基于SCADA数据的风电机组偏航控制参数优化
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摘要
针对大型风电机组偏航控制参数在实际应用中适应水平差、控制精度低等问题,首先对机组SCADA数据进行统计处理和分析计算,以确定偏航控制区间的划分界限;然后依据各个区间控制策略和风向特点的不同确定参数优化范围,在此基础上应用细菌群体趋药性(BCC)算法对偏航控制参数进行搜索寻优,分别得到高、中、低3级风速区间最优偏航偏差阈值和延迟时间;通过Bladed软件仿真表明该优化方法可在满足偏航比要求的前提下提高发电量,使风场获得更大的经济效益。
The yaw control parameters for large wind turbine currently used encounters the problem of low-level adaptability to the environment and low control accuracy. The SCADA data of the unit is first analyzed and calculated to determine the boundaries line of the yaw control region,based on each interval different control strategy and the wind direction characteristics to determine the scope of the parameter optimization. Then,using the bacterial colony chemotaxis(BBC)algorithm to optimize the yaw control parameters,get high,medium and low three wind speed interval optimization of yaw deviation threshold and delay time. The simulation results of Bladed show that the optimization method increase the power generation capacity in the premise of ensuring the yaw ratio to meet the relevant requirements,so that the wind farm can obtain greater economic benefits.
The yaw control parameters for large wind turbine currently used encounters the problem of low-level adaptability to the environment and low control accuracy. The SCADA data of the unit is first analyzed and calculated to determine the boundaries line of the yaw control region,based on each interval different control strategy and the wind direction characteristics to determine the scope of the parameter optimization. Then,using the bacterial colony chemotaxis(BBC)algorithm to optimize the yaw control parameters,get high,medium and low three wind speed interval optimization of yaw deviation threshold and delay time. The simulation results of Bladed show that the optimization method increase the power generation capacity in the premise of ensuring the yaw ratio to meet the relevant requirements,so that the wind farm can obtain greater economic benefits.
引文
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[11]杜杨超.风力发电机组偏航控制策略的设计[J].机械管理开发,2015,30(8):23—24.[11]Du Yangchao. Design of yaw control strategy of the wind generating set[J]. Mechanical Management and Development,2015,30(8):23—24.
[12]王欣,吴根勇,潘东浩,等.基于运行数据的风电机组偏航优化控制方法研究[J].可再生能源,2016,34(3):413—420.[12]Wang Xin,Wu Genyong,Pan Donghao,et al. Wind turbine yaw control optimization utilizing the running data[J]. Renewable Energy Resources,2016,34(3):413—420.
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[14]Yalcinoz T,K?ksoy O. A multi-objective optimization method to environmental economic dispatch[J].International Journal of Electrical Power and Energy Systems,2007,29(1):42—50.
[15]Muller S D,Marchetto J,Airaghi S,et al. Optimization based on bacterial chemotaxis[J]. IEEE Transactions on Evolutionary Computation,2002,6(1):16—29.
[16]Li Wei-Wu,Wang Hui,Zou Zhi-Jun,et al. Function optimization method based on bacterial colony chemotaxis[J]. Journal of Circuits and System,2005,10(1):58—63.
[17]陈继明,王元元,孙名妤,等.基于改进BCC算法的配电网综合运行优化[J].江苏大学学报:自然科学版,2015,36(01):87—92.[17]Chen Jiming,Wang Yuanyuan,Sun Mingyu,et al.Comprehensive operation optimization of distribution network based on improved bacterial colony chemotaxis algorithm[J]. Journal of Jiangsu University:Natural Science Edition,2015,36(01):87—92.
[18]贾利.基于细菌群体趋药性算法的配电网开关优化配置研究[D].北京:华北电力大学,2009.[18]Jia Li. Research on optimal switching device configuration of distribution system based on bacterial colony chemotaxis[J]. Beijing:North China East Power University,2009.
[2]Choi Han-Soon,Kim Jeong-Gi,Cho Jang-Hwan,et al.Active yaw control of MW class wind turbine[A].International Conference on Control Automation and Systems,IEEE[C]. Gyeonggi-Do,South Korea,2010:1075—1078.
[3]沈小军,杜万里.大型风力发电机偏航系统控制策略研究现状及展望[J].电工技术学报,2015,30(10):196—203.[3]Shen Xiaojun,Du Wanli. Expectation and review of control strategy of large wind turbines yaw system[J].Transactions of China Electrotechnical Socity,2015,30(10):196—203.
