基于实测数据的风电场稳态等值建模研究
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摘要
针对大型风电场仿真模型复杂,计算量大的特点,提出一种利用实测数据建立大型风电场稳态等值模型的新方法。通过粒子滤波算法对原始风速数据进行预处理,消除噪声干扰对真实数据的影响;考虑到风电场内风机的风况差异问题,采用K-均值聚类算法提取反映风电机组风况差异的特征风速,以简化建模过程;选择特征风速和实测风电功率为输入、输出信号,应用BP神经网络拟合风电场稳态等值模型。该模型考虑了风电场地形地貌、机组分布因素,利用实测数据对模型进行泛化能力分析和精度验证,仿真结果表明,该方法具有一定的准确性与合理性。
In order to resolve complexity and large calculation of large-scale wind farm simulation model,a new method of wind farm steady-state equivalent modeling with measured data is proposed in this paper. Utilizing the particle filter algorithm,various interferences in measured wind speed can be eliminated;in consideration of wind regime differences between wind turbines,the K-means clustering algorithm is introduced to extract the featured wind speed reflecting wind regime differences so as to simplify the modeling process;the featured wind speed and measured power data are collected respectively as the input and output signals,BP neural network is employed to establish the wind farm steady-state equivalent model. The proposed model involves topography and turbines distribution of the actual wind farm,measured data are adopted to analyze its generalization ability and verify its accuracy,simulation results indicates that the modeling method is precise and rational.
In order to resolve complexity and large calculation of large-scale wind farm simulation model,a new method of wind farm steady-state equivalent modeling with measured data is proposed in this paper. Utilizing the particle filter algorithm,various interferences in measured wind speed can be eliminated;in consideration of wind regime differences between wind turbines,the K-means clustering algorithm is introduced to extract the featured wind speed reflecting wind regime differences so as to simplify the modeling process;the featured wind speed and measured power data are collected respectively as the input and output signals,BP neural network is employed to establish the wind farm steady-state equivalent model. The proposed model involves topography and turbines distribution of the actual wind farm,measured data are adopted to analyze its generalization ability and verify its accuracy,simulation results indicates that the modeling method is precise and rational.
引文
[1]World Wind Energy Association.Special issue:World wind energy report 2014[R].Bonn:World Wind Energy Association,2015.
[2]张丽英,叶廷路,辛耀中,等.大规模风电接入电网的相关问题及措施[J].中国电机工程学报,2010,30(25):1-9.[2]Zhang Liying,Ye Tinglu,Xin Yaozhong,et al.Problems and measures of power grid accommodating large scale wind power[J].Proceedings of the CSEE,2010,30(25):1-9.
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[4]薛禹胜,雷兴,薛峰,等.关于风电不确定性对电力系统影响的评述[J].中国电机工程学报,2014,34(29):5029-5040.[4]Xue Yusheng,Lei Xing,Xue Feng,et al.A Review on impacts of wind power uncertainties on power systems[J].Proceedings of the CSEE,2014,34(29):5029-5040.
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[7]王铮,刘纯,冯双磊,等.基于非参数回归的风电场理论功率计算方法[J].电网技术,2015,39(8):2148-2153.[7]Wang Zheng,Liu Chun,Feng Shuanglei,et al.The wind farm theoretical power calculation method research based on non-parameter regression[J].Power System Technology,2015,39(8):2148-2153.
[8]张元,郝丽丽,戴嘉祺.风电场等值建模研究综述[J].电力系统保护与控制,2015,43(6):138-146.[8]Zhang Yuan,Hao Lili,Dai Jiaqi.Overview of the equivalent model research for wind farms[J].Power System Protection and Control,2015,43(6):138-146.
[9]蒙晓航,叶林,赵永宁.永磁直驱同步风电场多机动态等值模型[J].电力系统保护与控制,2013,41(14):25-32.[9]Meng Xiaohang,Ye Lin,Zhao Yongning.Dynamic multimachine equivalent model of direct drive permanen magnet synchronous generators of wind farm[J].Power System Protection and Control,2013,41(14):25-32.
[10]叶林,饶日晟,朗燕生,等.考虑有向功率特性的风电场功率输出模型[J].电网技术,2016,40(12):3775-3782.[10]Ye Lin,Rao Risheng,Lang Yansheng,et al.Power outpu model of wind farms considering directional power characteristics[J].Power System Technology,2016,40(12):3775-3782.
[11]郑睿敏,李建华,李作红,等.考虑尾流效应的风电场建模以及随机潮流计算[J].西安交通大学学报,2008,42(12):1515-1520.[11]Zheng Ruimin,Li Jianhua,Li Zuohong,et al Modeling of large-scale wind farms in the probabilistic power flow analysis considering wake effects[J].Journa of Xi'an Jiaotong University,2008,42(12):1515-1520.
