Journal of South China University of Technology (Natural Science Edition) ›› 2016, Vol. 44 ›› Issue (4): 40-46.doi: 10.3969/j.issn.1000-565X.2016.04.007

• Power & Electrical Engineering • Previous Articles     Next Articles

Analysis Method of Practical Coefficient Based on Fuzzy Clustering

OUYANG Sen WU Yu-sheng Feng Tian-rui   

  1. School of Electric Power//Key Laboratory of Clean Energy Technology of Guangdong Province,South China University of Technology,Guangzhou 510640,Guangdong,China
  • Received:2015-06-01 Revised:2015-08-14 Online:2016-04-25 Published:2016-04-12
  • Contact: 欧阳森(1974-) ,男,博士,副研究员,主要从事电能质量、节能技术与智能电器等的研究. E-mail:ouyangs@scut.edu.cn
  • About author:欧阳森(1974-) ,男,博士,副研究员,主要从事电能质量、节能技术与智能电器等的研究.
  • Supported by:
    Supported by the Key Program of National Natural Science Foundation of China( 51377060) and the National Natural Science Foundation for Young Scholars of China( 61104181)

Abstract: Practical coefficient is usually applied to the selection of distribution transformer capacity for the business expending.As the existing practical coefficient selection methods with low flexibility are greatly affected by dataand do not take into consideration the load development feature,a method to analyze the practical coefficient based on fuzzy clustering is proposed.In this method,first,power usersare divided into such three types as business,house and industry,and the corresponding evaluation indexes,namely the load density,the annual growth rate of electricity consumption and the commission time of distribution transformer,are used to describe the power consumption level and its variation as well as the load development feature of power users.Then,a classification method of practical coefficient levels is designed based on the fuzzy clustering,which uses the three above-mentioned evaluation indexes to perform a fuzzy clustering for the coefficient level classification and determines the evaluation index and practical coefficient's central value of each classification.Finally,the level and value of the practical coefficient of a new power user are obtained according to the sum of the weighted distance between the index value and the central value of each classification.In addition,the effectiveness and practicability of the proposed method are verified through a case study.

Key words: practical coefficient, fuzzy clustering, central value, business expending