<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zuhaina Zakaria</style></author><author><style face="normal" font="default" size="100%">K L Lo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Two-Stage Fuzzy Clustering Approach for Load Profiling</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 44th International Universities Power Engineering Conference</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Operation of future power systems</style></keyword><keyword><style  face="normal" font="default" size="100%">Power System Simulation and Analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">September</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%"></style></number><edition><style face="normal" font="default" size="100%"></style></edition><publisher><style face="normal" font="default" size="100%"></style></publisher><pub-location><style face="normal" font="default" size="100%">University of Strathclyde</style></pub-location><volume><style face="normal" font="default" size="100%"></style></volume><pages><style face="normal" font="default" size="100%"></style></pages><isbn><style face="normal" font="default" size="100%"></style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Load profiling is a process to estimate consumers load profile in electricity industries. For many years, load profiles have been employed to provide information for forecasting, system planning and demand side planning. However, in the current deregulated environment, there is a growing interest in understanding the nature of variations in load shape to facilitate electricity supplier in their marketing strategy. The determination of customer load profile will provide utility companies with better marketing strategies and improved efficiency in operating the existent facilities. This paper presents a two-stage clustering technique based on fuzzy c-means (FCM) to determine consumers load profiles. The load data used in this work are from actual measurements from different feeders derived from a distribution network. Cluster validity indices will be used to determine the best cluster number. This paper also proposed quantile-quantile plot to validate the results from re-clustering process.</style></abstract><issue><style face="normal" font="default" size="100%"></style></issue><work-type><style face="normal" font="default" size="100%"></style></work-type><accession-num><style face="normal" font="default" size="100%"></style></accession-num><call-num><style face="normal" font="default" size="100%"></style></call-num><notes><style face="normal" font="default" size="100%"></style></notes><custom1><style face="normal" font="default" size="100%"></style></custom1><custom2><style face="normal" font="default" size="100%"></style></custom2><custom3><style face="normal" font="default" size="100%"></style></custom3><custom4><style face="normal" font="default" size="100%"></style></custom4><custom5><style face="normal" font="default" size="100%"></style></custom5><custom6><style face="normal" font="default" size="100%"></style></custom6><custom7><style face="normal" font="default" size="100%"></style></custom7><research-notes><style face="normal" font="default" size="100%"></style></research-notes><num-vols><style face="normal" font="default" size="100%"></style></num-vols><orig-pub><style face="normal" font="default" size="100%"></style></orig-pub><reprint-edition><style face="normal" font="default" size="100%"></style></reprint-edition><section><style face="normal" font="default" size="100%"></style></section><auth-address><style face="normal" font="default" size="100%"></style></auth-address><remote-database-name><style face="normal" font="default" size="100%"></style></remote-database-name><remote-database-provider><style face="normal" font="default" size="100%"></style></remote-database-provider><label><style face="normal" font="default" size="100%"></style></label><access-date><style face="normal" font="default" size="100%"></style></access-date></record></records></xml>
