. They were also impressed by the potential
environmental impacts and improvements that the solution could bring, enabling us to move towards a more sustainable world.” – Sam Adlen, Chief Strategy Officer, Satellite Applications Catapult


Daniel O’Connell, Jeremy Gondolf