{"title":"电力系统负荷管理中的服务延迟排队分析","authors":"Andrés Ferragut, F. Paganini","doi":"10.1109/ALLERTON.2015.7446990","DOIUrl":null,"url":null,"abstract":"With the advent of renewable sources and Smart-Grid deployments, it is increasingly common to control demands in order to reduce power consumption variability and thus the need for regulation, with load aggregators now exploiting the deferability of some power loads to smooth the consumption profile. In this paper, we analyze the impact of service deferrals and scheduling on power consumption variability using tools from queueing theory. We consider a generic model for a load aggregator that receive job requests, involving a certain amount of energy to be provided and a deadline. We analyze different scheduling policies and examine the impact of service deferrals, quantifying the tradeoff between variance reduction and attained deadlines.","PeriodicalId":112948,"journal":{"name":"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Queueing analysis of service deferrals for load management in power systems\",\"authors\":\"Andrés Ferragut, F. Paganini\",\"doi\":\"10.1109/ALLERTON.2015.7446990\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the advent of renewable sources and Smart-Grid deployments, it is increasingly common to control demands in order to reduce power consumption variability and thus the need for regulation, with load aggregators now exploiting the deferability of some power loads to smooth the consumption profile. In this paper, we analyze the impact of service deferrals and scheduling on power consumption variability using tools from queueing theory. We consider a generic model for a load aggregator that receive job requests, involving a certain amount of energy to be provided and a deadline. We analyze different scheduling policies and examine the impact of service deferrals, quantifying the tradeoff between variance reduction and attained deadlines.\",\"PeriodicalId\":112948,\"journal\":{\"name\":\"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ALLERTON.2015.7446990\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ALLERTON.2015.7446990","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Queueing analysis of service deferrals for load management in power systems
With the advent of renewable sources and Smart-Grid deployments, it is increasingly common to control demands in order to reduce power consumption variability and thus the need for regulation, with load aggregators now exploiting the deferability of some power loads to smooth the consumption profile. In this paper, we analyze the impact of service deferrals and scheduling on power consumption variability using tools from queueing theory. We consider a generic model for a load aggregator that receive job requests, involving a certain amount of energy to be provided and a deadline. We analyze different scheduling policies and examine the impact of service deferrals, quantifying the tradeoff between variance reduction and attained deadlines.