Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/102815
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Building Environment and Energy Engineering | en_US |
| dc.contributor | Research Institute for Smart Energy | en_US |
| dc.creator | Li, W | en_US |
| dc.creator | Wang, S | en_US |
| dc.creator | Koo, C | en_US |
| dc.date.accessioned | 2023-11-17T02:57:58Z | - |
| dc.date.available | 2023-11-17T02:57:58Z | - |
| dc.identifier.issn | 0306-2619 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/102815 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Pergamon Press | en_US |
| dc.rights | © 2021 Elsevier Ltd. All rights reserved. | en_US |
| dc.rights | © 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/. | en_US |
| dc.rights | The following publication Li, W., Wang, S., & Koo, C. (2021). A real-time optimal control strategy for multi-zone VAV air-conditioning systems adopting a multi-agent based distributed optimization method. Applied Energy, 287, 116605 is available at https://doi.org/10.1016/j.apenergy.2021.116605. | en_US |
| dc.subject | Air-conditioning systems | en_US |
| dc.subject | Distributed optimal control | en_US |
| dc.subject | Energy efficiency | en_US |
| dc.subject | Indoor air quality | en_US |
| dc.subject | Multi-agent system | en_US |
| dc.subject | Thermal comfort | en_US |
| dc.title | A real-time optimal control strategy for multi-zone VAV air-conditioning systems adopting a multi-agent based distributed optimization method | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.volume | 287 | en_US |
| dc.identifier.doi | 10.1016/j.apenergy.2021.116605 | en_US |
| dcterms.abstract | Determining the proper trade-off among thermal comfort, Indoor Air Quality (IAQ) and energy use is important for optimal control of air-conditioning systems. The number of optimization variables increases as systems become increasingly complex, as with multi-zone VAV (Variable Air Volume) air-conditioning systems, leading to large-scale mathematics programming challenges and inconveniences in the implementation of conventional centralized optimization strategies. This paper therefore proposes a real-time optimal control strategy adopting a multi-agent based distributed optimization method for multi-zone VAV air-conditioning systems. The proposed strategy consists of three novel schemes. First, a temperature set-point reset scheme adopts a linear rule to correlate the resetting of the temperature set-points in individual zones to simplify the optimization problem while applying proper optimization in individual zones. Second, a multi-objective optimization scheme optimizes the fresh air ratio of the supply air and the temperature set-point in the critical zone by formulating the multi-objective optimization problem. Third, a multi-agent distributed optimization scheme is developed to solve the optimization problem in a distributed manner, facilitating the deployment of local control devices of limited capacity. A TRNSYS-MATLAB co-simulation testbed is constructed to test and validate the proposed strategy. Test results show that the strategy is effective in properly balancing thermal comfort, IAQ and energy use while largely reducing programming challenges. The distributed optimization method can provide almost the same optimal outputs as conventional centralized optimization methods. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Applied energy, 1 Apr. 2021, v. 287, 116605 | en_US |
| dcterms.isPartOf | Applied energy | en_US |
| dcterms.issued | 2021-04-01 | - |
| dc.identifier.scopus | 2-s2.0-85100650030 | - |
| dc.identifier.eissn | 1872-9118 | en_US |
| dc.identifier.artn | 116605 | en_US |
| dc.description.validate | 202310 bckw | en_US |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | BEEE-0104 | - |
| dc.description.fundingSource | RGC | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.identifier.OPUS | 56346530 | - |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Li_Real-Time_Optimal_Control.pdf | Pre-Published version | 2.15 MB | Adobe PDF | View/Open |
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