Rui Fan, Yong Li, Yijia Cao, Wei Xie, Yi Tan, Ye Cai
{"title":"An optimization management strategy for energy efficiency of air conditioning loads in smart building","authors":"Rui Fan, Yong Li, Yijia Cao, Wei Xie, Yi Tan, Ye Cai","doi":"10.1109/EEEIC.2016.7555507","DOIUrl":null,"url":null,"abstract":"With the technological development of the smart grid, the demand response technology will be developed to enhance the security, stability and economy of power system to a great extent. The air conditioning load, as a kind of temperature controlled load, is a typical load that can be used for demand response. In this paper, an optimization management strategy of the air conditioning load is proposed, which can adapt to the seasonal temperature changes and increase the energy efficiency of smart buildings. First, we divided the control mode into two parts for summer and winter respectively, aiming at the peak load shifting and smooth the load curve. Secondly, the controlling process block is embed into the terminal control platform; Finally, an experimental system of energy efficiency optimization management has been developed as shown in the demonstration project, which indicates the feasibility of proposed strategy for load scheduling.","PeriodicalId":246856,"journal":{"name":"2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EEEIC.2016.7555507","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
With the technological development of the smart grid, the demand response technology will be developed to enhance the security, stability and economy of power system to a great extent. The air conditioning load, as a kind of temperature controlled load, is a typical load that can be used for demand response. In this paper, an optimization management strategy of the air conditioning load is proposed, which can adapt to the seasonal temperature changes and increase the energy efficiency of smart buildings. First, we divided the control mode into two parts for summer and winter respectively, aiming at the peak load shifting and smooth the load curve. Secondly, the controlling process block is embed into the terminal control platform; Finally, an experimental system of energy efficiency optimization management has been developed as shown in the demonstration project, which indicates the feasibility of proposed strategy for load scheduling.