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Improved Adaptive Torque Control for Wind Turbine Considering Varying Turbulence Conditions
Author:
Affiliation:

1.Jiangsu Goldwind Science & Technology Co., Ltd., Yancheng 224100, China;2.School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China;3.State Grid Jiangsu Electric Power Co., Ltd., Nanjing 211106, China

Abstract:

The wind energy capture efficiency can be effectively improved by properly decreasing the torque gain for the optimal torque control of the maximum power point tracking of wind turbines. However, existing research has pointed out that varying turbulence conditions can not only change the coefficients of optimal torque gain but also affect the convergence performance of the adaptive algorithm for searching the optimal value. The consequent unreasonable torque gain makes it difficult to improve or even reduces the wind energy capture efficiency. Therefore, through the mechanism analysis of the impact of varying turbulence conditions on adaptive algorithm, a well-graded scene of wind conditions is found, which can lead the algorithm search direction continuous incorrect and make wind energy capture efficiency worse. On this basis, an improved adaptive torque control considering varying turbulence conditions is proposed to identify such scenes by introducing the dynamic wind energy capture loss index. By combining the interrupt and restart search mechanism, the search divergence of adaptive algorithm can be prevented, so as to improve the efficiency of wind turbine power generation. Finally, the experiments based on wind turbine drive chain test bench are presented to verify the effectiveness of the proposed method.

Keywords:

Foundation:

This work is supported by National Natural Science Foundation of China (No. 61773214) and Postdoctoral Science Foundation of Jiangsu Province (No. 2019K237).

Get Citation
[1]ZHOU Lianjun, YIN Minghui, YANG Jiongming, et al. Improved Adaptive Torque Control for Wind Turbine Considering Varying Turbulence Conditions[J]. Automation of Electric Power Systems,2021,45(1):184-191. DOI:10.7500/AEPS20200603001
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History
  • Received:June 03,2020
  • Revised:September 27,2020
  • Adopted:
  • Online: January 05,2021
  • Published: