Wind farm power optimization via yaw angle control: A wind tunnel study

Bastankhah, Majid; Porté-Agel, Fernando

Abstract

Yaw angle control is known nowadays as a promising and effective technique to mitigate wake effects in wind farms. In this paper, we perform wind tunnel experiments to study the performance of a model wind farm with five turbine rows under a wide variety of yaw angle distributions. Electrical servo controllers are used to monitor and control the operating conditions of each model wind turbine, which consists of a recently developed, highly efficient rotor with a diameter of 15 cm. Each turbine is used as a sensor to detect its own inflow conditions. Using this method ensures us that all the turbines within the wind farm always operate with an optimal rotational velocity, regardless of their yaw angles or inflow conditions. Wind farm power measurements are carried out for more than 200 cases with different yaw angle distributions. Our results show that yaw angle control can increase the overall wind farm efficiency as much as 17% with respect to fully non-yawed conditions. Special emphasis is placed on studying yaw angle distributions with different levels of simplicity and power improvement. Among different yaw angle distributions, the most successful ones are those with a relatively large yaw angle value for the first turbine row, and then, the yaw angle decreases progressively for downwind rows until it eventually becomes zero for the last one. In addition, power measurements show that yaw angle control can improve the wind farm efficiency more noticeably for a larger number of turbine rows although this improvement is expected to reach a plateau after several rows.

Citation

Bastankhah, M., & Porté-Agel, F. (2019). Wind farm power optimization via yaw angle control: A wind tunnel study. Journal of Renewable and Sustainable Energy, 11(2), Article 023301. https://doi.org/10.1063/1.5077038

• Journal Article Type: Article
• Acceptance Date: Feb 2, 2019
• Online Publication Date: Mar 8, 2019
• Publication Date: Mar 31, 2019
• Deposit Date: Mar 11, 2019
• Publicly Available Date: Mar 8, 2020
• Journal: Journal of Renewable and Sustainable Energy
• Electronic ISSN: 1941-7012
• Publisher: American Institute of Physics
• Peer Reviewed: Peer Reviewed
• Volume: 11
• Issue: 2
• Article Number: 023301
• DOI: https://doi.org/10.1063/1.5077038
• Public URL: https://durham-repository.worktribe.com/output/1306533