{"title":"新一代智能电网停电分析的粒子群算法","authors":"Zhe Chen, A. Chegu","doi":"10.1109/TDC.2012.6281650","DOIUrl":null,"url":null,"abstract":"Smart Grid realization has been an ultimate goal for the power research community. The goal makes it necessary to incorporate the advanced algorithm and new technologies to make the power system more robust and secure. In order to reduce system-wide blackouts, high order contingency has to be analyzed and extensive work has been performed on N-k contingency studies. This paper proposes to use the Artificial Intelligence algorithm Particle Swarm Optimization (PSO) in solving cascading power outage failure problems, identifying potential risk, quantifying fitness results, and providing important guidance for system operators and business owners to make informed decisions.","PeriodicalId":19873,"journal":{"name":"PES T&D 2012","volume":"11 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Particle Swarm Optimization for next generation Smart Grid outage analyses\",\"authors\":\"Zhe Chen, A. Chegu\",\"doi\":\"10.1109/TDC.2012.6281650\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Smart Grid realization has been an ultimate goal for the power research community. The goal makes it necessary to incorporate the advanced algorithm and new technologies to make the power system more robust and secure. In order to reduce system-wide blackouts, high order contingency has to be analyzed and extensive work has been performed on N-k contingency studies. This paper proposes to use the Artificial Intelligence algorithm Particle Swarm Optimization (PSO) in solving cascading power outage failure problems, identifying potential risk, quantifying fitness results, and providing important guidance for system operators and business owners to make informed decisions.\",\"PeriodicalId\":19873,\"journal\":{\"name\":\"PES T&D 2012\",\"volume\":\"11 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"PES T&D 2012\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TDC.2012.6281650\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"PES T&D 2012","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TDC.2012.6281650","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Particle Swarm Optimization for next generation Smart Grid outage analyses
Smart Grid realization has been an ultimate goal for the power research community. The goal makes it necessary to incorporate the advanced algorithm and new technologies to make the power system more robust and secure. In order to reduce system-wide blackouts, high order contingency has to be analyzed and extensive work has been performed on N-k contingency studies. This paper proposes to use the Artificial Intelligence algorithm Particle Swarm Optimization (PSO) in solving cascading power outage failure problems, identifying potential risk, quantifying fitness results, and providing important guidance for system operators and business owners to make informed decisions.
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