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Case based reasoning with expert system and swarm intelligence to determine energy reduction in buildings energy management

2017Journal article Open access
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dc.contributor.authorFaia, R.
dc.contributor.authorPinto, Tiago
dc.contributor.authorAbrishambaf, Omid
dc.contributor.authorFernandes, Filipe
dc.contributor.authorVale, Zita
dc.contributor.authorCorchado, Juan Manuel
dc.date.accessioned2021-03-09T14:57:31Z
dc.date.available2021-03-09T14:57:31Z
dc.date.issued2017
dc.description.abstractThis paper proposes a novel Case Based Reasoning (CBR) application for intelligent management of energy resources in residential buildings. The proposed CBR approach enables analyzing the history of previous cases of energy reduction in buildings, and using them to provide a suggestion on the ideal level of energy reduction that should be applied in the consumption of houses. The innovations of the proposed CBR model are the application of the k-Nearest Neighbors algorithm (k-NN) clustering algorithm to identify similar past cases, the adaptation of Particle Swarm Optimization (PSO) meta-heuristic optimization method to optimize the choice of the variables that characterize each case, and the development of expert systems to adapt and refine the final solution. A case study is presented, which considers a knowledge base containing a set of scenarios obtained from the consumption of a residential building. In order to provide a response for a new case, the proposed CBR application selects the most similar cases and elaborates a response, which is provided to the SCADA House Intelligent Management (SHIM) system as input data. SHIM uses this specification to determine the loads that should be reduced in order to fulfill the reduction suggested by the CBR approach. Results show that the proposed approach is capable of suggesting the most adequate levels of reduction for the considered house, without compromising the comfort of the users.pt_PT
dc.description.sponsorshipThis work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAMGO) and a grant agreement No 703689 (project ADAPT); and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1016/j.enbuild.2017.09.020pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/17338
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relationEnabling Demand Response for short and real-time Efficient And Market Based smart Grid Operation - An intelligent and real-time simulation approach
dc.relationAdaptive Decision support for Agents negotiation in electricity market and smart grid Power Transactions
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/abs/pii/S0378778817318170?via%3Dihubpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectArtificial intelligencept_PT
dc.subjectCase based reasoningpt_PT
dc.subjectDemand responsept_PT
dc.subjectEnergy efficiencypt_PT
dc.subjectIntelligent house energy managementpt_PT
dc.titleCase based reasoning with expert system and swarm intelligence to determine energy reduction in buildings energy managementpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleEnabling Demand Response for short and real-time Efficient And Market Based smart Grid Operation - An intelligent and real-time simulation approach
oaire.awardTitleAdaptive Decision support for Agents negotiation in electricity market and smart grid Power Transactions
oaire.awardURIinfo:eu-repo/grantAgreement/EC/H2020/641794/EU
oaire.awardURIinfo:eu-repo/grantAgreement/EC/H2020/703689/EU
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FEEA%2F00760%2F2013/PT
oaire.citation.endPage281pt_PT
oaire.citation.startPage269pt_PT
oaire.citation.titleEnergy and Buildingspt_PT
oaire.citation.volume155pt_PT
oaire.fundingStreamH2020
oaire.fundingStreamH2020
oaire.fundingStream5876
person.familyNameFaia
person.familyNamePinto
person.familyNameAbrishambaf
person.familyNameFernandes
person.familyNameVale
person.familyNameCorchado
person.givenNameRicardo Francisco Marcos
person.givenNameTiago
person.givenNameOmid
person.givenNameFilipe
person.givenNameZita
person.givenNameJuan Manuel
person.identifier78FtZwIAAAAJ
person.identifierR-000-T7J
person.identifier632184
person.identifier.ciencia-id9B12-19F6-D6C7
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person.identifier.ciencia-id2B1C-3662-2BC9
person.identifier.orcid0000-0002-1053-7720
person.identifier.orcid0000-0001-8248-080X
person.identifier.orcid0000-0002-4249-8367
person.identifier.orcid0000-0002-4642-6950
person.identifier.orcid0000-0002-4560-9544
person.identifier.orcid0000-0002-2829-1829
person.identifier.ridT-2245-2018
person.identifier.ridA-5824-2012
person.identifier.ridD-3229-2013
person.identifier.scopus-author-id35219107600
person.identifier.scopus-author-id57189232486
person.identifier.scopus-author-id7004115775
person.identifier.scopus-author-id7006360842
project.funder.identifierhttp://doi.org/10.13039/501100008530
project.funder.identifierhttp://doi.org/10.13039/501100008530
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameEuropean Commission
project.funder.nameEuropean Commission
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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