A User-Transformer Relation Identification Method Based on QPSO and Kernel Fuzzy Clustering  

作　　者：Yong Xiao Xin Jin Jingfeng Yang Yanhua Shen Quansheng Guan 

机构地区：[1]China Southern Power Grid Research Institute Co.,Ltd.,Guangzhou,510663,China [2]China Southern Power Grid Co.,Ltd.,Guangzhou,510663,China [3]School of Materials Science and Engineering,South China University of Technology,Guangzhou,510641,China [4]School of Electronics and Information,South China University of Technology,Guangzhou,510641,China

出　　处：《Computer Modeling in Engineering & Sciences》2021年第3期1293-1313,共21页工程与科学中的计算机建模（英文）

基　　金：supported by the National Natural Science Foundation of China(61671208).

摘　　要：User-transformer relations are significant to electric power marketing,power supply safety,and line loss calculations.To get accurate user-transformer relations,this paper proposes an identification method for user-transformer relations based on improved quantum particle swarm optimization(QPSO)and Fuzzy C-Means Clustering.The main idea is:as energymeters at different transformer areas exhibit different zero-crossing shift features,we classify the zero-crossing shift data from energy meters through Fuzzy C-Means Clustering and compare it with that at the transformer end to identify user-transformer relations.The proposed method contributes in three main ways.First,based on the fuzzy C-means clustering algorithm(FCM),the quantum particle swarm optimization(PSO)is introduced to optimize the FCM clustering center and kernel parameters.The optimized FCM algorithm can improve clustering accuracy and efficiency.Since easily falls into a local optimum,an improved PSO optimization algorithm(IQPSO)is proposed.Secondly,considering that traditional FCM cannot solve the linear inseparability problem,this article uses a FCM(KFCM)that introduces kernel functions.Combinedwith the IQPSOoptimization algorithm used in the previous step,the IQPSO-KFCM algorithm is proposed.Simulation experiments verify the superiority of the proposed method.Finally,the proposed method is applied to transformer detection.The proposed method determines the class members of transformers and meters in the actual transformer area,and obtains results consistent with actual user-transformer relations.This fully shows that the proposed method has practical application value.

关 键 词：User-transformer relation identification zero-crossing shift fuzzy C-means clustering quantum particle swarm optimization attractor multiple update strategy dynamic crossover strategy perturbation strategy of potential-well characteristic length 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]