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Abstract This paper presents results from wind tunnel experiments to evaluate power gains from wake steering via yaw control. An experimental scaled wind farm with 12 turbines in an aligned rectangular array is used. Wake steering is performed by yawing turbines using a closed-loop algorithm termed the Log-of-Power Proportional Integral Extremum Seeking Control (LP-PIESC). Two configurations are considered. In the first configuration, the turbines in the first two upstream rows are controlled. In the second case, yaw control is applied to the turbines in the first upstream row and the third row. For both cases, uncontrolled turbines have no yaw misalignment. The results show that by independent parallel maximization of the power sum of a reduced number of turbines, it is possible to obtain a close approximation of the true maximum power. The data shows that the LP-PIESC algorithm can converge relatively fast compared to traditional ESC algorithms.
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Wind plant power maximization via extremum seeking yaw control: A wind tunnel experiment
Abstract This work describes the results from wind tunnel experiments performed to maximize wind plant total power output using wake steering via closed loop yaw angle control. The experimental wind plant consists of nine turbines arranged in two different layouts; both are two dimensional arrays and differ in the positioning of the individual turbines. Two algorithms are implemented to maximize wind plant power: Log‐of‐Power Extremum Seeking Control (LP‐ESC) and Log‐of‐Power Proportional Integral Extremum Seeking Control (LP‐PIESC). These algorithms command the yaw angles of the turbines in the upstream row. The results demonstrate that the algorithms can find the optimal yaw angles that maximize total power output. The LP‐PIESC reached the optimal yaw angles much faster than the LP‐ESC. The sensitivity of the LP‐PIESC to variations in free stream wind speed and initial yaw angles is studied to demonstrate robustness to variations in wind speed and unknown yaw misalignment.
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- Award ID(s):
- 1916776
- PAR ID:
- 10395468
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Wind Energy
- Volume:
- 26
- Issue:
- 3
- ISSN:
- 1095-4244
- Page Range / eLocation ID:
- p. 283-309
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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