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dc.contributor.authorHosseini, Mohammad
dc.contributor.authorErba, Silvia
dc.contributor.authorHajialigol, Parisa
dc.contributor.authorAghaei, Mohammadreza
dc.contributor.authorMoazami, Amin
dc.contributor.authorNik, Vahid M.
dc.date.accessioned2024-09-12T12:42:35Z
dc.date.available2024-09-12T12:42:35Z
dc.date.created2024-03-15T13:52:40Z
dc.date.issued2024
dc.identifier.citationEnergy and Buildings. 2024, 308, 1-17.en_US
dc.identifier.issn0378-7788
dc.identifier.urihttps://hdl.handle.net/11250/3151915
dc.description.abstractThe combined challenge of climate change and population aging requires novel solutions that enhance the resilience of building energy systems and secure indoor comfort for vulnerable occupants in extreme weather conditions. This research investigates the performance of a newly developed Energy Management (EM) system based on Collective Intelligence (CI) and Reinforcement Learning (RL), called CIRLEM, managing the energy performance of an urban complex in Ålesund, Norway, including an elderly care center with decentralized PV generation, EV charging and storage, while connected to a main electricity grid. CIRLEM controls multiple flexibility assets including independent thermal zones (the demand-side agents) and Electric Vehicle (EV) charging stations (the local storage). In a novel approach, CIRLEM coordinates the distributed storage and generation together with the demand side to control energy systems and react collaboratively to environmental variations. Under extreme weather conditions, without applying CIRLEM, the demand can be more than double that of typical weather conditions. The implementation of the double-layer CIRLEM can reduce the total demand by 35 % over a month. Furthermore, the inclusion of photovoltaic (PV) systems allows the system to be independent from the grid for almost 40 % of its operational hours, while adding EV storage can increase it to around 70 %. Finally, the application of CIRLEM reduced overheating hours from 17 h °C to 2 h °C under extreme conditions, while maintaining comfortable conditions even during temperature ramps.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleEnhancing climate resilience in buildings using Collective Intelligence: A pilot study on a Norwegian elderly care centeren_US
dc.title.alternativeEnhancing climate resilience in buildings using Collective Intelligence: A pilot study on a Norwegian elderly care centeren_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber1-17en_US
dc.source.volume308en_US
dc.source.journalEnergy and Buildingsen_US
dc.identifier.doi10.1016/j.enbuild.2024.114030
dc.identifier.cristin2254879
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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