Recursion based contingency analysis of an electrical power system

S. Gusev, V. Oboskalov
{"title":"Recursion based contingency analysis of an electrical power system","authors":"S. Gusev, V. Oboskalov","doi":"10.1109/INDEL.2016.7797797","DOIUrl":null,"url":null,"abstract":"Large computational load is one of the key issues of an electrical power system security analysis. Currently, most of the researchers are trying to find out how to reduce the computational load. The contingency analysis is one of the most promising approaches for solving the problem. In fact, there are several ways to improve the effectiveness of the contingency analysis. The first way is to reduce the number of simulated situations via contingency searching or contingency screening. Another way is to increase the efficiency of power flow computations. This paper presents a novel recursion-based approach for solving the contingency analysis problem. The approach improves the effectiveness of the contingency analysis by the above-mentioned ways. It relies on a specific contingency sorting procedure based on the recursive call of the calculating procedure. The proposed approach has been tested on the 14-bus IEEE test system. The results obtained show almost a twofold increase in the computational efficiency in comparison with the conventional contingency sorting procedure.","PeriodicalId":273613,"journal":{"name":"2016 International Symposium on Industrial Electronics (INDEL)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Symposium on Industrial Electronics (INDEL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDEL.2016.7797797","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Large computational load is one of the key issues of an electrical power system security analysis. Currently, most of the researchers are trying to find out how to reduce the computational load. The contingency analysis is one of the most promising approaches for solving the problem. In fact, there are several ways to improve the effectiveness of the contingency analysis. The first way is to reduce the number of simulated situations via contingency searching or contingency screening. Another way is to increase the efficiency of power flow computations. This paper presents a novel recursion-based approach for solving the contingency analysis problem. The approach improves the effectiveness of the contingency analysis by the above-mentioned ways. It relies on a specific contingency sorting procedure based on the recursive call of the calculating procedure. The proposed approach has been tested on the 14-bus IEEE test system. The results obtained show almost a twofold increase in the computational efficiency in comparison with the conventional contingency sorting procedure.
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
基于递归的电力系统偶然性分析
大计算负荷是电力系统安全分析的关键问题之一。目前,大多数研究人员都在试图找到减少计算负荷的方法。权变分析是解决这一问题最有前途的方法之一。实际上,有几种方法可以提高权变分析的有效性。第一种方法是通过偶然性搜索或偶然性筛选来减少模拟情景的数量。另一种方法是提高潮流计算的效率。本文提出了一种新的基于递归的权变分析方法。该方法提高了上述方法的权变分析的有效性。它依赖于基于计算过程递归调用的特定偶然性排序过程。该方法已在14总线IEEE测试系统上进行了测试。所得结果表明,与传统的偶然性排序过程相比,计算效率几乎提高了两倍。
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
Start-up vibration analysis for novelty detection on industrial gas turbines Modeling and analysis of DC-DC SEPIC converter with coupled inductors Software tools in electronics — Experiences from teaching the course A neuro-adaptive control of nonlinear slow processes On the importance of electromagnetic models in RFIC design
×
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