Nationwide evaluation of energy and indoor air quality predictive control and impact on infection risk for cooling season  

作　　者：Xuezheng Wang Bing Dong Jianshun(Jensen)Zhang 

机构地区：[1]Department of Mechanical and Aerospace Engineering,Syracuse University,Syracuse,NY 13244,USA

出　　处：《Building Simulation》2023年第2期205-223,共19页建筑模拟（英文）

基　　金：This research was jointly sponsored by Honeywell International Inc.and Syracuse University.

摘　　要：Since the coronavirus disease 2019,the extended time indoors makes people more concerned about indoor air quality,while the increased ventilation in seeks of reducing infection probability has increased the energy usage from heating,ventilation,and air-conditioning systems.In this study,to represent the dynamics of indoor temperature and air quality,a coupled grey-box model is developed.The model is identified and validated using a data-driven approach and real-time measured data of a campus office.To manage building energy usage and indoor air quality,a model predictive control strategy is proposed and developed.The simulation study demonstrated 18.92%energy saving while maintaining good indoor air quality at the testing site.Two nationwide simulation studies assessed the overall energy saving potential and the impact on the infection probability of the proposed strategy in different climate zones.The results showed 20%–40%energy saving in general while maintaining a predetermined indoor air quality setpoint.Although the infection risk is increased due to the reduced ventilation rate,it is still less than the suggested threshold(2%)in general.

关 键 词：model predictive control indoor air quality infection risk ENERGY-SAVING large-scale simulation 

分 类 号：X51[环境科学与工程—环境工程]