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基于小波模糊熵GG聚类的同调机群识别
引用本文:王涛,杨越,顾雪平,张祥成,张文朝.基于小波模糊熵GG聚类的同调机群识别[J].电力自动化设备,2018,38(7).
作者姓名:王涛  杨越  顾雪平  张祥成  张文朝
作者单位:华北电力大学新能源电力系统国家重点实验室;国网青海省电力公司经济技术研究院;南京南瑞集团公司北京监控技术中心
基金项目:国家自然科学基金资助项目(51677071);国家电网公司科技项目(XT71-16-034);中央高校基本科研业务费专项资金资助项目(2016MS130)
摘    要:针对同调机群识别面临的特征提取片面及计算过程复杂相互制约的问题,提出一种基于小波模糊熵-GG(Gath-Geva)聚类的同调机组识别新方法。根据广域测量系统获取的故障后系统机组功角信息,利用多尺度小波分解将功角摇摆曲线分解为整体趋势和细节信息,计算各个尺度小波系数的模糊熵,并作为发电机的特征向量,再通过GG模糊聚类算法对其进行同调聚类。对IEEE 39节点系统和某实际电网进行仿真,算例分析结果表明所提方法能够根据故障后系统机组功角信息的变化更新功角数据库,实现快速准确的同调机群识别。

关 键 词:同调机组  广域测量系统  小波分解  模糊熵  GG聚类

Identification of coherent generators based on wavelet fuzzy entropy and GG clustering
WANG Tao,YANG Yue,GU Xueping,ZHANG Xiangcheng and ZHANG Wenchao.Identification of coherent generators based on wavelet fuzzy entropy and GG clustering[J].Electric Power Automation Equipment,2018,38(7).
Authors:WANG Tao  YANG Yue  GU Xueping  ZHANG Xiangcheng and ZHANG Wenchao
Affiliation:State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China,State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China,State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China,State Grid Qinghai Electric Power Company Economic Research Institute, Xining 810000, China and NARI Group Corporation Beijing Monitoring Technology Center, Beijing 102200, China
Abstract:A new method for identifying the coherent generators based on wavelet fuzzy entropy and GG(Gath-Geva) clustering is proposed to solve the contradiction between unilateral feature extraction and complex computation. The power angle swing curve obtained by the wide area measurement system is decomposed into the overall trend information and the detailed information by the multi-scale wavelet decomposition, and the fuzzy entropies of wavelet coefficients at each scale are calculated as the eigenvectors of the generators, which are used for coherent clustering by GG fuzzy clustering algorithm. Simulation is carried out for IEEE 39-bus system and a practical power system, and results show that the proposed method can update the power angle database according to the change of power angle after fault, realizing fast and accurate identification of coherent generators.
Keywords:coherent generators  wide area measurement system  wavelet decomposition  fuzzy entropy  Gath-Geva clustering
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