Comparison of Multi-Control Strategies for the Control of Indoor Air Temperature and CO 2 with OpenModelica Modeling

Wei Wang, Xiaofang Shan, Syed Asad Hussain, Changshan Wang and Ying Ji
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Wei Wang: School of Architecture, Southeast University, Sipailou 2#, Xuanwu District, Nanjing 210096, China
Xiaofang Shan: School of Civil Engineering and Architecture, Wuhan University of Technology, No. 122 Luoshi Road, Wuhan 430070, China
Syed Asad Hussain: Department of Architecture and Civil Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong 999077, China
Changshan Wang: Nanjing Lvzhen Construction Technology Co., Ltd. Building 11, Qinhefang, Chunjiang New Town, Yuhuatai District, Nanjing 210096, China
Ying Ji: College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China

Energies, 2020, vol. 13, issue 17, 1-20

Abstract: As most residents spend more than 90% of their time in buildings, acceptable and reasonable control of both indoor thermal comfort and air quality is imperative to ensure occupants’ health status and work productivity. However, current control strategies generally take either thermal comfort or indoor air quality as a single loop, rather than the concurrent control of two. To analyze their mutual influence, this study investigated the performance of three multi-control approaches, i.e., proportional integral derivative (PID) control of thermal comfort and a fixed outdoor air ratio, PID control of thermal comfort and design outdoor air rate, and PID control of thermal comfort and occupancy-based demand-controlled ventilation. As a pilot study, three typical control methods were implemented to a multi-zone building via OpenModelica modeling. The results indicate that indoor air temperature can be well-maintained under three control methods, however, the CO 2 concentration under the fixed outdoor air ratio was over 1000 ppm, leading to poor indoor air quality. The control strategy with the design outdoor air rate could not properly ensure the CO 2 concentration, due to the over-ventilated or under-ventilated phenomena, subsequently resulting in unnecessary energy waste. The occupancy-based demand controlled ventilation could maintain the CO 2 concentration under the set-point with an intermediate power energy utilization.

Keywords: thermal comfort; indoor air quality; multi-control strategies; energy use; OpenModelica modeling (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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