Jie Cai, Donghun Kim, V. Putta, J. Braun, Jianghai Hu
{"title":"Multi-agent control for centralized air conditioning systems serving multi-zone buildings","authors":"Jie Cai, Donghun Kim, V. Putta, J. Braun, Jianghai Hu","doi":"10.1109/ACC.2015.7170862","DOIUrl":null,"url":null,"abstract":"Coordinating different components in a complex air conditioning system is challenging for centralized controls due to the large number of optimization variables. In this scenario, de-centralized controls are more appropriate alternatives. This study proposes a multi-agent control methodology for the optimal control of centralized air conditioning systems that are typically adopted in multi-zone commercial buildings. A hierarchical multi-agent framework is developed in which the agents cooperate to find the optimal operating point. Two consensus-based distributed optimization algorithms are formulated for this specific type of problem, which form the underlying mechanism of intra-agent optimization and inter-agent cooperation. Finally, a 3-zone building case study is used to demonstrate the performance of the proposed approach.","PeriodicalId":223665,"journal":{"name":"2015 American Control Conference (ACC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 American Control Conference (ACC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACC.2015.7170862","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21
Abstract
Coordinating different components in a complex air conditioning system is challenging for centralized controls due to the large number of optimization variables. In this scenario, de-centralized controls are more appropriate alternatives. This study proposes a multi-agent control methodology for the optimal control of centralized air conditioning systems that are typically adopted in multi-zone commercial buildings. A hierarchical multi-agent framework is developed in which the agents cooperate to find the optimal operating point. Two consensus-based distributed optimization algorithms are formulated for this specific type of problem, which form the underlying mechanism of intra-agent optimization and inter-agent cooperation. Finally, a 3-zone building case study is used to demonstrate the performance of the proposed approach.