Distributed model predictive control for central heating of high-rise residential buildings
Central heating system faults affect building energy consumption and indoor thermal comfort significantly. To aim at the balance between thermal comfortable and energy-saving of the heating system for high-rise residential buildings, this paper proposes a method for the central heating system of hig...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2022-11-01
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| Series: | Journal of Asian Architecture and Building Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/13467581.2021.1987245 |
| _version_ | 1797960622820818944 |
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| author | Zhou Meng YU Junqi Zhao Anjun |
| author_facet | Zhou Meng YU Junqi Zhao Anjun |
| author_sort | Zhou Meng |
| collection | DOAJ |
| description | Central heating system faults affect building energy consumption and indoor thermal comfort significantly. To aim at the balance between thermal comfortable and energy-saving of the heating system for high-rise residential buildings, this paper proposes a method for the central heating system of high-rise residential buildings based on distributed model predictive control. The method analyzes the coupling factors between adjacent rooms’ temperature. Based on the state space method, a multivariable indoor temperature model is established and verified. The distributed model predictive control method is used to control and optimize the indoor temperature, and the load distribution of the circulating water pump in the heat exchange station is optimized according to the predicted heat demand. The results demonstrate that the indoor temperature after distributed model predictive control can stable near the set value. Compared with the centralized control methods, the proposed methodology can reduce energy consumption by 14.28%. Meanwhile, the efficiency of water pumps is increased by 16.74% after using the distributed control strategy. |
| first_indexed | 2024-04-11T00:49:11Z |
| format | Article |
| id | doaj.art-93cd46a14da141139b94a04919fa6206 |
| institution | Directory Open Access Journal |
| issn | 1347-2852 |
| language | English |
| last_indexed | 2024-04-11T00:49:11Z |
| publishDate | 2022-11-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Asian Architecture and Building Engineering |
| spelling | doaj.art-93cd46a14da141139b94a04919fa62062023-01-05T12:01:26ZengTaylor & Francis GroupJournal of Asian Architecture and Building Engineering1347-28522022-11-012162580259210.1080/13467581.2021.19872451987245Distributed model predictive control for central heating of high-rise residential buildingsZhou Meng0YU JunqiZhao AnjunXi’an University of Architecture and TechnologyCentral heating system faults affect building energy consumption and indoor thermal comfort significantly. To aim at the balance between thermal comfortable and energy-saving of the heating system for high-rise residential buildings, this paper proposes a method for the central heating system of high-rise residential buildings based on distributed model predictive control. The method analyzes the coupling factors between adjacent rooms’ temperature. Based on the state space method, a multivariable indoor temperature model is established and verified. The distributed model predictive control method is used to control and optimize the indoor temperature, and the load distribution of the circulating water pump in the heat exchange station is optimized according to the predicted heat demand. The results demonstrate that the indoor temperature after distributed model predictive control can stable near the set value. Compared with the centralized control methods, the proposed methodology can reduce energy consumption by 14.28%. Meanwhile, the efficiency of water pumps is increased by 16.74% after using the distributed control strategy.http://dx.doi.org/10.1080/13467581.2021.1987245high-rise residential buildingcentral heating systemdistributed controlindoor temperaturemodel predictive control |
| spellingShingle | Zhou Meng YU Junqi Zhao Anjun Distributed model predictive control for central heating of high-rise residential buildings Journal of Asian Architecture and Building Engineering high-rise residential building central heating system distributed control indoor temperature model predictive control |
| title | Distributed model predictive control for central heating of high-rise residential buildings |
| title_full | Distributed model predictive control for central heating of high-rise residential buildings |
| title_fullStr | Distributed model predictive control for central heating of high-rise residential buildings |
| title_full_unstemmed | Distributed model predictive control for central heating of high-rise residential buildings |
| title_short | Distributed model predictive control for central heating of high-rise residential buildings |
| title_sort | distributed model predictive control for central heating of high rise residential buildings |
| topic | high-rise residential building central heating system distributed control indoor temperature model predictive control |
| url | http://dx.doi.org/10.1080/13467581.2021.1987245 |
| work_keys_str_mv | AT zhoumeng distributedmodelpredictivecontrolforcentralheatingofhighriseresidentialbuildings AT yujunqi distributedmodelpredictivecontrolforcentralheatingofhighriseresidentialbuildings AT zhaoanjun distributedmodelpredictivecontrolforcentralheatingofhighriseresidentialbuildings |