{"title":"Multi-objective optimal analysis of comfort and energy management for intelligent buildings","authors":"Nan Wang, F. Fang, M. Feng","doi":"10.1109/CCDC.2014.6852646","DOIUrl":null,"url":null,"abstract":"Building energy consumption and human comfort are two major but often contradictory themes in modern building management. To alleviate the contradiction between the two themes, multi-objective optimization methods are always introduced. In this paper, three indexes, thermal comfort, visual comfort and indoor air quality (IAQ) are integrated to evaluate the indoor comfort. Based on a multi-agent structure, a model including comfort function and energy function is proposed. The multi-objective genetic algorithm is used to optimize the energy and comfort targets. And the Pareto optimal solution and its sensitivity analysis are discussed under several cases.","PeriodicalId":380818,"journal":{"name":"The 26th Chinese Control and Decision Conference (2014 CCDC)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 26th Chinese Control and Decision Conference (2014 CCDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2014.6852646","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
Abstract
Building energy consumption and human comfort are two major but often contradictory themes in modern building management. To alleviate the contradiction between the two themes, multi-objective optimization methods are always introduced. In this paper, three indexes, thermal comfort, visual comfort and indoor air quality (IAQ) are integrated to evaluate the indoor comfort. Based on a multi-agent structure, a model including comfort function and energy function is proposed. The multi-objective genetic algorithm is used to optimize the energy and comfort targets. And the Pareto optimal solution and its sensitivity analysis are discussed under several cases.