[4]Farret F A,Pfitscher L L,Bernardon D P. Sensorless active yaw control for wind turbines[A]. Industrial Electronics Society 2001(IECON’0l),The 27th Annual Conference of the IEEE[C],Denver,CO,USA,2001.
[5]邹强,刘波峰,彭镭,等.爬山算法在风力发电机组偏航控制系统中的应用[J].电网技术,2010,34(5):72—76.[5]Zou Qiang,Liu Bofeng,Peng Lei,et al. Application of hill-climbing control algorithm in yaw control system for wind power generation sets[J]. Power System Technology,2010,34(5):72—76.
[6]朴海国,王志新.风电机组偏航控制系统的新型算法:V-HC研究[J].太阳能学报,2008,29(8):1028—1032.[6]Piao Haiguo,Wang Zhixin. A new control algorithm for yaw control system of wind turbine[J]. Acta Energiae Solaris Sinica,2008,29(8):1028—1032.
[7]Azimi V,Menhaj M B,Fakharian A. Adaptive control of a wind turbine based on neural networks[A]. 13th Iranian Conference on Fuzzy Systems(IFSC)[C],Qazvin,Iran,2013.
[8]杨伟欢,叶安丽,马鸿雁.模糊控制在风力发电机组偏航控制系统中的应用[J].北京建筑工程学院学报,2011,27(14):44—48.[8]Yang Weihuan,Ye Anli,Ma Hongyan. Yaw control system of wind turbine based on fuzzy control[J].Journal of Beijing University of Civil Engineering and Architecture,2011,27(14):44—48.
[9]Zhu Chenghui, Li Pengju, Wang Jianping, et al.Research on intelligent controller of wind-power yaw based on modulation of artificial neuro-endocrineimmunity system[J]. Procedia Engineering,2011,15:903—907.
[10]卢晓光,岳红轩,吴鹏,等.大型风机偏航状态力学分析及偏航控制策略研究[J].可再生能源,2014,32(7):973—977.[10]Lu Xiaoguang, Yue Hongxuan, Wu Peng, et al.Mechanical analysis and control strategy of yaw for largescale wind turbine[J]. Renewable Energy Resources,2014,32(7):973—977.
[11]杜杨超.风力发电机组偏航控制策略的设计[J].机械管理开发,2015,30(8):23—24.[11]Du Yangchao. Design of yaw control strategy of the wind generating set[J]. Mechanical Management and Development,2015,30(8):23—24.
[12]王欣,吴根勇,潘东浩,等.基于运行数据的风电机组偏航优化控制方法研究[J].可再生能源,2016,34(3):413—420.[12]Wang Xin,Wu Genyong,Pan Donghao,et al. Wind turbine yaw control optimization utilizing the running data[J]. Renewable Energy Resources,2016,34(3):413—420.
[13]李威武,王慧,邹志君.基于细菌群体趋药性的函数优化方法[J].电路与系统学报,2005,10(1):58—63.[13]Ling Weiwu, Wang Hui, Zou Zhijun. Function optimization method based on bacterial colony chemotaxis[J]. Journal of Circuits and Systems,2005,10(1):58—63.
[14]Yalcinoz T,K?ksoy O. A multi-objective optimization method to environmental economic dispatch[J].International Journal of Electrical Power and Energy Systems,2007,29(1):42—50.
[15]Muller S D,Marchetto J,Airaghi S,et al. Optimization based on bacterial chemotaxis[J]. IEEE Transactions on Evolutionary Computation,2002,6(1):16—29.
[16]Li Wei-Wu,Wang Hui,Zou Zhi-Jun,et al. Function optimization method based on bacterial colony chemotaxis[J]. Journal of Circuits and System,2005,10(1):58—63.
[17]陈继明,王元元,孙名妤,等.基于改进BCC算法的配电网综合运行优化[J].江苏大学学报:自然科学版,2015,36(01):87—92.[17]Chen Jiming,Wang Yuanyuan,Sun Mingyu,et al.Comprehensive operation optimization of distribution network based on improved bacterial colony chemotaxis algorithm[J]. Journal of Jiangsu University:Natural Science Edition,2015,36(01):87—92.
[18]贾利.基于细菌群体趋药性算法的配电网开关优化配置研究[D].北京:华北电力大学,2009.[18]Jia Li. Research on optimal switching device configuration of distribution system based on bacterial colony chemotaxis[J]. Beijing:North China East Power University,2009.