{"title":"A network asset based probabilistic model of ground potential rise and touch voltage hazard profiles at MV substations","authors":"Matthew B. Bastian, W. Carman, D. Woodhouse","doi":"10.1109/DTEC.2016.7731278","DOIUrl":null,"url":null,"abstract":"A probabilistic model for predicting the expected touch voltage hazard profiles at HV/MV substations is presented. The model uses readily available asset information to analyse the MV network fed from the HV/MV substation. Probabilistic profiling of the expected magnitude, frequency and duration of typical ground faults on a given distribution network, provides quantitative information for use in determining the actual risk profile for the assets. This in turn helps asset owners demonstrate that they meet their duty of care in relation to ground fault related hazards. The model is applied to two example substations, generating a probabilistic profile for ground fault current, ground potential rise and the expected hazard ratio of expected touch voltages in relation to IEEE80 safety criteria across the range of simulated faults. The model output profiles for each HV/MV substation are then compared against profiles derived from seven years of recorded ground potential rise events during real ground faults.","PeriodicalId":417330,"journal":{"name":"2016 Down to Earth Conference (DTEC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Down to Earth Conference (DTEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DTEC.2016.7731278","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
A probabilistic model for predicting the expected touch voltage hazard profiles at HV/MV substations is presented. The model uses readily available asset information to analyse the MV network fed from the HV/MV substation. Probabilistic profiling of the expected magnitude, frequency and duration of typical ground faults on a given distribution network, provides quantitative information for use in determining the actual risk profile for the assets. This in turn helps asset owners demonstrate that they meet their duty of care in relation to ground fault related hazards. The model is applied to two example substations, generating a probabilistic profile for ground fault current, ground potential rise and the expected hazard ratio of expected touch voltages in relation to IEEE80 safety criteria across the range of simulated faults. The model output profiles for each HV/MV substation are then compared against profiles derived from seven years of recorded ground potential rise events during real ground faults.