ON PACE: Oracle for Negating Progressive Ageing by Curtailment Events

ON PACE investigates how frequent start-stop cycles affect wear in offshore wind turbines and develops insights to extend component lifetime and improve operational reliability.

Centre of Expertise Digital Operations & Finance

windmolens

Offshore wind turbines are being temporarily shut down with increasing frequency. This is due to factors like negative electricity prices, an overloaded electricity grid, storms or environmental measures. These more frequent start-up and shut-down times cause greater wear and tear on important parts, such as bearings and drivetrains. Wind turbines were not originally designed for this. Bearings, in particular, are vulnerable and account for a large proportion of breakdowns and maintenance costs. The ON PACE project investigates how this wear and tear occurs and how the service life of offshore wind turbines can be extended.

Target group 

Managers and operators of offshore wind farms, and companies involved in the monitoring, maintenance and asset management of wind turbines.

Research

The Hague University of Applied Sciences and Sensing360 are conducting research into the impact of start-up and shut-down times on service life of wind turbines. Sensor measurements on offshore wind turbines, together with laboratory tests, form the basis for this research. Using these data, the researchers are developing a digital copy (digital twin) of a wind turbine. This makes it possible to run simulations for different scenarios to predict wear and tear more accurately. These insights form the basis for smart models and a dashboard that helps operators make maintenance decisions.

Intended outcomes

To gain a better understanding of the consequences of frequently shutting down wind turbines. By monitoring wear and tear more accurately and planning maintenance more effectively, the researchers expect to be able to extend the service life of offshore wind turbines by five to ten per cent. ON PACE ultimately results in a practical decision-support system that enables wind farm operators to make better-informed decisions. This leads to lower maintenance costs, fewer unexpected breakdowns, and longer operational availability of existing wind farms.

Duration

September 2025 to August 2027

Partner 

Sensing360

Funding 

Topsector Energie

HBO degree programmes involved

Mechanical Engineering, Electrical Engineering, Engineering Physics and Applied Data Science

Team