Show simple item record

dc.contributor.authorLu, Shengze
dc.contributor.authorZhou, Shiyu
dc.contributor.authorDing, Yan
dc.contributor.authorKim, Moon Keun
dc.contributor.authorYang, Bin
dc.contributor.authorTian, Zhe
dc.contributor.authorLiu, Jiying
dc.date.accessioned2025-01-29T08:33:49Z
dc.date.available2025-01-29T08:33:49Z
dc.date.created2025-01-28T16:11:56Z
dc.date.issued2025
dc.identifier.issn2590-1230
dc.identifier.urihttps://hdl.handle.net/11250/3174966
dc.description.abstractWith the rapid development of the artificial intelligence (AI) technology, its application in optimizing heating, ventilation and air-conditioning (HVAC) systems operation is becoming increasingly widespread. This study reviews the latest advances in AI optimization for HVAC systems operation, systematically outlining the characteristics of the AI technology and its various application methods in air conditioning systems. The main features of the AI technology are first introduced. The main algorithms of supervised learning, reinforcement learning, and deep learning are then analyzed in the fields of air conditioning operation optimization, energy consumption prediction and control, indoor environmental protection, and fault detection and diagnosis. The combination of the AI and digital twin technologies is also explored. This review study focuses on the intelligent control technology, multi-objective optimization of system operation, system optimization based on occupant behavior and thermal comfort, and system fault detection and diagnosis. Although the AI technology has led to satisfactory results in air conditioning system optimization, its practical applications still face challenges, such as the model accuracy and generalization ability, applicability, and integration with existing systems. The analysis conducted in this paper provides a foundation for the optimization of HVAC system operation.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.ispartofseriesResults in Engineering (RINENG);
dc.rightsNavngivelse-Ikkekommersiell 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/deed.no*
dc.titleExploring the Comprehensive Integration of Artificial Intelligence in Optimizing HVAC System Operations: A Review and Future Outlooken_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1
dc.identifier.doihttps://doi.org/10.1016/j.rineng.2024.103765
dc.identifier.cristin2350477
dc.source.journalResults in Engineering (RINENG)en_US
dc.source.volume25en_US
dc.source.issue103765en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Navngivelse-Ikkekommersiell 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse-Ikkekommersiell 4.0 Internasjonal