Probabilistic Load Flow Using Point Estimate Method Based on Nataf Transformation for Active Distribution Network

Youlin Bai
{"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}
引用次数: 0

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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于Nataf变换的有功配电网概率潮流点估计方法
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。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Research on Parallel Data Mining Based on Spark Research and Development of a Portable Ultrasonic Device for Detecting Urine Volume Research on Data Transmission Simulation System Based on Computer 3D Simulation Technology Brain Tumor Prediction with LSTM Method CRIoU: A Complete and Relevant Bounding Box Regression Method
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1