Fleet-based Artificial Intelligence for Fault Detection and Maintenance Optimisation for Offshore Wind Farms (BitWind)

You are here


Fleet-based data analytics, maintenance optimisation, offshore wind energie

Project Description 

Wind power is one of the fastest growing renewable energy sources, and investments in wind energy are expected to grow considerably in the next decades. Giant wind turbines with capacities of 20 MW will be put into service by 2020 and are an absolute necessity for tackling climate change, a topic which is high on the agenda of all EU countries.

In order to remain competitive with other sources of electricity generation, offshore wind energy needs to bring down the associated costs significantly. This not only includes the upfront investment costs related to the planning, financing, manufacturing and installation of offshore wind farms but also their operation and maintenance (O&M) costs (operational costs count for 25% of the costs of electricity from offshore wind).

BitWind aims at developing novel artificial intelligence techniques on data of operational offshore wind farms. The use case focus is on automatic performance degradation detection and prognosis of the expected lifetime of components. These innovations should lead to new services and a strategic cost reduction for the existing and new concessions in Belgium. 

Project partners


Project details

October 2018 - December 2021

With the support of 

Screen Shot 2018-10-15 at 13.51.48.png