基于Nataf变换的有功配电网概率潮流点估计方法

Youlin Bai
{"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}
引用次数: 0

摘要

针对可再生能源资源与负荷的不确定性和相关性,提出了一种考虑输入变量间相关性的有功配电网概率潮流方法。首先分别建立不确定输入变量的概率模型,然后通过反Nataf变换将独立标准正态空间中的采样点转化为相应的非正态变量空间。其次,提出了改进的概率潮流方法,利用三点估计法和Nataf变换拟合各输出变量的概率分布。最后,通过IEEE 33总线配电系统的对比测试,验证了该算法的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信