Combining LIDAR and LADRC for intelligent pitch control of wind turbines

Chengzhen Jia, Lingmei Wang, Enlong Meng, Liming Chen, Yushan Liu, Wenqiang Jia, Yutao Bao and Zhenguo Liu

Renewable Energy, 2021, vol. 169, issue C, 1091-1105

Abstract: At present, most of the pitch control methods are based on PI controller, the pitch control system has poor disturbance resistance, and the research of variable parameter feedforward based on Light detection and ranging (LIDAR) and the Linear Active Disturbance Rejection controller (LADRC) composite control is rarely studied to reduce the blade root load, so this paper conceives a hybrid intelligent and adaptive pitch control approach to reduce a wind turbine generator speed fluctuation and its blade root load. Specifically, we combine the Radial Basis Neural Network and Finite Impulse Response filter (RBFNNFIR) based on LIDAR wind measurement. We then use a variable bandwidth of LADRC controller. Overall the approach enables and facilitates self-adaption and self-adjustment. We use Matlab s-function to call the multi-freedom mathematical wind turbine model based on FAST code, the composite intelligent control algorithm is established in Simulink. Initial results from the statistical analysis of the experiments under different turbulent wind conditions shows that the hybrid intelligent pitch control approach can reduce the generator speed fluctuation by about 40.8%, and the blade root max value of load moment by about 13.1%, compared with the baseline values of the traditional variable gain PI control algorithm.

Keywords: LIDAR; RBFNNFIR; LADRC; Speed fluctuation; Load moment; Pitch control (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:169:y:2021:i:c:p:1091-1105

DOI: 10.1016/j.renene.2021.01.065

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