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Optimizing Energy Consumption of Household Appliances Using PSO and GWO

2021Journal article Open access
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dc.contributor.authorTavares, Inês
dc.contributor.authorAlmeida, José
dc.contributor.authorSoares, João
dc.contributor.authorRamos, Sérgio
dc.contributor.authorVale, Zita
dc.contributor.authorForoozandeh, Zahra
dc.date.accessioned2022-07-07T08:50:54Z
dc.date.available2022-07-07T08:50:54Z
dc.date.issued2021
dc.description.abstractDue to the increasing electricity consumption in the residential sector, new control systems emerged to control the demand side. Some techniques have been developed, such as shaping the curve’s load peaks by planning and shifting the electricity demand for household appliances. This paper presents a comparative analysis for the energy consumption optimization of two household appliances using two Swarm Intelligence (SI) algorithms: Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO). This problem’s main objective is to minimize the energy cost according to both machines’ energy consumption, respecting the restrictions applied. Three scenarios are presented: changing the energy market price during the day according to three types of energy tariffs. The results show that the user in the cheapest periods could switch on both machines because both techniques presented the highest energy consumption values. Regarding the objective function analysis, PSO and GWO obtained the best (more economical) values for the simple tariff due to its lower energy consumption. The GWO technique also presented more diverging values from the average objective function value than the PSO algorithm.pt_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 un- der CEECIND/02814/2017 grant.pt_PT
dc.description.versioninfo:eu-repo/semantics/acceptedVersionpt_PT
dc.identifier.citationTavares, I., Almeida, J., Soares, J., Ramos, S., Vale, Z., Foroozandeh, Z. (2021). Optimizing Energy Consumption of Household Appliances Using PSO and GWO. In: Marreiros, G., Melo, F.S., Lau, N., Lopes Cardoso, H., Reis, L.P. (eds) Progress in Artificial Intelligence. EPIA 2021. Lecture Notes in Computer Science(), vol 12981. Springer, Cham. https://doi.org/10.1007/978-3-030-86230-5_11pt_PT
dc.identifier.doi10.1007/978-3-030-86230-5_11pt_PT
dc.identifier.isbn978-3-030-86230-5
dc.identifier.urihttp://hdl.handle.net/10400.22/20668
dc.language.isoporpt_PT
dc.publisherSpringerpt_PT
dc.relationResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
dc.relationNot Available
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007/978-3-030-86230-5_11pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/pt_PT
dc.subjectEnergy consumptionpt_PT
dc.subjectGrey Wolf Optimizerpt_PT
dc.subjectOptimizationpt_PT
dc.subjectParticle Swarm Optimizationpt_PT
dc.subjectSwarm Intelligencept_PT
dc.titleOptimizing Energy Consumption of Household Appliances Using PSO and GWOpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
oaire.awardTitleNot Available
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/9471 - RIDTI/PTDC%2FEEI-EEE%2F29070%2F2017/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00760%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/CEEC IND 2017/CEECIND%2F02814%2F2017%2FCP1417%2FCT0002/PT
oaire.citation.endPage150pt_PT
oaire.citation.startPage137pt_PT
oaire.citation.titleEPIA Conference on Artificial Intelligence (EPIA 2021)pt_PT
oaire.citation.volume12981pt_PT
oaire.fundingStream9471 - RIDTI
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStreamCEEC IND 2017
person.familyNameSoares Almeida
person.familyNameSoares
person.familyNameCarvalho Ramos
person.familyNameVale
person.familyNameforouzandehjouneghani
person.givenNameJosé Miguel
person.givenNameJoão
person.givenNameSérgio Filipe
person.givenNameZita
person.givenNamezahra
person.identifier1043580
person.identifier632184
person.identifierzahra foroozandeh
person.identifier.ciencia-idD018-2A4D-8588
person.identifier.ciencia-id1612-8EA8-D0E8
person.identifier.ciencia-id6D1F-C495-6660
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.ciencia-idC71B-D2A3-8705
person.identifier.orcid0000-0001-5844-5393
person.identifier.orcid0000-0002-4172-4502
person.identifier.orcid0000-0002-1120-5656
person.identifier.orcid0000-0002-4560-9544
person.identifier.orcid0000-0003-3901-690X
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id23007623500
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.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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