基于WAMS和曲线相似的同调机群识别方法
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摘要
提出了一种基于曲线相似的电力系统同调机群辨识新方法。首先获取WAMS实时监测得到的功角轨迹曲线作为基础数据,根据离散曲线相似性的定义,将各发电机的轨迹曲线分段,借助遗传算法确定分段轨迹之间的最优相似距离,保存了轨迹段的局部特性。然后整合各段相似距离得到各发电机之间的整体相似度并以此作为聚类指标,再利用层次聚类法实现多机系统同调机组分群。该方法简单可行,不受系统模型参数和故障类型的限制。最后对IEEE39节点系统进行分析计算,该仿真实验佐证了所提算法的有效性。
This paper proposed a new method to recognize coherent generator groups based on curve similarity in power system. Firstly,the real-time perturbed trajectory of rotor angle is used as an original data,which can be obtained from wide-area measurement system( WAMS). According to the definition of discrete curve similarity,the power angle trajectory of each generator is divided into several sections. The method uses genetic algorithm to determine the best similarity distance between track segments,which can keep the local features of the track segments. Then,all segment similarity distances are integrated into overall similarity between generators. The overall similarity is taken as clustering index. Then,with the hierarchical clustering method,it can achieve clustering coherent generators in multimachine system. This method is simple and feasible,and is not restricted by the parameters of the system model and the fault type. Finally,the simulation analysis results of IEEE39 node system show that the proposed method is effective.
This paper proposed a new method to recognize coherent generator groups based on curve similarity in power system. Firstly,the real-time perturbed trajectory of rotor angle is used as an original data,which can be obtained from wide-area measurement system( WAMS). According to the definition of discrete curve similarity,the power angle trajectory of each generator is divided into several sections. The method uses genetic algorithm to determine the best similarity distance between track segments,which can keep the local features of the track segments. Then,all segment similarity distances are integrated into overall similarity between generators. The overall similarity is taken as clustering index. Then,with the hierarchical clustering method,it can achieve clustering coherent generators in multimachine system. This method is simple and feasible,and is not restricted by the parameters of the system model and the fault type. Finally,the simulation analysis results of IEEE39 node system show that the proposed method is effective.
引文
[1]鞠平,王卫华,谢宏杰,等.3区域互联电力系统动态等值的辨识方法[J].中国电机工程学报,2007,27(13):29-34.Ju Ping,Wang Weihua,Xie Hongjie,et al.Identification approach to dynamic equivalents of the power system interconnected with three areas[J].Proceedings of the CSEE,2007,27(13):29-34.
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[10]宋洪磊,吴俊勇,郝亮亮,等.基于WAMS和改进拉普拉斯特征映射的同调机群在线识别[J].电网技术,2013,37(8):2157-2164.Song Hongwei,Wu Junyong,Hao Liangliang,et al.On-line identification of coherent generator based on WAMS and improved Laplacian Eigenmap algorithm[J].Power System Technology,2013,37(8):2157-2164.
[11]姜涛,黄河,贾宏杰,等.基于投影寻踪最佳方向的同调机群识别方法[J].中国电机工程学报,2015,35(2):359-367.Jiang Tao,Huang He,Jia Hongjie,et al.Coherency identification through projection pursuit[J].Proceedings of the CSEE,2015,35(2):359-367.
[12]张亚洲,张艳霞,蒙高鹏,等.基于广域信息的同调机群聚类识别方法[J].电网技术,2015,39(10):2889-2893.Zhang Yazhou,Zhang Yanxia,Meng Gaopeng,et al.A wide area information based clustering recognition method of coherent generators[J].Power System Technology,2015,39(10):2889-2893.
[13]朱洁.一种新的曲线相似性判别方法研究[D].武汉:武汉理工大学,2008.
[14]Zheng J B,Zhu G X.A new algorithm for on-line handwriting signature verification based on evolutionary computation[J].Wuhan University Journal of Natural Sciences,2006,11(3):596-600.
[15]邱益鸣,胡华成,郑建彬,等.基于曲线相似的在线签名认证方法[J].系统工程与电子技术,2014,36(5):1016-1020.
[16]戴晨松,薛峰,薛禹胜.受扰轨迹的分群研究[J].电力系统自动化,2000,24(1):13-16.Dai Chensong,Xue Feng,Xue Yusheng.Classification of disturbed trajectories[J].Automation of Electric Power Systems,2000,24(1):13-16.
[17]倪以信,陈寿孙,张宝霖.动态电力系统的理论和分析[M].北京:清华大学出版社,2002.
[18]杨小兵.聚类分析中若干关键技术的研究[D].杭州:浙江大学,2005.
