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Evolutionary Algorithms applied to the Intraday Energy Resource Scheduling in the Context of Multiple Aggregators

2021Journal article Open access
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dc.contributor.authorAlmeida, José
dc.contributor.authorSoares, João
dc.contributor.authorLezama, Fernando
dc.contributor.authorCanizes, Bruno
dc.contributor.authorVale, Zita
dc.date.accessioned2023-03-14T10:35:42Z
dc.date.available2023-03-14T10:35:42Z
dc.date.issued2021
dc.description.abstractThe growing number of electric vehicles (EVs) on the road and renewable energy production to meet carbon reduction targets has posed numerous electrical grid problems. The increasing use of distributed energy resources (DER) in the grid poses severe operational issues, such as grid congestion and overloading. Active management of distribution networks using the smart grid (SG) technologies and artificial intelligence (AI) techniques by multiple entities. In this case, aggregators can support the grid's operation, providing a better product for the end-user. This study proposes an effective intraday energy resource management starting with a day-ahead time frame, considering the uncertainty associated with high DER penetration. The optimization is achieved considering five different metaheuristics (DE, HyDE-DF, DEEDA, CUMDANCauchy++, and HC2RCEDUMDA). Results show that the proposed model is effective for the multiple aggregators with variations from the day-ahead around the 6 % mark, except for the final aggregator. A Wilcoxon test is also applied to compare the performance of the CUMDANCauchy++ algorithm with the remaining. CUMDANCauchy++ shows competitive results beating all algorithms in all aggregators except for DEEDA, which presents similar results.pt_PT
dc.description.sponsorshipThis research has received funding from FEDER funds through the Operational Programme for Competitiveness and Internationalization (COMPETE 2020), under Project POCI- 01-0145-FEDER-028983; by National Funds through the FCT Portuguese Foundation for Science and Technology, under Projects PTDC/EEI-EEE/28983/2017(CENERGETIC),CEECIND/02814/2017, and UIDB/000760/2020.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1109/SSCI50451.2021.9660005pt_PT
dc.identifier.issn978-1-7281-9048-8
dc.identifier.urihttp://hdl.handle.net/10400.22/22471
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.relationPOCI-01-0145-FEDER-028983pt_PT
dc.relationNot Available
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/9660005pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectAggregatorpt_PT
dc.subjectEnergy resource managementpt_PT
dc.subjectLocal electricity marketspt_PT
dc.subjectMetaheuristicspt_PT
dc.subjectOptimizationpt_PT
dc.titleEvolutionary Algorithms applied to the Intraday Energy Resource Scheduling in the Context of Multiple Aggregatorspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleNot Available
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/9471 - RIDTI/PTDC%2FEEI-EEE%2F28983%2F2017/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/CEEC IND 2017/CEECIND%2F02814%2F2017%2FCP1417%2FCT0002/PT
oaire.citation.conferencePlaceOrlando, FL, USApt_PT
oaire.citation.endPage08pt_PT
oaire.citation.startPage01pt_PT
oaire.citation.title2021 IEEE Symposium Series on Computational Intelligence (SSCI)pt_PT
oaire.fundingStream9471 - RIDTI
oaire.fundingStreamCEEC IND 2017
person.familyNameAlmeida
person.familyNameSoares
person.familyNameLezama
person.familyNameCanizes
person.familyNameVale
person.givenNameJosé
person.givenNameJoão
person.givenNameFernando
person.givenNameBruno
person.givenNameZita
person.identifier1043580
person.identifier632184
person.identifier.ciencia-idC017-775D-9F55
person.identifier.ciencia-id1612-8EA8-D0E8
person.identifier.ciencia-idE31F-56D6-1E0F
person.identifier.ciencia-idA411-F561-E922
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0002-9504-0501
person.identifier.orcid0000-0002-4172-4502
person.identifier.orcid0000-0001-8638-8373
person.identifier.orcid0000-0002-9808-5537
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-6945-2017
person.identifier.ridI-3492-2017
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id35436109600
person.identifier.scopus-author-id36810077500
person.identifier.scopus-author-id35408699300
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
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