{"title":"基于多智能体系统的配电网重构","authors":"C. Silva, Frederico Gadelha Guimarães","doi":"10.1109/BRICS-CCI-CBIC.2013.96","DOIUrl":null,"url":null,"abstract":"Power Distribution Network Reconfiguration demands the change of current state of the network in order to reach optimal operation according to some previouly defined figures of merit. This paper presents a new methodology based on Multi-Agent Systems for power distribution network reconfiguration aiming at minimizing power losses based on game theory. The principal characteristic of the game is the interpretation of the payoff matrix as having physical meaning. This way allowed better decisions to be taken in order to improve the overall performance of the network. Test cases with 100 buses/1 feeder and 83 buses/11 feeders in operation mode were taken as example of application of the proposed algorithm and to illustrate its success.","PeriodicalId":306195,"journal":{"name":"2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence","volume":"97 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Reconfiguration of Power Distribution Networks by Multi-agent Systems\",\"authors\":\"C. Silva, Frederico Gadelha Guimarães\",\"doi\":\"10.1109/BRICS-CCI-CBIC.2013.96\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Power Distribution Network Reconfiguration demands the change of current state of the network in order to reach optimal operation according to some previouly defined figures of merit. This paper presents a new methodology based on Multi-Agent Systems for power distribution network reconfiguration aiming at minimizing power losses based on game theory. The principal characteristic of the game is the interpretation of the payoff matrix as having physical meaning. This way allowed better decisions to be taken in order to improve the overall performance of the network. Test cases with 100 buses/1 feeder and 83 buses/11 feeders in operation mode were taken as example of application of the proposed algorithm and to illustrate its success.\",\"PeriodicalId\":306195,\"journal\":{\"name\":\"2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence\",\"volume\":\"97 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BRICS-CCI-CBIC.2013.96\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BRICS-CCI-CBIC.2013.96","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reconfiguration of Power Distribution Networks by Multi-agent Systems
Power Distribution Network Reconfiguration demands the change of current state of the network in order to reach optimal operation according to some previouly defined figures of merit. This paper presents a new methodology based on Multi-Agent Systems for power distribution network reconfiguration aiming at minimizing power losses based on game theory. The principal characteristic of the game is the interpretation of the payoff matrix as having physical meaning. This way allowed better decisions to be taken in order to improve the overall performance of the network. Test cases with 100 buses/1 feeder and 83 buses/11 feeders in operation mode were taken as example of application of the proposed algorithm and to illustrate its success.
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