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Robust Energy Resource Management Incorporating Risk Analysis Using Conditional Value-at-Risk

2022Journal article Open access
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dc.contributor.authorAlmeida, José
dc.contributor.authorSoares, Joao
dc.contributor.authorLezama, Fernando
dc.contributor.authorVale, Zita
dc.date.accessioned2023-02-01T10:28:22Z
dc.date.available2023-02-01T10:28:22Z
dc.date.issued2022
dc.description.abstractThe energy resource management (ERM) problem in today’s energy systems is complex and challenging due to the increasing penetration of distributed energy resources with uncertain behavior. Despite the improvement of forecasting tools, and the development of strategies to deal with this uncertainty (for instance, considering Monte Carlo simulation to generate a set of different possible scenarios), the risk associated with such variable resources cannot be neglected and deserves proper attention to guarantee the correct functioning of the entire system. This paper proposes a risk-based optimization approach for the centralized day-ahead ERM taking into account extreme events. Risk-neutral and risk-averse methodologies are implemented, where the risk-averse strategy considers the worst scenario costs through the conditional value-at-risk ( CVaR ) method. The model is formulated from the perspective of an aggregator that manages multiple technologies such as distributed generation, demand response, energy storage systems, among others. The case study analysis the aggregator’s management inserted in a 13-bus distribution network in the smart grid context with high penetration of renewable energy and electric vehicles. Results show an increase of nearly 4% in the day-ahead operational costs comparing the risk-neutral to the risk-averse strategy, but a reduction of up to 14% in the worst-case scenario cost. Thus, the proposed model can provide safer and more robust solutions incorporating the CVaR tool into the day-ahead management.pt_PT
dc.description.sponsorshipThis work was supported in part by the European Regional Development Fund (FEDER) through the Operational Program for Competitiveness and Internationalization (COMPETE 2020), under Project POCI-01-0145-FEDER-028983; and in part by the National Funds through the Fundação para a Ciância e Tecnologia (FCT) Portuguese Foundation for Science and Technology, under Project PTDC/EEI-EEE/28983/2017(CENERGETIC), Project CEECIND/02814/2017, Project UIDB/000760/2020, and Project UIDP/00760/2020.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1109/ACCESS.2022.3147501pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/22047
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherIEEEpt_PT
dc.relationPOCI-01-0145-FEDER-028983pt_PT
dc.relationNot Available
dc.relationResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/9696323pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectAggregatorpt_PT
dc.subjectConditional value-at-riskpt_PT
dc.subjectEnergy resource managementpt_PT
dc.subjectRisk-based optimizationpt_PT
dc.subjectUncertaintypt_PT
dc.titleRobust Energy Resource Management Incorporating Risk Analysis Using Conditional Value-at-Riskpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleNot Available
oaire.awardTitleResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
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.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00760%2F2020/PT
oaire.citation.endPage16077pt_PT
oaire.citation.startPage16063pt_PT
oaire.citation.titleIEEE Accesspt_PT
oaire.citation.volume10pt_PT
oaire.fundingStream9471 - RIDTI
oaire.fundingStreamCEEC IND 2017
oaire.fundingStream6817 - DCRRNI ID
person.familyNameAlmeida
person.familyNameSoares
person.familyNameLezama
person.familyNameVale
person.givenNameJosé
person.givenNameJoão
person.givenNameFernando
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-id721B-B0EB-7141
person.identifier.orcid0000-0002-9504-0501
person.identifier.orcid0000-0002-4172-4502
person.identifier.orcid0000-0001-8638-8373
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-6945-2017
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id35436109600
person.identifier.scopus-author-id36810077500
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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