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Individual Pitch Control of Wind Turbines Based on SVM Load Estimation and LIDAR Measurement
Author(s) -
Xin Wang,
Jianshu Zhou,
Bin Qin,
Yingbing Luo,
Chenjuan Hu,
Jiameng Pang
Publication year - 2021
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2021.3120543
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
With the development of wind turbines to the large scale with high rated powers, how to reduce fatigue loads is the key factor for modern wind turbine control. Aiming at reducing the wind turbine structural fatigue loads, an individual pitch control (IPC) method based on SVM estimation of blade root loads was proposed in this paper. The blade root loads were dynamically estimated by a SVM model according to light detection and ranging (LIDAR) wind speed data. Two approximate decoupling systems for yaw moments and pitch moments were then obtained through Coleman transform. Meanwhile, two individual pitch controllers were designed to reduce the loads and a wind speed feedforward controller was adopted to improve the pitch control performance. The proposed method was verified by a FAST, LIDAR and RT-LAB semi-physical real-time combined simulation system. On this basis, a master control unit was developed and the overall unit was further verified by a CRRC wind turbine master control and pitch joint test platform. Compared with collective pitch control (CPC) and the IPC based on azimuth, the proposed method is effective on reducing fatigue loads and vibration.

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