Nationwide evaluation of energy and indoor air quality predictive control and impact on infection risk for cooling season
Building Simulation
; 16(2):205-223, 2023.
Article
in English
| Scopus | ID: covidwho-2246225
ABSTRACT
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. © 2022, Tsinghua University Press.
Air conditioning; Air quality; Indoor air pollution; Model predictive control; Probability; Ventilation; Energy; Energy savings; Energy usage; Energy-savings; Indoor air quality; Infection risk; Large scale simulations; Model-predictive control; Predictive control; Simulation studies; Energy conservation; energy-saving; large-scale simulation
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Experimental Studies
/
Prognostic study
Language:
English
Journal:
Building Simulation
Year:
2023
Document Type:
Article
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