Yingmeng Xiang, Lingfeng Wang, Nian Liu, Ruosong Xiao, K. Xie
{"title":"A resilient power system operation strategy considering presumed attacks","authors":"Yingmeng Xiang, Lingfeng Wang, Nian Liu, Ruosong Xiao, K. Xie","doi":"10.1109/PMAPS.2016.7764213","DOIUrl":null,"url":null,"abstract":"Power system operation is facing increasing cyber and physical attack risks and it is pressing to develop effective methods to improve the resiliency of electric power infrastructure against malicious attacks. In this study, a holistic resiliency framework is proposed by extending the conventional security-constrained optimal power flow analysis (SCOPF) to incorporate the presumed risk caused by the attacks. The improved solution method is studied by combining particle swarm optimization, primal-dual interior point (PDIP) method and parallel computing. The case studies conducted on IEEE 39-bus and 118-bus systems demonstrate the proposed SCOPF model is able to improve the resiliency of power system for the presumed attacks. This study can provide some meaningful insights on improving the power system operation resiliency.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"17 12","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PMAPS.2016.7764213","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Power system operation is facing increasing cyber and physical attack risks and it is pressing to develop effective methods to improve the resiliency of electric power infrastructure against malicious attacks. In this study, a holistic resiliency framework is proposed by extending the conventional security-constrained optimal power flow analysis (SCOPF) to incorporate the presumed risk caused by the attacks. The improved solution method is studied by combining particle swarm optimization, primal-dual interior point (PDIP) method and parallel computing. The case studies conducted on IEEE 39-bus and 118-bus systems demonstrate the proposed SCOPF model is able to improve the resiliency of power system for the presumed attacks. This study can provide some meaningful insights on improving the power system operation resiliency.
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