{"title":"基于Nataf变换的有功配电网概率潮流点估计方法","authors":"Youlin Bai","doi":"10.1109/ISAIEE57420.2022.00026","DOIUrl":null,"url":null,"abstract":"To deal with the uncertainty and correlation of renewable energy resources and loads, a probabilistic load flow method for active distribution network considering the correlation between input variables is proposed. Firstly, the probabilistic models of uncertain input variables are established respectively, and then the sampling points in the independent standard normal space can be transformed into the relevant non-normal variable space through inverse Nataf transformation. Next, improved probabilistic load flow method using three-point estimate method with Nataf transformation is proposed to fit the probability distribution of each output variable. At last, accuracy of the proposed algorithm has been validated by the comparative tests in IEEE 33-bus distribution system.","PeriodicalId":345703,"journal":{"name":"2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Probabilistic Load Flow Using Point Estimate Method Based on Nataf Transformation for Active Distribution Network\",\"authors\":\"Youlin Bai\",\"doi\":\"10.1109/ISAIEE57420.2022.00026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To deal with the uncertainty and correlation of renewable energy resources and loads, a probabilistic load flow method for active distribution network considering the correlation between input variables is proposed. Firstly, the probabilistic models of uncertain input variables are established respectively, and then the sampling points in the independent standard normal space can be transformed into the relevant non-normal variable space through inverse Nataf transformation. Next, improved probabilistic load flow method using three-point estimate method with Nataf transformation is proposed to fit the probability distribution of each output variable. At last, accuracy of the proposed algorithm has been validated by the comparative tests in IEEE 33-bus distribution system.\",\"PeriodicalId\":345703,\"journal\":{\"name\":\"2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISAIEE57420.2022.00026\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISAIEE57420.2022.00026","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Probabilistic Load Flow Using Point Estimate Method Based on Nataf Transformation for Active Distribution Network
To deal with the uncertainty and correlation of renewable energy resources and loads, a probabilistic load flow method for active distribution network considering the correlation between input variables is proposed. Firstly, the probabilistic models of uncertain input variables are established respectively, and then the sampling points in the independent standard normal space can be transformed into the relevant non-normal variable space through inverse Nataf transformation. Next, improved probabilistic load flow method using three-point estimate method with Nataf transformation is proposed to fit the probability distribution of each output variable. At last, accuracy of the proposed algorithm has been validated by the comparative tests in IEEE 33-bus distribution system.