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A multistage stochastic approach for the optimal bidding of variable renewable energy in the day-ahead, intraday and balancing markets

dc.contributor.authorSilva, Ana Rita
dc.contributor.authorPousinho, H. M. I.
dc.contributor.authorEstanqueiro, Ana
dc.date.accessioned2022-10-12T16:34:21Z
dc.date.available2022-10-12T16:34:21Z
dc.date.issued2022-11
dc.description.abstractABSTRACT: Market agents with renewable resources face amplified uncertainty when forecasting energy production to securely place bids in electricity markets. To deal with uncertainties, stochastic modelling has been applied to optimize the bidding strategy of these market agents. However, studies found in the literature usually focus on day-ahead and balancing markets, leaving aside intraday markets that could be used to correct bidding positions as uncertainty gets resolved. This paper proposes a multistage stochastic decision-aid algorithm based on linear programming to optimize the bidding strategy of market agents in three different electricity markets -day-ahead, intraday, and balance markets. The market agent represents a Virtual Power Plant with wind, solar PV, and storage technologies, and its participation in three electricity markets was compared to the participation in DA and BM markets only. Results show that participating in all three markets increased the profit achieved by the VPP agent by 10.1% while also decreasing the incurred imbalances by 63.8%. The results demonstrate that having accurate tools to deal with the multi-settlement framework of electricity markets while considering the uncertainties of daily operations is key to a successful integration of renewable energy resources into electricity markets and power systems.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationSilva, Ana Rita... [et.al.] - A multistage stochastic approach for the optimal bidding of variable renewable energy in the day-ahead, intraday and balancing markets. In: Energy, 2022, vol. 258, article nº 124856pt_PT
dc.identifier.doi10.1016/j.energy.2022.124856pt_PT
dc.identifier.eissn1873-6785
dc.identifier.issn0360-5442
dc.identifier.urihttp://hdl.handle.net/10400.9/3917
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relationA AGREGAÇÃO OTIMIZADA DA PRODUÇÃO RENOVÁVEL DISTRIBUÍDA
dc.relationTools for the Design and modelling of new markets and negotiation mechanisms for a ~100% Renewable European Power Systems
dc.relation.publisherversionhttps://doi.org/10.1016/j.energy.2022.124856pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectRenewable energy sourcespt_PT
dc.subjectStochastic modellingpt_PT
dc.subjectStorage systempt_PT
dc.subjectElectricity marketspt_PT
dc.subjectOptimizationpt_PT
dc.subjectPower systemspt_PT
dc.titleA multistage stochastic approach for the optimal bidding of variable renewable energy in the day-ahead, intraday and balancing marketspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleA AGREGAÇÃO OTIMIZADA DA PRODUÇÃO RENOVÁVEL DISTRIBUÍDA
oaire.awardTitleTools for the Design and modelling of new markets and negotiation mechanisms for a ~100% Renewable European Power Systems
oaire.awardURIinfo:eu-repo/grantAgreement/FCT//SFRH%2FBD%2F133419%2F2017/PT
oaire.awardURIinfo:eu-repo/grantAgreement/EC/H2020/864276/EU
oaire.citation.titleEnergypt_PT
oaire.citation.volume258pt_PT
oaire.fundingStreamH2020
person.familyNameEstanqueiro
person.givenNameAna
person.identifier.ciencia-id7F11-A24D-EE81
person.identifier.orcid0000-0002-0476-2526
person.identifier.ridJ-9752-2012
person.identifier.scopus-author-id19336967700
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100008530
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameEuropean Commission
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication20aa31b3-fa3c-42b7-82a4-e6b91c017f9c
relation.isAuthorOfPublication.latestForDiscovery20aa31b3-fa3c-42b7-82a4-e6b91c017f9c
relation.isProjectOfPublication2da6b0da-812b-43d0-8fcc-cfae14f4198d
relation.isProjectOfPublication7d7e6f9b-bf23-4adc-8f93-2061ef327e26
relation.isProjectOfPublication.latestForDiscovery2da6b0da-812b-43d0-8fcc-cfae14f4198d

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