M. Stfelec, Andrea Zápotocká, P. Janeček, E. Janecek
{"title":"Probabilistic assessment of the impact of dispersed generation on voltage quality","authors":"M. Stfelec, Andrea Zápotocká, P. Janeček, E. Janecek","doi":"10.1109/RTUCON.2015.7343141","DOIUrl":null,"url":null,"abstract":"Dispersed generation sources are slowly penetrating into distribution power networks. Renewables represent the majority of newly installed energy sources, which are of stochastic nature. With this phenomenon, new technical challenges are rising up, where appropriate impact assessment of volatile dispersed generation on voltage quality stands for one of them. Current planning tools and optimization methods mostly rely on the deterministic key performance indicators (KPI), which assesses the power quality in a distribution network. These indicators may not be sufficient for power network with high presence of uncertainty. In this paper, power network model with emphasis on probabilistic description of power injections is described. Correlation among stochastic power injection is discussed and consequently this correlation is categorized into several groups. Main focus of the paper is on design of probabilistic key performance indicators for assessment of power quality in a distribution network. Two probabilistic load flow methods used for computation of introduced KPIs are presented and their performance is analyzed on selected test case. On the test case, KPIs evaluation is demonstrated and the results are analyzed.","PeriodicalId":389419,"journal":{"name":"2015 56th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 56th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTUCON.2015.7343141","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Dispersed generation sources are slowly penetrating into distribution power networks. Renewables represent the majority of newly installed energy sources, which are of stochastic nature. With this phenomenon, new technical challenges are rising up, where appropriate impact assessment of volatile dispersed generation on voltage quality stands for one of them. Current planning tools and optimization methods mostly rely on the deterministic key performance indicators (KPI), which assesses the power quality in a distribution network. These indicators may not be sufficient for power network with high presence of uncertainty. In this paper, power network model with emphasis on probabilistic description of power injections is described. Correlation among stochastic power injection is discussed and consequently this correlation is categorized into several groups. Main focus of the paper is on design of probabilistic key performance indicators for assessment of power quality in a distribution network. Two probabilistic load flow methods used for computation of introduced KPIs are presented and their performance is analyzed on selected test case. On the test case, KPIs evaluation is demonstrated and the results are analyzed.