LOW-VOLTAGLOW-VOLTAGE AREA PREDICTION MODEL RESEARCH BASED ON SELF-ORGANIZING COMPETITIVE NEURAL NETWORK

摘要：

　　The distribution network voltage level is directly related to residents normal use of electricity,in order to correctly predict the low-voltage distribution network voltage quality,to take timely and effective means to prevent low-voltage phenomenon,the article collects nine indicators to reflect the characteristics of low-voltage distribution network voltage quality which are mainline diameter,mainline type,branch line diameter,branch line type,power supply radius,distribution transformer capacity -load ratio,the threephase load unbalance rate,single-phase-home number,reactive power compensation rate.Then the article establishes a self-organizing competitive neural network model to automatic cluster the samples into three kinds which are normal,existing low voltage risk and existing severe low voltage risk.Using the known practical result to compare with the calculation results will indicate that the network model has high accuracy and feasibility.

关键词： Voltage quality self-organizing competitive neural network low-voltage of distribution network automatic clustering

作者: ZHANG Ying ZHANG Shu-xin RU Wei-kang WU Cai-biao CHEN Yong

作者单位: Qingpu Power Supply Company,SMEPC,No.6155 Waiqingsong Road Qingpu Shanghai China

会议类型: 国际会议

会议名称: 第五届中国国际供电会议(GIRED)

会议地点: 上海

会议语种:英文

页码: 1-5

在线出版日期: 2012-09-05（万方平台首次上网日期，不代表论文的发表时间）