Yeyu Wu, Haihua Jiang, Weiming Chen, Junhui Fan, Bin Cao
{"title":"Overall and local environmental collaborative control based on personal comfort model and personal comfort system","authors":"Yeyu Wu, Haihua Jiang, Weiming Chen, Junhui Fan, Bin Cao","doi":"10.1016/j.apenergy.2024.123707","DOIUrl":null,"url":null,"abstract":"<div><p>Most methods for creating an indoor thermal environment are based on controlling heating, ventilation, and air conditioning (HVAC) systems and do not consider the various needs of individuals in a multiperson space. Personal comfort systems (PCS) and personal comfort models (PCM) are popular technologies for achieving personal thermal comfort. This paper presents a thermal environmental collaborative control system (TECCS) that regulates environments at different spatial scales by leveraging the advantages of the HVAC system, PCS, PCM, and PCM-based automatic control to address the issue of individual differences in thermal demand in multiperson environments. The TECCS predicts thermal sensation votes (TSV) by combining facial skin temperature data obtained by an infrared sensor with environmental parameters. Subsequently, it performs the corresponding PCS control and adjusts the air conditioner according to the operating state of the PCS. This study proposes a collaborative control strategy with PCS at the core, enabling communication between thermal state recognition, HVAC system, and PCS. Twenty-eight adult males participated in the experiments testing the TECCS's performance. The results indicate that the TECCS can automatically regulate environments at different spatial scales based on thermal sensation prediction and that the operating state of the PCS can effectively guide air conditioning operations. Compared with constant setpoint control, the TECCS offers the advantage of improving thermal comfort. This paper also proposes future optimization directions based on the research results, focusing on recognition, equipment, and control.</p></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":null,"pages":null},"PeriodicalIF":10.1000,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Energy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0306261924010900","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
Most methods for creating an indoor thermal environment are based on controlling heating, ventilation, and air conditioning (HVAC) systems and do not consider the various needs of individuals in a multiperson space. Personal comfort systems (PCS) and personal comfort models (PCM) are popular technologies for achieving personal thermal comfort. This paper presents a thermal environmental collaborative control system (TECCS) that regulates environments at different spatial scales by leveraging the advantages of the HVAC system, PCS, PCM, and PCM-based automatic control to address the issue of individual differences in thermal demand in multiperson environments. The TECCS predicts thermal sensation votes (TSV) by combining facial skin temperature data obtained by an infrared sensor with environmental parameters. Subsequently, it performs the corresponding PCS control and adjusts the air conditioner according to the operating state of the PCS. This study proposes a collaborative control strategy with PCS at the core, enabling communication between thermal state recognition, HVAC system, and PCS. Twenty-eight adult males participated in the experiments testing the TECCS's performance. The results indicate that the TECCS can automatically regulate environments at different spatial scales based on thermal sensation prediction and that the operating state of the PCS can effectively guide air conditioning operations. Compared with constant setpoint control, the TECCS offers the advantage of improving thermal comfort. This paper also proposes future optimization directions based on the research results, focusing on recognition, equipment, and control.
期刊介绍:
Applied Energy serves as a platform for sharing innovations, research, development, and demonstrations in energy conversion, conservation, and sustainable energy systems. The journal covers topics such as optimal energy resource use, environmental pollutant mitigation, and energy process analysis. It welcomes original papers, review articles, technical notes, and letters to the editor. Authors are encouraged to submit manuscripts that bridge the gap between research, development, and implementation. The journal addresses a wide spectrum of topics, including fossil and renewable energy technologies, energy economics, and environmental impacts. Applied Energy also explores modeling and forecasting, conservation strategies, and the social and economic implications of energy policies, including climate change mitigation. It is complemented by the open-access journal Advances in Applied Energy.