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Context analysis in energy resource management residential buildings

2017Conference object Open access
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dc.contributor.authorMadureira, Bruno
dc.contributor.authorPinto, Tiago
dc.contributor.authorFernandes, Filipe
dc.contributor.authorVale, Zita
dc.date.accessioned2021-03-09T14:33:37Z
dc.date.available2021-03-09T14:33:37Z
dc.date.issued2017
dc.description.abstractThis paper presents a context analysis methodology to improve the management of residential energy resources by making the decision making process adaptive to different contexts. A context analysis model is proposed and described, using a clustering process to group similar situations. Several clustering quality assessment indices, which support the decisions on how many clusters should be created in each run, are also considered, namely: the Calinski Harabasz, Davies Bouldin, Gap Value and Silhouette. Results show that the application of the proposed model allows to identify different contexts by finding patterns of devices' use and also to compare different optimal k criteria. The data used in this case study represents the energy consumption of a generic home during one year (2014) and features the measurements of several devices' consumption as well as of several contextual variables. The proposed method enhances the energy resource management through adaptation to different contexts.pt_PT
dc.description.sponsorshipThe present work was done and funded in the scope of the following projects: European Union's Horizon 2020 research and innovation programme, under the Marie Sklodowska-Curie grant agreement No 703689 (project ADAPT); EUREKA - ITEA2 Project M2MGrids (ITEA-13011), Project SIMOCE (ANI|P2020 17690), and has received funding from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1109/PTC.2017.7981222pt_PT
dc.identifier.isbn978-1-5090-4237-1
dc.identifier.urihttp://hdl.handle.net/10400.22/17333
dc.language.isoengpt_PT
dc.publisherIEEEpt_PT
dc.relationAdaptive Decision support for Agents negotiation in electricity market and smart grid Power Transactions
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/7981222pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectArtificial intelligencept_PT
dc.subjectContext Analysispt_PT
dc.subjectData-Miningpt_PT
dc.subjectHouse Managamentpt_PT
dc.subjectResidential Energy Managementpt_PT
dc.titleContext analysis in energy resource management residential buildingspt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardTitleAdaptive Decision support for Agents negotiation in electricity market and smart grid Power Transactions
oaire.awardURIinfo:eu-repo/grantAgreement/EC/H2020/703689/EU
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FEEA%2F00760%2F2013/PT
oaire.citation.conferencePlaceManchester, UKpt_PT
oaire.citation.endPage6pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleIEEE Manchester PowerTech, 2017pt_PT
oaire.fundingStreamH2020
oaire.fundingStream5876
person.familyNamePinto
person.familyNameFernandes
person.familyNameVale
person.givenNameTiago
person.givenNameFilipe
person.givenNameZita
person.identifierR-000-T7J
person.identifier632184
person.identifier.ciencia-id2414-9B03-C4BB
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0001-8248-080X
person.identifier.orcid0000-0002-4642-6950
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridT-2245-2018
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id35219107600
person.identifier.scopus-author-id7004115775
project.funder.identifierhttp://doi.org/10.13039/501100008530
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameEuropean Commission
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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