{"title":"Approximation of the Time Alignment Error for Measurements in Electricity Grids","authors":"Imad Antonios, H. Schwefel, L. Lipsky","doi":"10.1109/EDCC.2019.00038","DOIUrl":null,"url":null,"abstract":"Measurements of parameters in electricity grids are frequently captured as average values over some time interval. In scenarios of distributed measurements such as in distribution grids, offsets of local clocks can result in misaligned averaging intervals. This paper investigates the properties of the so-called time alignment error of such measurands that is caused by shifts of the averaging interval. We extend a previously derived Markov-modulated model and provide an approximation of the variance of the time alignment error. The model accounts for slow-decaying correlation structure found in actual traces of electrical measures. We compare results of three electrical measures for 20 traces with numerical results and simulations from the the fitted Markov model.","PeriodicalId":334498,"journal":{"name":"2019 15th European Dependable Computing Conference (EDCC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 15th European Dependable Computing Conference (EDCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EDCC.2019.00038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Measurements of parameters in electricity grids are frequently captured as average values over some time interval. In scenarios of distributed measurements such as in distribution grids, offsets of local clocks can result in misaligned averaging intervals. This paper investigates the properties of the so-called time alignment error of such measurands that is caused by shifts of the averaging interval. We extend a previously derived Markov-modulated model and provide an approximation of the variance of the time alignment error. The model accounts for slow-decaying correlation structure found in actual traces of electrical measures. We compare results of three electrical measures for 20 traces with numerical results and simulations from the the fitted Markov model.