Solving Uncertain Power Flow Problem by Affine Arithmetic

G. Coletta, A. Vaccaro, D. Villacci, A. Zollo
{"title":"Solving Uncertain Power Flow Problem by Affine Arithmetic","authors":"G. Coletta, A. Vaccaro, D. Villacci, A. Zollo","doi":"10.23919/AEIT.2018.8577403","DOIUrl":null,"url":null,"abstract":"Uncertainty management is becoming a very challenging tool in operation scheduling of networks interested by massive distributed generators' penetration. From this point of view, self-validated computing techniques are very useful tools, allowing to intrinsically track data uncertainty effects into power system operation procedures. In this field, the use of Affine Arithmetic has been demonstrated to be one of the most promising research direction, since it prevents the typical error explosion phenomena affecting the standard range arithmetic-based computing frameworks. Starting from these considerations, the aim of this paper is to investigate the Affine Arithmetic-based Power Flow problem, which, by mean of the uncertainty bounds characterization, can provide additional information to the system operators in their decision making processes. The methodology will be tested on the 30-bus IEEE test network and the results will be validated by application of traditional sampling-based techniques.","PeriodicalId":413577,"journal":{"name":"2018 AEIT International Annual Conference","volume":"290 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 AEIT International Annual Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/AEIT.2018.8577403","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Uncertainty management is becoming a very challenging tool in operation scheduling of networks interested by massive distributed generators' penetration. From this point of view, self-validated computing techniques are very useful tools, allowing to intrinsically track data uncertainty effects into power system operation procedures. In this field, the use of Affine Arithmetic has been demonstrated to be one of the most promising research direction, since it prevents the typical error explosion phenomena affecting the standard range arithmetic-based computing frameworks. Starting from these considerations, the aim of this paper is to investigate the Affine Arithmetic-based Power Flow problem, which, by mean of the uncertainty bounds characterization, can provide additional information to the system operators in their decision making processes. The methodology will be tested on the 30-bus IEEE test network and the results will be validated by application of traditional sampling-based techniques.
用仿射算法求解不确定潮流问题
由于分布式发电机组的大量渗透,不确定性管理已成为网络运行调度中一个非常具有挑战性的工具。从这个角度来看,自我验证的计算技术是非常有用的工具,可以从本质上跟踪电力系统运行过程中数据不确定性的影响。在该领域,使用仿射算法已被证明是最有前途的研究方向之一,因为它可以防止典型的误差爆炸现象影响基于标准距离算法的计算框架。从这些考虑出发,本文的目的是研究基于仿射算法的潮流问题,该问题通过不确定性边界的表征,可以为系统操作员的决策过程提供额外的信息。该方法将在30总线的IEEE测试网络上进行测试,并通过传统的基于采样的技术验证结果。
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 求助全文
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:604180095
Book学术官方微信