{"title":"Stochastic dynamic power flow analysis based on stochastic response surfarce method and ARMA-GARCH model","authors":"Nhung Nguyen-Hong, Y. Nakanishi","doi":"10.1109/ISGT.2017.8086059","DOIUrl":null,"url":null,"abstract":"Nowadays, renewable energy has become a very viable alternative solution to provide electricity. However, the uncertainty of renewable energy changes traditional issues in operation and control of power system. This paper proposes a Stochastic Dynamic Power Flow Analysis to evaluate state variables' probability distribution at any time t. Stochastic process of renewable energy is modeled and simulated by ARMA-GARCH model. The Stochastic Response Surface Method is also applied to increase computational efficiency with the same accuracy as Monte Carlo simulation. Stochastic Dynamic Power Flow Analysis is applied to IEEE 30-bus system and time dependent probability distribution of voltage, frequency and network loss will be analyzed.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISGT.2017.8086059","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
Nowadays, renewable energy has become a very viable alternative solution to provide electricity. However, the uncertainty of renewable energy changes traditional issues in operation and control of power system. This paper proposes a Stochastic Dynamic Power Flow Analysis to evaluate state variables' probability distribution at any time t. Stochastic process of renewable energy is modeled and simulated by ARMA-GARCH model. The Stochastic Response Surface Method is also applied to increase computational efficiency with the same accuracy as Monte Carlo simulation. Stochastic Dynamic Power Flow Analysis is applied to IEEE 30-bus system and time dependent probability distribution of voltage, frequency and network loss will be analyzed.
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