Repository logo
 
Publication

Energy Management in Smart Building by a Multi-Objective Optimization Model and Pascoletti-Serafini Scalarization Approach

2021Journal article Open access
Simple item page
dc.contributor.authorForoozandeh, Zahra
dc.contributor.authorRamos, Sérgio Filipe Carvalho
dc.contributor.authorSoares, João
dc.contributor.authorVale, Zita
dc.date.accessioned2021-09-17T14:08:09Z
dc.date.available2021-09-17T14:08:09Z
dc.date.issued2021
dc.description.abstractGenerally, energy management in smart buildings is formulated by mixed-integer linear programming, with different optimization goals. The most targeted goals are the minimization of the electricity consumption cost, the electricity consumption value from external power grid, and peak load smoothing. All of these objectives are desirable in a smart building, however, in most of the related works, just one of these mentioned goals is considered and investigated. In this work, authors aim to consider two goals via a multi-objective framework. In this regard, a multi-objective mixed-binary linear programming is presented to minimize the total energy consumption cost and peak load in collective residential buildings, considering the scheduling of the charging/discharging process for electric vehicles and battery energy storage system. Then, the Pascoletti-Serafini scalarization approach is used to obtain the Pareto front solutions of the presented multi-objective model. In the final, the performance of the proposed model is analyzed and reported by simulating the model under two different scenarios. The results show that the total consumption cost of the residential building has been reduced 35.56% and the peak load has a 45.52% reductionpt_PT
dc.description.sponsorshipThis work has received funding from FEDER Funds through COMPETE program and from National Funds through FCT under the project BENEFICE–PTDC/EEI-EEE/29070/2017 and UIDB/00760/2020 under CEECIND/02814/2017 grantpt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.3390/pr9020257pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/18417
dc.language.isoengpt_PT
dc.publisherMDPIpt_PT
dc.relationBENEFICE–PTDC/EEI-EEE/29070/2017pt_PT
dc.relation.publisherversionhttps://www.mdpi.com/2227-9717/9/2/257pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectSmart buildingpt_PT
dc.subjectEnergy managementpt_PT
dc.subjectMulti-objective optimization problempt_PT
dc.subjectMixed binary linear programmingpt_PT
dc.subjectPascoletti-Serafini approachpt_PT
dc.subjectPareto frontpt_PT
dc.titleEnergy Management in Smart Building by a Multi-Objective Optimization Model and Pascoletti-Serafini Scalarization Approachpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/157466/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/PRAXIS XXI/4292/PT
oaire.citation.issue2pt_PT
oaire.citation.startPage257pt_PT
oaire.citation.titleProcessespt_PT
oaire.citation.volume9pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStreamPRAXIS XXI
person.familyNameforouzandehjouneghani
person.familyNameCarvalho Ramos
person.familyNameSoares
person.familyNameVale
person.givenNamezahra
person.givenNameSérgio Filipe
person.givenNameJoão
person.givenNameZita
person.identifierzahra foroozandeh
person.identifier1043580
person.identifier632184
person.identifier.ciencia-idC71B-D2A3-8705
person.identifier.ciencia-id6D1F-C495-6660
person.identifier.ciencia-id1612-8EA8-D0E8
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0003-3901-690X
person.identifier.orcid0000-0002-1120-5656
person.identifier.orcid0000-0002-4172-4502
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id35436109600
person.identifier.scopus-author-id7004115775
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication7a18aa02-2c1d-446d-a6b0-4dab18aa17ac
relation.isAuthorOfPublicationf01a54a0-e6c0-4cf3-afd8-5a664bbac7b4
relation.isAuthorOfPublication9ece308b-6d79-4cec-af91-f2278dcc47eb
relation.isAuthorOfPublicationff1df02d-0c0f-4db1-bf7d-78863a99420b
relation.isAuthorOfPublication.latestForDiscovery7a18aa02-2c1d-446d-a6b0-4dab18aa17ac
relation.isProjectOfPublicationc8b89528-2f4d-4be2-b8bb-46826a29deeb
relation.isProjectOfPublication2e765a22-f72f-4825-9c5d-5a702d94473f
relation.isProjectOfPublication.latestForDiscoveryc8b89528-2f4d-4be2-b8bb-46826a29deeb

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
ART_GECAD_processes_2021.pdf
Size:
687 KB
Format:
Adobe Portable Document Format
Download

Collections

ISEP – GECAD – Artigos