Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/102815
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dc.contributorDepartment of Building Environment and Energy Engineeringen_US
dc.contributorResearch Institute for Smart Energyen_US
dc.creatorLi, Wen_US
dc.creatorWang, Sen_US
dc.creatorKoo, Cen_US
dc.date.accessioned2023-11-17T02:57:58Z-
dc.date.available2023-11-17T02:57:58Z-
dc.identifier.issn0306-2619en_US
dc.identifier.urihttp://hdl.handle.net/10397/102815-
dc.language.isoenen_US
dc.publisherPergamon Pressen_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.rightsThe 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.subjectAir-conditioning systemsen_US
dc.subjectDistributed optimal controlen_US
dc.subjectEnergy efficiencyen_US
dc.subjectIndoor air qualityen_US
dc.subjectMulti-agent systemen_US
dc.subjectThermal comforten_US
dc.titleA real-time optimal control strategy for multi-zone VAV air-conditioning systems adopting a multi-agent based distributed optimization methoden_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume287en_US
dc.identifier.doi10.1016/j.apenergy.2021.116605en_US
dcterms.abstractDetermining 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.accessRightsopen accessen_US
dcterms.bibliographicCitationApplied energy, 1 Apr. 2021, v. 287, 116605en_US
dcterms.isPartOfApplied energyen_US
dcterms.issued2021-04-01-
dc.identifier.scopus2-s2.0-85100650030-
dc.identifier.eissn1872-9118en_US
dc.identifier.artn116605en_US
dc.description.validate202310 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberBEEE-0104-
dc.description.fundingSourceRGCen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS56346530-
dc.description.oaCategoryGreen (AAM)en_US
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