{"title":"住宅负荷管理中需求响应整合的在线框架","authors":"Shamwilu Ahmed, F. Bouffard","doi":"10.1109/EPEC.2017.8286202","DOIUrl":null,"url":null,"abstract":"In this paper we make use of demand response (DR) for economic and system reliability purposes. In particular, we focus on an incentive based program for residential consumers with the objective of matching a predetermined consumption profile to the aggregated demand to provide peak management and reduce cost from the market. The objective is to maintain the utility of consumers by rescheduling activities within a scheduling horizon. In addition we discuss extensions to the framework for improved reliability and generalization. The model is tested on peaking load periods for the Ontario power system. The results show that the proposed framework is able to match demand to a profile and thereby reduce operating costs.","PeriodicalId":141250,"journal":{"name":"2017 IEEE Electrical Power and Energy Conference (EPEC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"An online framework for integration of demand response in residential load management\",\"authors\":\"Shamwilu Ahmed, F. Bouffard\",\"doi\":\"10.1109/EPEC.2017.8286202\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we make use of demand response (DR) for economic and system reliability purposes. In particular, we focus on an incentive based program for residential consumers with the objective of matching a predetermined consumption profile to the aggregated demand to provide peak management and reduce cost from the market. The objective is to maintain the utility of consumers by rescheduling activities within a scheduling horizon. In addition we discuss extensions to the framework for improved reliability and generalization. The model is tested on peaking load periods for the Ontario power system. The results show that the proposed framework is able to match demand to a profile and thereby reduce operating costs.\",\"PeriodicalId\":141250,\"journal\":{\"name\":\"2017 IEEE Electrical Power and Energy Conference (EPEC)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE Electrical Power and Energy Conference (EPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EPEC.2017.8286202\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Electrical Power and Energy Conference (EPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EPEC.2017.8286202","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An online framework for integration of demand response in residential load management
In this paper we make use of demand response (DR) for economic and system reliability purposes. In particular, we focus on an incentive based program for residential consumers with the objective of matching a predetermined consumption profile to the aggregated demand to provide peak management and reduce cost from the market. The objective is to maintain the utility of consumers by rescheduling activities within a scheduling horizon. In addition we discuss extensions to the framework for improved reliability and generalization. The model is tested on peaking load periods for the Ontario power system. The results show that the proposed framework is able to match demand to a profile and thereby reduce operating costs.