[19]史坤鹏,穆钢,李婷,等.基于经验模式分解的聚类树方法及其在同调机组分群中的应用[J].电网技术,2007,31(22):21-25.Shi Kunpeng,Mu Gang,Li Ting,et al.Empirical mode decomposition based clustering-tree method and its application in coherency identification of generating sets[J].Power System Technology,2014,31(22):21-25.
[2]许剑冰,薛禹胜,张启平,等.电力系统同调动态等值的述评[J].电力系统自动化,2009,25(14):91-95.Xu Jianbing,Xue Yusheng,Zhang Qiping,et al.A critical review on coherency-based dynamic equivalen[J].Automation of Electric Power Systems,2009,25(14):91-95.
[3]Podmore R.Identification of coherent generators for dynamic equivalents[J].IEEE Trans on Power Apparatus and Systems,1978,97(4):1344-1354.
[4]Wu F F,Narasimhamnrthi N.Coherency identification for power system dynamic equivalents[J].IEEE Trans on CAS,1983,30(3):140-147.
[5]赵书强,常鲜戎,潘云江.电力系统同调机群识别的一种模糊聚类方法[J].电网技术,2001,25(4):10-13.Zhao Shuqiang,Chang Xianrong,Pan Yunjiang.A fuzzy clustering method for coherent generator groups in power systems[J].Power system Technology,2001,25(4):10-13.
[6]段刚,严亚勤,谢晓冬,等.广域相量测量技术发展现状与展望[J].电力系统自动化,2015,39(1):73-80.Duan Gang,Yan Yaqin,Xie Xiaodong,et al.Development Status Quo and tendency of wide area phasor measuring technology[J].Automation of Electric Power Systems,2015,39(1):73-80.
[7]Stahlhut J W,Browne T J,Heydt G T,et al.Latency viewed as a stochastic process and its impact on wide area power system control signals[J].IEEE Trans.on Power Systems,2008,23(1):84-91.
[8]Zhou N,Pierre J W,Hauer J F.Initial results in power system identification from injected probing signals using a subspace method[J].IEEE Trans.on Power Systems,2006,21(3):1296-1302.
[9]安军,穆钢,徐炜彬.基于主成分分析法的电力系统同调机群识别[J].电网技术,2009,33(3):25-28.An Jun,Mu Gang,Xu Weibin.Recognition of power system coherent generators based on principal component analysis[J].Power System Technology,2009,33(3):25-28.
[10]宋洪磊,吴俊勇,郝亮亮,等.基于WAMS和改进拉普拉斯特征映射的同调机群在线识别[J].电网技术,2013,37(8):2157-2164.Song Hongwei,Wu Junyong,Hao Liangliang,et al.On-line identification of coherent generator based on WAMS and improved Laplacian Eigenmap algorithm[J].Power System Technology,2013,37(8):2157-2164.
[11]姜涛,黄河,贾宏杰,等.基于投影寻踪最佳方向的同调机群识别方法[J].中国电机工程学报,2015,35(2):359-367.Jiang Tao,Huang He,Jia Hongjie,et al.Coherency identification through projection pursuit[J].Proceedings of the CSEE,2015,35(2):359-367.
[12]张亚洲,张艳霞,蒙高鹏,等.基于广域信息的同调机群聚类识别方法[J].电网技术,2015,39(10):2889-2893.Zhang Yazhou,Zhang Yanxia,Meng Gaopeng,et al.A wide area information based clustering recognition method of coherent generators[J].Power System Technology,2015,39(10):2889-2893.
[13]朱洁.一种新的曲线相似性判别方法研究[D].武汉:武汉理工大学,2008.
[14]Zheng J B,Zhu G X.A new algorithm for on-line handwriting signature verification based on evolutionary computation[J].Wuhan University Journal of Natural Sciences,2006,11(3):596-600.
[15]邱益鸣,胡华成,郑建彬,等.基于曲线相似的在线签名认证方法[J].系统工程与电子技术,2014,36(5):1016-1020.
[16]戴晨松,薛峰,薛禹胜.受扰轨迹的分群研究[J].电力系统自动化,2000,24(1):13-16.Dai Chensong,Xue Feng,Xue Yusheng.Classification of disturbed trajectories[J].Automation of Electric Power Systems,2000,24(1):13-16.
[17]倪以信,陈寿孙,张宝霖.动态电力系统的理论和分析[M].北京:清华大学出版社,2002.
[18]杨小兵.聚类分析中若干关键技术的研究[D].杭州:浙江大学,2005.
[19]史坤鹏,穆钢,李婷,等.基于经验模式分解的聚类树方法及其在同调机组分群中的应用[J].电网技术,2007,31(22):21-25.Shi Kunpeng,Mu Gang,Li Ting,et al.Empirical mode decomposition based clustering-tree method and its application in coherency identification of generating sets[J].Power System Technology,2014,31(22):21-25.