{"title":"办公楼优化运行的随机模型预测控制","authors":"","doi":"10.1016/j.buildenv.2024.112248","DOIUrl":null,"url":null,"abstract":"<div><div>This paper developed a novel stochastic model predictive control (SMPC) strategy to enhance the operational efficiency of office buildings. Firstly, an improved state space model encompassing temperature and relative humidity simultaneously is developed to accurately characterize the thermal comfort condition within the office building. Then, given the obtained comprehensive model, a new SMPC approach is proposed based on chance constraints to minimize energy consumption while guaranteeing thermal comfort for occupants. Besides, the feasibility and stability properties of the SMPC are demonstrated theoretically. Finally, the proposed SMPC method is verified through a real office building located in Xi'an, China, and the result shows that compared to the conventional ON<img>OFF and MPC control strategies, the SMPC can achieve 39.1 % and 33.3 % energy-saving and less temperature and relative humidity requirement violations.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":null,"pages":null},"PeriodicalIF":7.1000,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Stochastic model predictive control for the optimal operation of office buildings\",\"authors\":\"\",\"doi\":\"10.1016/j.buildenv.2024.112248\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper developed a novel stochastic model predictive control (SMPC) strategy to enhance the operational efficiency of office buildings. Firstly, an improved state space model encompassing temperature and relative humidity simultaneously is developed to accurately characterize the thermal comfort condition within the office building. Then, given the obtained comprehensive model, a new SMPC approach is proposed based on chance constraints to minimize energy consumption while guaranteeing thermal comfort for occupants. Besides, the feasibility and stability properties of the SMPC are demonstrated theoretically. Finally, the proposed SMPC method is verified through a real office building located in Xi'an, China, and the result shows that compared to the conventional ON<img>OFF and MPC control strategies, the SMPC can achieve 39.1 % and 33.3 % energy-saving and less temperature and relative humidity requirement violations.</div></div>\",\"PeriodicalId\":9273,\"journal\":{\"name\":\"Building and Environment\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":7.1000,\"publicationDate\":\"2024-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Building and Environment\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0360132324010904\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CONSTRUCTION & BUILDING TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Building and Environment","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0360132324010904","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
Stochastic model predictive control for the optimal operation of office buildings
This paper developed a novel stochastic model predictive control (SMPC) strategy to enhance the operational efficiency of office buildings. Firstly, an improved state space model encompassing temperature and relative humidity simultaneously is developed to accurately characterize the thermal comfort condition within the office building. Then, given the obtained comprehensive model, a new SMPC approach is proposed based on chance constraints to minimize energy consumption while guaranteeing thermal comfort for occupants. Besides, the feasibility and stability properties of the SMPC are demonstrated theoretically. Finally, the proposed SMPC method is verified through a real office building located in Xi'an, China, and the result shows that compared to the conventional ONOFF and MPC control strategies, the SMPC can achieve 39.1 % and 33.3 % energy-saving and less temperature and relative humidity requirement violations.
期刊介绍:
Building and Environment, an international journal, is dedicated to publishing original research papers, comprehensive review articles, editorials, and short communications in the fields of building science, urban physics, and human interaction with the indoor and outdoor built environment. The journal emphasizes innovative technologies and knowledge verified through measurement and analysis. It covers environmental performance across various spatial scales, from cities and communities to buildings and systems, fostering collaborative, multi-disciplinary research with broader significance.