Please wait a minute...
浙江大学学报(工学版)
机械工程     
电液数字马达变桨距控制与辨识
殷秀兴,林勇刚,李伟,顾亚京,刘宏伟
浙江大学 流体动力与机电系统国家重点实验室,浙江 杭州 310027
Control and model identification of an electro-hydraulic digital pitch system
YIN Xiu-xing, LIN Yong-gang, LI Wei, GU ya-jing, LIU Hong-wei
The State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou 310027, China
 全文: PDF(2004 KB)   HTML
摘要:

为通过变桨距来较好地控制风力机功率,提出电液数字马达变桨距控制系统.采用由工控机直接控制的大功率液压马达来进行变桨距,通过开环通道实现直接的变桨距控制,并经由内部自反馈回路确保变桨距精度,而由液压回路提供变桨恒压油源.分析系统非线性特征,并针对该特征,改进极限状态机算法并用于该变桨距系统模型的辨识.在此基础上,采用实测数据进行仿真验算.结果表明,电液数字马达能够有效地进行变桨距控制,相比于传统变桨距方式,能够较好地稳定机组功率,改进的辨识算法具有较高的模型辨识精度.

Abstract:

An electro-hydraulic digital pitch system is proposed to smooth the output power fluctuations for wind turbine. An industrial personal computer-controlled hydraulic motor with high power/mass ratio is employed to achieve the pitch control in an outer open loop of this system. An inherent feedback position control loop in this system guarantees the pitch control accuracy. A constant hydraulic circuit provides the pressure supply. System model was identified using an improved identification algorithm to deal with the nonlinearities and uncertainties associated with the pitch actions. Simulations were carried out based on practical measurements. The simulation results have verified the effectiveness and higher power control precision of this system compared to conventional pitch systems. Effectiveness of the improved identification algorithm has been also validated by simulation results.

出版日期: 2014-11-26
:  TM 619  
基金资助:

国家自然科学基金创新研究群体科学基金资助项目(51221004);国家“十一五”科技支撑计划资助项目(2012BAA01B01).

通讯作者: 林勇刚,副教授,硕导.     E-mail: yglin@zju.edu.cn
作者简介: 殷秀兴,(1986-),博士生,主要从事风力及海流能发电与控制等方面的研究.E-mail:lixingfile@163.com
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  

引用本文:

殷秀兴,林勇刚,李伟,顾亚京,刘宏伟. 电液数字马达变桨距控制与辨识[J]. 浙江大学学报(工学版), 10.3785/j.issn.1008-973X.2014.05.004.

YIN Xiu-xing, LIN Yong-gang, LI Wei, GU ya-jing, LIU Hong-wei. Control and model identification of an electro-hydraulic digital pitch system. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 10.3785/j.issn.1008-973X.2014.05.004.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2014.05.004        http://www.zjujournals.com/eng/CN/Y2014/V48/I5/777

[1] 王亚飞,赵斌,许洪华.风电机组电动变桨距系统的研究[J].可再生能源,201129(5):69.
WANG Ya-fei, ZHAO Bin,XU Hong-hua. Wind turbine electric pitch system [J]. Renewable Energy, 2011,29 (5): 69.
[2] 林勇刚. 大型风力机变桨距控制技术研究[D]. 杭州: 浙江大学, 2005.
LIN Yong-gang. Large-scale wind turbine pitch control technology research, doctoral thesis of Zhejiang University [D],Hangzhou:Zhejiang University, 2005.
[3] LIANG N Y, HUANG G B, SARATCHANDRAN P, et al. A fast and accurate online sequential learning algorithm for feed forward networks[J]. IEEE Transactions on Neural Networks,2006,17(6): 1011-1434.
[4] HUANG Guang- bin,ZHU Qin- yu,SIEW C K.Extreme learning ma-chine: a new learning scheme of feedforward neural networks[C]∥Proc. of IEEE International Joint Conference on Neural Networks.Singapore: MIT Press, 2004: 985990.
[5] PLATT J C. Fast training of support vector machines using sequential minimal optimization [J]. IEEE Transactions on Neural Networks, 1999, 18(7): 185-208.
[6]王春行.液压控制系统[M].北京:机械工业出版社,1999:128168.
[7] 龚纯, 王正林.精通MATLAB最优化计算[M],2版,北京:电子工业出版社, 2012:86178.
[8] 叶杭冶.风力发电机组的控制技术[M].北京:机械工业出版社,2002:28126.
[9] 徐丽娜. 神经网络控制[M].北京:电子工业出版社,2003:43168.
[10] 周开利,康耀红,著.神经网络模型及其matlab仿真程序设计[M].北京:清华大学出版社,2005:96178.
[11] HUANG G B, ZHU Q Y, SIEW C K. Extreme learning machine: theory and applications [J]. Neurocomputing, 2006, 12(1): 489-501.
[12] 刘骏佳.电力系统计算机仿真[M].杭州: 浙江大学出版社,1998:98196.

[1] 吴越, 张国月, 杨捷, 齐冬莲. 新能源变流器SSR-MDF控制方法[J]. 浙江大学学报(工学版), 2015, 49(8): 1516-1521.
[2] 殷秀兴, 顾亚京, 林勇刚, 叶杭冶, 李伟. 复现风力机五自由度载荷的加载控制方法[J]. 浙江大学学报(工学版), 2015, 49(8): 1470-1477.
[3] 殷秀兴, 林勇刚, 李伟, 顾亚京, 楼杉, 刘宏伟. 基于电液行星锥齿马达的变桨距控制[J]. J4, 2014, 48(2): 206-213.