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[13]严干贵,李鸿博,穆钢,等.基于等效风速的风电场等值建模[J].东北电力大学学报,2011,31(3):13-19.[13]Yan Gangui,Li Hongbo,Mu Gang,et al.Equivalent model of wind farm by using the equivalent wind speed[J].Journal of Northeast Dianli University,2011,31(3):13-19.
[14]胡士强.粒子滤波原理及其应用[M].北京:科学出版社,2010.17-20.[14]Hu Shiqiang.The Principle and Application of Particle Filter[M].Beijing:Science Press,2010.17-20.
[15]陈志敏,薄煜明,吴盘龙,等.基于自适应粒子群优化的新型粒子滤波在目标跟踪中的应用[J].控制与决策,2013,28(2):193-200.[15]Chen Zhimin,Bo Yuming,Wu Panlong,et al.Novel particle filter algorithm based on adaptive particle swarm optimization and its application to radar target tracking[J].Control and Decision,2013,28(2):193-200.
[16]龙波,刘喜昂.关联数据聚类-模型、算法及应用[M].北京:科学出版社,2015.73.[16]Long Bo,Liu Xi’ang.Linked Data Clustering-Model,Algorithm and Application[M].Beijing:Science Press,2015.73.
[17]陆亿红,夏聪.不确定数据的最优k近邻和局部密度聚类算法[J].控制与决策,2016,31(3):541-546.[17]Lu Yihong,Xia Cong.Optimal k-nearest neighbors and local density-based clustering algorithm for uncertain data[J].Control and Decision,2016,31(3):541-546.
[18]余胜威.MATLAB优化算法案例分析与应用[M].北京:清华大学出版社,2016.61-62.[18]Yu Shengwei.Analysis and Application of MATLABOptimization Algorithm Cases[M].Beijing:Tsinghua University Press,2016.61-62.
[19]杨杰,占君,张继传.MATLAB神经网络30例[M].北京:电子工业出版社,2014.6-11.[19]Yang Jie,Zhan Jun,Zhang Jichuan.30 Cases of MATLAB Neural Network[M].Beijing:Publishing House of Electronics Industry,2014.6-11.
[20]飞思科技产品研发中心.神经网络理论与MATLAB7实现[M].北京:电子工业出版社,2005.103.[20]Fiseeo Product Research&Development Center.Neural Network Theory and MATLAB 7 Implementation[M].Beijing:Publishing House of Electronics Industry,2005.103.
[21]孟岩峰,胡书举,邓雅,等.风电功率预测误差分析及预测误差评价方法[J].电力建设,2013,34(7):6-9.[21]Meng Yanfeng,Hu Shuju,Deng Ya,et al.Analysis and evaluation method of wind power predicted-error[J].Electric Power Construction,2013,34(7):6-9.
[22]徐曼,乔颖,鲁宗相.短期风电功率预测误差综合评价方法[J].电力系统自动化,2011,35(12):20-26.[22]Xu Man,Qiao Ying,Lu Zongxiang.A comprehensive error method for short-term wind power prediction[J].Automation of Electric Power System,2011,35(12):20-26.
[2]张丽英,叶廷路,辛耀中,等.大规模风电接入电网的相关问题及措施[J].中国电机工程学报,2010,30(25):1-9.[2]Zhang Liying,Ye Tinglu,Xin Yaozhong,et al.Problems and measures of power grid accommodating large scale wind power[J].Proceedings of the CSEE,2010,30(25):1-9.
[3]潘学萍,张弛,鞠平,等.风电场同调动态等值研究[J].电网技术,2015,39(3):621-627.[3]Pan Xueping,Zhang Chi,Ju Ping,et al.Coherencybased dynamic equivalence of wind farm composed of doubly fed induction generators[J].Power System Technology,2015,39(3):621-627.
[4]薛禹胜,雷兴,薛峰,等.关于风电不确定性对电力系统影响的评述[J].中国电机工程学报,2014,34(29):5029-5040.[4]Xue Yusheng,Lei Xing,Xue Feng,et al.A Review on impacts of wind power uncertainties on power systems[J].Proceedings of the CSEE,2014,34(29):5029-5040.
[5]葛江北,周明,李庚银.大型风电场建模综述[J].电力系统保护与控制,2013,41(17):146-151.[5]Ge Jiangbei,Zhou Ming,Li Gengyin.Review on large scale wind farm modeling[J].Power System Protection and Control,2013,41(17):146-151.
[6]孙辉,徐箭,孙元章,等.考虑风速时空分布及风机运行状态的风电场功率计算方法[J].电力系统自动化,2015,39(2):30-38,60.[6]Sun Hui,Xu Jian,Sun Yuanzhang,et al.A method for wind power calculation considering wind speed spatia and temporal distribution and wind turbine operation status[J].Automation of Electric Power Systems,2015,39(2):30-38,60.
[7]王铮,刘纯,冯双磊,等.基于非参数回归的风电场理论功率计算方法[J].电网技术,2015,39(8):2148-2153.[7]Wang Zheng,Liu Chun,Feng Shuanglei,et al.The wind farm theoretical power calculation method research based on non-parameter regression[J].Power System Technology,2015,39(8):2148-2153.
