Power Grid Optimal Topology Control Considering Correlations of System Uncertainties

Mohannad Alhazmi, P. Dehghanian, Shiyuan Wang, B. Shinde
{"title":"Power Grid Optimal Topology Control Considering Correlations of System Uncertainties","authors":"Mohannad Alhazmi, P. Dehghanian, Shiyuan Wang, B. Shinde","doi":"10.1109/ICPS.2019.8733326","DOIUrl":null,"url":null,"abstract":"This paper presents a probabilistic formulation and solution technique for the application of DC optimal power flow (DCOPF)-based network topology control through the transmission line switching strategies. Efficient utilization of the point estimation method (PEM) is pursued to model the system uncertainties, i.e., the stochastic load profile and the intermittent renewable generation. In order to address the computational effectiveness of the suggested probabilistic methodology, the PEM formulation is harnessed by a scenario reduction approach to capture the correlations of the system uncertainties, thereby achieving a more robust and faster operation solution for day-ahead and real-time applications. The proposed approach is applied to a modified IEEE 118-bus test system, where it demonstrates its attractive performance under different test scenarios.","PeriodicalId":160476,"journal":{"name":"2019 IEEE/IAS 55th Industrial and Commercial Power Systems Technical Conference (I&CPS)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE/IAS 55th Industrial and Commercial Power Systems Technical Conference (I&CPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPS.2019.8733326","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20

Abstract

This paper presents a probabilistic formulation and solution technique for the application of DC optimal power flow (DCOPF)-based network topology control through the transmission line switching strategies. Efficient utilization of the point estimation method (PEM) is pursued to model the system uncertainties, i.e., the stochastic load profile and the intermittent renewable generation. In order to address the computational effectiveness of the suggested probabilistic methodology, the PEM formulation is harnessed by a scenario reduction approach to capture the correlations of the system uncertainties, thereby achieving a more robust and faster operation solution for day-ahead and real-time applications. The proposed approach is applied to a modified IEEE 118-bus test system, where it demonstrates its attractive performance under different test scenarios.
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
考虑系统不确定性相关性的电网最优拓扑控制
本文提出了基于直流最优潮流(DCOPF)的网络拓扑控制通过传输线交换策略应用的概率公式和求解技术。有效地利用点估计方法(PEM)来建模系统的不确定性,即随机负荷分布和间歇性可再生能源发电。为了解决建议的概率方法的计算效率,PEM公式通过场景简化方法来捕获系统不确定性的相关性,从而为提前和实时应用实现更健壮和更快的操作解决方案。将该方法应用于改进的IEEE 118总线测试系统,在不同的测试场景下证明了该方法具有良好的性能。
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
A Multi-stage Dynamic Equivalent Modeling of a Wind Farm for the Smart Grid Development Frequency-Selective Grounding for 3ϕ Power Transformers The Design of a Holistic IoT-Based Monitoring System for a Wind Turbine Stochastic Multi-objective Economic/Emission Energy Management of a Microgrid in Presence of Combined Heat and Power Systems Multi-objective Coordinated Energy Dispatch and Voyage Scheduling for a Multi-energy Cruising Ship
×
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