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.extremum seeking control, log-of-power feedback, model-free wind farm power maximization, wake steering, wind tunnel experiment, yaw control * | INTRODUCTIONComplex wake interactions in wind farms can lead to significant power losses, which reduce the annual energy production (AEP) and revenue. 1,2 Wake steering using nacelle yaw angle control solutions have been proposed to reduce power losses in waked conditions. [3][4][5] The idea is to introduce an intentional yaw misalignment between the turbine rotor and the incoming wind direction, which can deflect the wake laterally by an amount depending on the yaw misalignment. [6][7][8][9] Using this idea on the upstream turbines one can steer their wakes away from the trailing turbines and hence avoid or mitigate wake interactions, leading to an overall increase in power.In this approach, the overall wind farm power is increased by decreasing the power capture of selected upstream turbines, which in turn would increase the power capture of downstream turbines. 10 The output power of the downstream turbines would increase because of the lateral maneuvering of the incoming wake. However, the power of the upstream turbines, that is, intentionally yawed turbines, will decrease as only the

Impact of yaw misalignment on turbine loads in the presence of wind farm blockage

“…Several strategies have been proposed to reduce wake interaction and maximize power production 1,2 ; a review is presented in Kheirabadi and Nagamune 3 and Andersson et al 4 Among them, wake steering by yaw control, that is, the intentional application of yaw misalignment to upstream turbines, has been shown to be a promising technique to increase the power production of arrays of aligned turbines 5 and of wind farms. [6][7][8][9][10][11] The power production of the yawed turbines decreases, but their wakes are steered away from the downstream turbines, which increase their power production. As a result, depending on the atmospheric conditions and the turbine spacing, the cumulative power production of the turbine array increases.…”

“…In order to maximize the power production of a wind farm, the wake interaction among the wind turbines must be minimized. Several strategies have been proposed to reduce wake interaction and maximize power production 1,2 ; a review is presented in Kheirabadi and Nagamune 3 and Andersson et al 4 Among them, wake steering by yaw control, that is, the intentional application of yaw misalignment to upstream turbines, has been shown to be a promising technique to increase the power production of arrays of aligned turbines 5 and of wind farms 6–11 . The power production of the yawed turbines decreases, but their wakes are steered away from the downstream turbines, which increase their power production.…”

Multi-row extremum seeking for wind farm power maximization

“…In the current study, we perform multi-row wind farm power optimization through a feedback real-time yaw optimization strategy dubbed the Log-of-power proportional-integral extremum seeking control (LP-PIESC). In [10], the authors conducted wind tunnel experiments with extremum seeking control assuming that only a single row of turbines (the most upstream row) can change its yaw angle to perform wake steering. In the current work, we extend the IOP Publishing doi:10.1088/1742-6596/2767/3/032043 2 approach in [10] to the case when turbines in inner rows within the wind farm can also perform wake steering by yaw control.…”

“…In [10], the authors conducted wind tunnel experiments with extremum seeking control assuming that only a single row of turbines (the most upstream row) can change its yaw angle to perform wake steering. In the current work, we extend the IOP Publishing doi:10.1088/1742-6596/2767/3/032043 2 approach in [10] to the case when turbines in inner rows within the wind farm can also perform wake steering by yaw control.…”

Dynamic wind farm flow control using free-vortex wake models

“…The latter attempts to synthesise control signals directly from measurements of the wind farm. In wind tunnel experiments, a closed-loop, model-free yaw controller (Campagnolo et al, 2016) and extremum-seeking control (Kumar et al, 2023) have been demonstrated to produce power gains from wake steering under steady flow conditions. Extremum-seeking control has also been demonstrated in large-eddy simulation (LES) (Ciri et al, 2017).…”