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Portfolio optimization of electricity markets participation using forecasting error in risk formulation

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dc.contributor.authorFaia, R.
dc.contributor.authorPinto, Tiago
dc.contributor.authorVale, Zita
dc.contributor.authorCorchado, Juan Manuel
dc.date.accessioned2021-06-17T10:49:38Z
dc.date.embargo2100
dc.date.issued2021
dc.description.abstractRecent changes in the energy sector are increasing the importance of portfolio optimization for market participation. Although the portfolio optimization problem is most popular in finance and economics, it is only recently being subject of study and application in electricity markets. Risk modeling in this domain is, however, being addressed as in the classic portfolio optimization problem, where investment diversity is the adopted measure to mitigate risk. The increasing unpredictability of market prices as reflection of the renewable generation variability brings a new dimension to risk formulation, as market participation risk should consider the prices variation in each market. This paper thereby proposes a new portfolio optimization model, considering a new approach for risk management. The problem of electricity allocation between different markets is formulated as a classic portfolio optimization problem considering market prices forecast error as part of the risk asset. Dealing with a multi-objective problem leads to a heavy computational burden, and for this reason a particle swarm optimization-based method is applied. A case study based on real data from the Iberian electricity market demonstrates the advantages of the proposed approach to increase market players’ profits while minimizing the market participation risk.pt_PT
dc.description.sponsorshipThis work has received funding from the European Union's Horizon 2020 research and innovation programme under project DOMINOES (grant agreement No 771066), from FEDER Funds through COMPETE program and from National Funds through FCT under projects UIDB/00760/2020 and CEECIND/01811/2017. Ricardo Faia was supported by the PhD grant SFRH/BD/133086/2017 from National Funds through FCT.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1016/j.ijepes.2020.106739pt_PT
dc.identifier.issn0142-0615
dc.identifier.urihttp://hdl.handle.net/10400.22/18059
dc.language.isoengpt_PT
dc.publisherElsevierpt_PT
dc.relationCEECIND/01811/2017pt_PT
dc.relationApoio à decisão para participação em mercados de energia elétrica
dc.relationResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
dc.relationSmart Distribution Grid: a Market Driven Approach for the Next Generation of Advanced Operation Models and Services
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectElectricity marketspt_PT
dc.subjectPortfolio optimizationpt_PT
dc.subjectMulti-objective optimizationpt_PT
dc.titlePortfolio optimization of electricity markets participation using forecasting error in risk formulationpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleApoio à decisão para participação em mercados de energia elétrica
oaire.awardTitleResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
oaire.awardTitleSmart Distribution Grid: a Market Driven Approach for the Next Generation of Advanced Operation Models and Services
oaire.awardURIinfo:eu-repo/grantAgreement/FCT//SFRH%2FBD%2F133086%2F2017/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00760%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/EC/H2020/771066/EU
oaire.citation.startPage106739pt_PT
oaire.citation.titleInternational Journal of Electrical Power & Energy Systemspt_PT
oaire.citation.volume129pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStreamH2020
person.familyNameFaia
person.familyNamePinto
person.familyNameVale
person.givenNameRicardo Francisco Marcos
person.givenNameTiago
person.givenNameZita
person.identifier78FtZwIAAAAJ
person.identifierR-000-T7J
person.identifier632184
person.identifier.ciencia-id9B12-19F6-D6C7
person.identifier.ciencia-id2414-9B03-C4BB
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0002-1053-7720
person.identifier.orcid0000-0001-8248-080X
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridT-2245-2018
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id35219107600
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/10.13039/501100008530
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameEuropean Commission
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
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