[8]张元,郝丽丽,戴嘉祺.风电场等值建模研究综述[J].电力系统保护与控制,2015,43(6):138-146.[8]Zhang Yuan,Hao Lili,Dai Jiaqi.Overview of the equivalent model research for wind farms[J].Power System Protection and Control,2015,43(6):138-146.
[9]蒙晓航,叶林,赵永宁.永磁直驱同步风电场多机动态等值模型[J].电力系统保护与控制,2013,41(14):25-32.[9]Meng Xiaohang,Ye Lin,Zhao Yongning.Dynamic multimachine equivalent model of direct drive permanen magnet synchronous generators of wind farm[J].Power System Protection and Control,2013,41(14):25-32.
[10]叶林,饶日晟,朗燕生,等.考虑有向功率特性的风电场功率输出模型[J].电网技术,2016,40(12):3775-3782.[10]Ye Lin,Rao Risheng,Lang Yansheng,et al.Power outpu model of wind farms considering directional power characteristics[J].Power System Technology,2016,40(12):3775-3782.
[11]郑睿敏,李建华,李作红,等.考虑尾流效应的风电场建模以及随机潮流计算[J].西安交通大学学报,2008,42(12):1515-1520.[11]Zheng Ruimin,Li Jianhua,Li Zuohong,et al Modeling of large-scale wind farms in the probabilistic power flow analysis considering wake effects[J].Journa of Xi'an Jiaotong University,2008,42(12):1515-1520.
[12]胡雅娟.基于实测运行数据风电场整体模型的研究[D].吉林:东北电力大学,2007.[12]Hu Yajuan.Research on global wind farm model based on measured operation data[D].Jilin:Northeast Dianli University,2007.
[13]严干贵,李鸿博,穆钢,等.基于等效风速的风电场等值建模[J].东北电力大学学报,2011,31(3):13-19.[13]Yan Gangui,Li Hongbo,Mu Gang,et al.Equivalent model of wind farm by using the equivalent wind speed[J].Journal of Northeast Dianli University,2011,31(3):13-19.
[14]胡士强.粒子滤波原理及其应用[M].北京:科学出版社,2010.17-20.[14]Hu Shiqiang.The Principle and Application of Particle Filter[M].Beijing:Science Press,2010.17-20.
[15]陈志敏,薄煜明,吴盘龙,等.基于自适应粒子群优化的新型粒子滤波在目标跟踪中的应用[J].控制与决策,2013,28(2):193-200.[15]Chen Zhimin,Bo Yuming,Wu Panlong,et al.Novel particle filter algorithm based on adaptive particle swarm optimization and its application to radar target tracking[J].Control and Decision,2013,28(2):193-200.
[16]龙波,刘喜昂.关联数据聚类-模型、算法及应用[M].北京:科学出版社,2015.73.[16]Long Bo,Liu Xi’ang.Linked Data Clustering-Model,Algorithm and Application[M].Beijing:Science Press,2015.73.
[17]陆亿红,夏聪.不确定数据的最优k近邻和局部密度聚类算法[J].控制与决策,2016,31(3):541-546.[17]Lu Yihong,Xia Cong.Optimal k-nearest neighbors and local density-based clustering algorithm for uncertain data[J].Control and Decision,2016,31(3):541-546.
[18]余胜威.MATLAB优化算法案例分析与应用[M].北京:清华大学出版社,2016.61-62.[18]Yu Shengwei.Analysis and Application of MATLABOptimization Algorithm Cases[M].Beijing:Tsinghua University Press,2016.61-62.
[19]杨杰,占君,张继传.MATLAB神经网络30例[M].北京:电子工业出版社,2014.6-11.[19]Yang Jie,Zhan Jun,Zhang Jichuan.30 Cases of MATLAB Neural Network[M].Beijing:Publishing House of Electronics Industry,2014.6-11.
[20]飞思科技产品研发中心.神经网络理论与MATLAB7实现[M].北京:电子工业出版社,2005.103.[20]Fiseeo Product Research&Development Center.Neural Network Theory and MATLAB 7 Implementation[M].Beijing:Publishing House of Electronics Industry,2005.103.
[21]孟岩峰,胡书举,邓雅,等.风电功率预测误差分析及预测误差评价方法[J].电力建设,2013,34(7):6-9.[21]Meng Yanfeng,Hu Shuju,Deng Ya,et al.Analysis and evaluation method of wind power predicted-error[J].Electric Power Construction,2013,34(7):6-9.
[22]徐曼,乔颖,鲁宗相.短期风电功率预测误差综合评价方法[J].电力系统自动化,2011,35(12):20-26.[22]Xu Man,Qiao Ying,Lu Zongxiang.A comprehensive error method for short-term wind power prediction[J].Automation of Electric Power System,2011,35(12):20-26.