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Differential Evolution Aplication in Portfolio optimization for Electricity Markets

2018Conference object Open access
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dc.contributor.authorFaia, R.
dc.contributor.authorLezama, Fernando
dc.contributor.authorSoares, João
dc.contributor.authorVale, Zita
dc.contributor.authorPinto, Tiago
dc.contributor.authorCorchado, Juan Manuel
dc.date.accessioned2022-01-11T14:56:38Z
dc.date.available2022-01-11T14:56:38Z
dc.date.issued2018
dc.description.abstractSmart Grid technologies enable the intelligent integration and management of distributed energy resources. Also, the advanced communication and control capabilities in smart grids facilitate the active participation of aggregators at different levels in the available electricity markets. The portfolio optimization problem consists in finding the optimal bid allocation in the different available markets. In this scenario, the aggregator should be able to provide a solution within a timeframe. Therefore, the application of metaheuristic approaches is justified, since they have proven to be an effective tool to provide near-optimal solutions in acceptable execution times. Among the vast variety of metaheuristics available in the literature, Differential Evolution (DE) is arguably one of the most popular and successful evolutionary algorithms due to its simplicity and effectiveness. In this paper, the use of DE is analyzed for solving the portfolio optimization problem in electricity markets. Moreover, the performance of DE is compared with another powerful metaheuristic, the Particle Swarm optimization (PSO), showing that despite both algorithms provide good results for the problem, DE overcomes PSO in terms of quality of the solutions.pt_PT
dc.description.sponsorshipThis work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAM-GO) and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013 and grant agreement No 703689 (project ADAPT);pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1109/IJCNN.2018.8489117pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/19389
dc.language.isoengpt_PT
dc.publisherIEEEpt_PT
dc.relationEnabling Demand Response for short and real-time Efficient And Market Based smart Grid Operation - An intelligent and real-time simulation approach
dc.relationAdaptive Decision support for Agents negotiation in electricity market and smart grid Power Transactions
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8489117pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectDifferencial Evolutionpt_PT
dc.subjectPortfolio optimizationpt_PT
dc.subjectElectricity marketspt_PT
dc.titleDifferential Evolution Aplication in Portfolio optimization for Electricity Marketspt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardTitleEnabling Demand Response for short and real-time Efficient And Market Based smart Grid Operation - An intelligent and real-time simulation approach
oaire.awardTitleAdaptive Decision support for Agents negotiation in electricity market and smart grid Power Transactions
oaire.awardURIinfo:eu-repo/grantAgreement/EC/H2020/641794/EU
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FEEA%2F00760%2F2013/PT
oaire.awardURIinfo:eu-repo/grantAgreement/EC/H2020/703689/EU
oaire.citation.conferencePlaceRio de Janeiro, Brazilpt_PT
oaire.citation.endPage8pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.title2018 International Joint Conference on Neural Networks (IJCNN)pt_PT
oaire.fundingStreamH2020
oaire.fundingStream5876
oaire.fundingStreamH2020
person.familyNameFaia
person.familyNameLezama
person.familyNameSoares
person.familyNameVale
person.familyNamePinto
person.givenNameRicardo Francisco Marcos
person.givenNameFernando
person.givenNameJoão
person.givenNameZita
person.givenNameTiago
person.identifier78FtZwIAAAAJ
person.identifier1043580
person.identifier632184
person.identifierR-000-T7J
person.identifier.ciencia-id9B12-19F6-D6C7
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person.identifier.ciencia-id721B-B0EB-7141
person.identifier.ciencia-id2414-9B03-C4BB
person.identifier.orcid0000-0002-1053-7720
person.identifier.orcid0000-0001-8638-8373
person.identifier.orcid0000-0002-4172-4502
person.identifier.orcid0000-0002-4560-9544
person.identifier.orcid0000-0001-8248-080X
person.identifier.ridA-6945-2017
person.identifier.ridA-5824-2012
person.identifier.ridT-2245-2018
person.identifier.scopus-author-id36810077500
person.identifier.scopus-author-id35436109600
person.identifier.scopus-author-id7004115775
person.identifier.scopus-author-id35219107600
project.funder.identifierhttp://doi.org/10.13039/501100008530
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100008530
project.funder.nameEuropean Commission
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameEuropean Commission
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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