{"title":"面向能源需求管理的快速精确分布式控制","authors":"J. Beal, J. Berliner, Kevin Hunter","doi":"10.1109/SASO.2012.12","DOIUrl":null,"url":null,"abstract":"Fast and precise demand shaping is critical for the electrical power grid. With residential and small-business customers, a distributed approach to demand shaping is desirable for reasons of scalability and of privacy. The Color Power architecture [1] provides such an approach, but the controller previously used was badly limited. We now present an improved control algorithm, Color Power 2.0, based on stochastic constraint satisfaction, which provides major improvements in capability and performance over the prior algorithm. Analysis shows that its performance is within a small constant factor of optimal, and these results are confirmed empirically on simulated networks of 100 to 1 million devices.","PeriodicalId":126067,"journal":{"name":"2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"28","resultStr":"{\"title\":\"Fast Precise Distributed Control for Energy Demand Management\",\"authors\":\"J. Beal, J. Berliner, Kevin Hunter\",\"doi\":\"10.1109/SASO.2012.12\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fast and precise demand shaping is critical for the electrical power grid. With residential and small-business customers, a distributed approach to demand shaping is desirable for reasons of scalability and of privacy. The Color Power architecture [1] provides such an approach, but the controller previously used was badly limited. We now present an improved control algorithm, Color Power 2.0, based on stochastic constraint satisfaction, which provides major improvements in capability and performance over the prior algorithm. Analysis shows that its performance is within a small constant factor of optimal, and these results are confirmed empirically on simulated networks of 100 to 1 million devices.\",\"PeriodicalId\":126067,\"journal\":{\"name\":\"2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems\",\"volume\":\"63 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"28\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SASO.2012.12\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SASO.2012.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fast Precise Distributed Control for Energy Demand Management
Fast and precise demand shaping is critical for the electrical power grid. With residential and small-business customers, a distributed approach to demand shaping is desirable for reasons of scalability and of privacy. The Color Power architecture [1] provides such an approach, but the controller previously used was badly limited. We now present an improved control algorithm, Color Power 2.0, based on stochastic constraint satisfaction, which provides major improvements in capability and performance over the prior algorithm. Analysis shows that its performance is within a small constant factor of optimal, and these results are confirmed empirically on simulated networks of 100 to 1 million devices.