Event‐triggered distributed model predictive control scheme for temperature regulation in multi‐zone air conditioning systems with improved indoor thermal preference indicator

Summary Driven by the increasing needs in multi‐zone buildings for reducing the air conditioning (A/C) system related energy consumption and increasing the occupants' thermal comfort, an event‐triggered distributed model predictive control (DMPC) scheme for building temperature regulation with...

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Veröffentlicht in:International journal of adaptive control and signal processing Jg. 37; H. 6; S. 1389 - 1409
Hauptverfasser: Gao, Jingjing, Yang, Xu, Zhang, Shilong, Tu, Rang, Ma, Hongjun
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Bognor Regis Wiley Subscription Services, Inc 01.06.2023
Schlagworte:
Air conditioning
Algorithms
distributed consensus algorithm
Energy consumption
event‐triggered distributed model predictive control
improved indoor thermal preference indicator
multi‐zone air conditioning system
Predictive control
Thermal comfort
ISSN:0890-6327, 1099-1115
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Zusammenfassung:Summary Driven by the increasing needs in multi‐zone buildings for reducing the air conditioning (A/C) system related energy consumption and increasing the occupants' thermal comfort, an event‐triggered distributed model predictive control (DMPC) scheme for building temperature regulation with improved indoor thermal preference indicator is proposed. To this end, a temperature‐energy model of the A/C system in a zone which considers multiple types of heat transfer, and the system model of the multi‐zone A/C system are derived first. On this basis, an improved indoor thermal preference indicator that trades off the A/C systems related energy consumption with the aggregate thermal comfort of the occupants is proposed for the multi‐zone A/C system, then the optimal indoor temperature set‐points for each zone are determined by using the distributed consensus algorithm. It is followed by an event‐triggered DMPC scheme by adjusting the A/C systems to arrive at the optimal indoor temperature set‐points for all the zones with lower communication and computation load. The performance and effectiveness of the proposed methods are demonstrated through a case study on an actual multi‐zone A/C system.
Bibliographie:Funding information
Beijing Natural Science Foundation, China, Grant/Award Number: 4212040; Interdisciplinary Research Project for Young Teachers of USTB (Fundamental Research Funds for the Central Universities), Grant/Award Number: FRF‐IDRY‐19‐015; National Natural Science Foundation of China, Grant/Award Number: 61873306
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ISSN:0890-6327
1099-1115
DOI:10.1002/acs.3578