Our work

Improved wind farm control for optimal performance

Currently, the turbines in commercial wind farms are operated individually, each aiming to maximize its own power production, thereby neglecting the interactions between the wind turbines through their wakes. A significant improvement of the overall power production and loads reduction is achievable when the wind turbines are operating in a coordinated way using wind farm control (also known as Active Wake Control). In the project CL-Windon ECN part of TNO and partners aim to develop highly innovative wind farm control algorithms that achieve an optimized balance between maximization of the yearly power production, lifetime extension and O&M cost reduction, and guarantee proper operation under realistic temporal and spatial variations of the wind resource.

Even though benefits in terms of power production have already been reported in the literature, the state-of-the-art is currently represented by a static open-loop approach in which the turbines’ settings (pitch angles and yaw misalignments) are optimized for fixed wind speeds and directions. In reality, the wind varies both in time (time-variations in the global wind resource) and in space (due to wake effects and local wind conditions), and the wind farm controller needs to adapt its control actions in real-time to optimize the farm operation to the time-varying wake interaction. The ambition is to move the current static, open-loop wind farm control towards dynamic closed-loop control. Dynamic wind farm control will be capable to take into account the variability of the flow (time and spatial variations in the wind resource), as well as model uncertainties, thereby ensuring optimal performance in real-life environment.

Wind tunnel at Politechnico di Milano



The project started in October 2016 and is coordinated by CENER. The consortium consists of a total of 16 partners, including ECN part of TNO, universities, research institutes and industry. The main objectives are:

  • develop dynamic wind farm models suitable for dynamic closed-loop wind farm control;
  • develop dynamic wind farm control algorithms that achieve optimized balance between the selected KPIs in realistic operating conditions (varying wind resource, model uncertainty);
  • develop wind turbine technologies that support the farm controller in achieving its goals;
  • verify the developed farm models and farm controllers by means of wind tunnel and field tests.

Dr Stoyan Kanev

Contact
Email

FOLLOW TNO ON SOCIAL MEDIA

Stay up to date with our latest news, activities and vacancies

We use anonymous cookies to enhance the use of our site. Our privacy statement has been updated to reflect the new EU privacy policy.