{"title":"Wireless network performance for residential demand-side participation","authors":"S. Lai, G. Messier, H. Zareipour, C. H. Wai","doi":"10.1109/ISGTEUROPE.2010.5638892","DOIUrl":null,"url":null,"abstract":"In this paper, we investigate the performance of wireless technology for monitoring and controlling the electrical load of a residential neighborhood. An event-based power metering scheme is assumed where transmissions are sent only when a change occurs in household consumption. Analysis of highresolution, empirical data suggests that consumption transitions can be modeled as a Poisson process in the time-domain. A peer-to-peer 802.11 wireless network was simulated to determine latency between houses and a local sub-station. Probability distributions for monitoring and control traffic show that packet latency is exponential distributed and neighborhoods larger than 400 homes may not be able to respond within a fraction of the 60 Hz cycle.","PeriodicalId":267185,"journal":{"name":"2010 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISGTEUROPE.2010.5638892","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
In this paper, we investigate the performance of wireless technology for monitoring and controlling the electrical load of a residential neighborhood. An event-based power metering scheme is assumed where transmissions are sent only when a change occurs in household consumption. Analysis of highresolution, empirical data suggests that consumption transitions can be modeled as a Poisson process in the time-domain. A peer-to-peer 802.11 wireless network was simulated to determine latency between houses and a local sub-station. Probability distributions for monitoring and control traffic show that packet latency is exponential distributed and neighborhoods larger than 400 homes may not be able to respond within a fraction of the 60 Hz cycle.