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| Wind turbine pitch control using ICPSO-PID algorithm |
| Xu Chang1, Tian Qiangqiang1,2, Shen Wenzhong3, Zhen Yuan1, Liu Deyou1, Zhang Ming4 |
| 1.College of Energy and Electrical Engineering, Hohai University, Nanjing, Jiangsu 210098, China; 2.Shanghai Investigation, Design and Research Institute, Shanghai 200434, China; 3.Department of Wind Energy, Technical University of Denmark, Lyngby, Copenhasen DK-2800, Danmark; 4.NanJing Mennekes Electric Appliances Co.Ltd., NanJing, Jiangsu 211100, China |
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Abstract For the traditional simplified first-order pitch-control system model, it is difficult to describe a real dynamic characteristic of a variable pitch action system, thus a complete high order mathematical model has to be developed for the pitch control of wind turbine generation(WTG). In the paper, a pitch controller was designed based on power and wind speed and by considering the inertia and delay characteristics of a pitch-control system to achieve a constant power output when a wind speed was beyond the rated one. A novel ICPSO-PID control algorithm was proposed based on a combination of improved cooperative particle swarm optimization(ICPSO)and PID, subsequently, it was used to tune the pitch controller parameters; thus the difficulty in PID tuning was removed when a wind speed was above the rated speed. It was indicated that the proposed optimization algorithm can tune the pitch controller parameters quickly; and the feed-forward controller for wind speed can improve dynamics of a pitch-control system; additionally the power controller can allow a wind turbine to have a constant power output as a wind speed is over the rated one. Compared with a conventional PID, the controller with ICPSO-PID algorithm has a smaller overshoot, a shorter tuning time and better robustness. The design method proposed in the paper can be applied in a practical electro-hydraulic pitch control system for WTG.
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Received: 20 July 2013
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| [1]Horiuchi N,Kawahito T.Torque and power limitations of variable speed wind turbines using pitch control and ge-nerator power control[C]//IEEE Power Engineering Society Summer Meeting, 2001:638-643.[2]Ostergaard K Z,Brath P,Stoustrup J.Gain-scheduled li-near quadraticcontrol of wind turbines operating at high wind speed[C]//Proceedings of the 2007 IEEE Multi-conference on Systems and Control, 2007:276-281.[3]Muhando E B,Senjyu T,Yona A,et al.Disturbance rejection by dual pitch control and self-tuning regulator for wind turbine generator parametric uncertainty compensation[J].IET Control Theory & Applications,2007,1(5):1431-1440.[4]Senjyu T,Sakamoto R,Urasaki N. Output power leveling of wind turbine generator for all operating regions by pitch angle control[J]. IEEE Transcation on Energy Conversion,2006,21(2):467-475.[5]Muhando E B,Senjyu T, Kinjo H,et al.Augmented LQG controller for enhancement of online dynamic perfor-mance for WTG system[J].Renewable Energy,2008,33(8):1942-1952.[6]张先勇,吴捷,杨金明,等.额定风速以上风力发电机组的恒功率H∞鲁棒控制[J].控制理论与应用,2008,25(2):321-324. Zhang Xianyong, Wu Jie, Yang Jinming, et al.The wind energy conversion system above rated wind[J]. Control Theory & Applications,2008,25(2):321-324.(in Chinese)[7]孙涛,秦录芳.风力机变桨距的模糊PID参数自整定控制[J].机床与液压,2011,39(10):121-130. Sun Tao, Qin Lufang.Fuzzy PID parameters self-tuning control of wind turbines variable-pitch[J].Machine Tool & Hydraulics, 2011,39(10): 121-130.(in Chinese)[8]郭鹏.模糊前馈与模糊PID结合的风力发电机组变桨距控制[J].中国电机工程学报,2010,30(8):123-128. Guo Peng.Variable pitch control of wind turbine generator combined with fuzzy feed forward and fuzzy PID controller [J].Proceedings of the CSEE, 2010, 30(8):123-128.(in Chinese)[9]韦徵,陈冉,陈家伟,等.基于功率变化和模糊控制的风力发电机组变速变桨距控制[J].中国电机工程学报,2011,31(17):121-126. Wei Zheng, Chen Ran, Chen Jiawei, et al. Wind turbine-generator unit variable-speed pitch control based on judgment of power changes and fuzzy control [J].Proceedings of the CSEE,2011,31(17):121-126.(in Chinese)[10]张巍,卢宇清.基于在线自适应遗传算法的 PID 参数整定和优化[J].计算机仿真,2011,28(12):154-157. Zhang Wei,Lu Yuqing.Optimized and adjust the para-meter of PID based on on-line adaptive genetic algorithms[J].Computer Simulation,2011,28(12):154-157.(in Chinese)[11]张兴华,著笑容,林锦国.基于量子遗传算法PID控制器参数自整定[J].计算机工程与应用,2007,43(21):218-223. Zhang Xinghua,Zhu Xiaorong,Lin Jinguo.Parameter self-tuning of PID controllers based on quantum genetic algorithms[J].Computer Engineering and Applications,2007,43(21):218-223.(in Chinese)[12]丁敬保.风力发电机组变桨距电液比例控制技术的研究 [D].长春:吉林大学机械科学与工程学院,2008.[13]Kennedy J,Eberhart R C. Particle swarm optimization[C]//Proceedings of IEEE International Conference on Neural Networks.Perth,Australia: IEEE Press,1995:1942-1948.[14]Song Y,Chen Z Q,Yuan Z Z. New chaotic PSO-based neural network predictive control for nonlinear process [J].IEEE Transactions on Neural Networks,2007,18(2):595-601.[15]Shen Xianjun, Chi Zhifeng,Kai Jin,et al. Particle swarm optimization with dynamic adaptive inertia weight[C]//Proceedings of the 2010 IEEE International conference on Challenges in Environmental Science and Computer Engineering, 2010:287-290.[16]Zhang Wei. The selection of acceleration factors for improving stability of particle swarm optimization [C]//Proceedings of the 2008 IEEE Fourth International Conference on Natural Computation,2008:376-380.[17]Lovbjerg M,Rasmussen T K,Krink T.Hybird particle swarm optimizer with breeding and subpopulation [C]//Proceedings of the 3th Genetic and Evolutionary Computation Conference,2001.[18]李林,李燕青,温秀峰.多粒子群协同优化算法的配电网网架规划 [J].继电器,2007,35(S1):409-412. Li Lin,Li Yanqing,Wen Xiufeng.Particle swarms coo-perative optimization algorithm for distribution network planning[J].Relay,2007,35(S1):409-412.(in Chinese) |
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