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Strategic Particle Swarm Inertia Selection for Electricity Markets Participation Portfolio Optimization

2018Journal article Open access
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dc.contributor.authorFaia, Ricardo
dc.contributor.authorPinto, Tiago
dc.contributor.authorVale, Zita
dc.contributor.authorCorchado, Juan Manuel
dc.date.accessioned2021-02-24T12:36:21Z
dc.date.available2021-02-24T12:36:21Z
dc.date.issued2018
dc.description.abstractThe portfolio optimization is a well-known problem in the areas of economy and finance. This problem has also become increasingly important in electrical power systems, particularly in the area of electricity markets, mostly due to the growing number of alternative/complementary market types that are being introduced to deal with important issues, such as the massive integration of renewable energy sources in power systems. The optimization of electricity market players’ participation portfolio comprises significant time constraints, which cannot be satisfied by the use of deterministic techniques. For this reason, meta-heuristic solutions are used, such as particle swarm optimization. The inertia is one of the most important parameter in this method, and it is the main focus of this paper. This paper studies 18 popular inertia calculation strategies, by comparing their performance in the portfolio optimization problem. A strategic methodology for the automatic selection of the best inertia calculation method for the needs of each optimization is also proposed. Results show that the proposed approach is able to automatically adapt the inertia parameter according to the needs in each execution.pt_PT
dc.description.sponsorshipThis work has been developed in the scope of the European Union's Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie grant agreement No 703689 (project ADAPT) and grant agreement No 641794 (project DREAM-GO); and has also been supported by the CONTEST project – SAICT-POL/23575/2016. Ricardo Faia is supported by FCT Funds through SFRH/BD/133086/2017 (PhD scholarship).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1080/08839514.2018.1506971pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/17117
dc.language.isoengpt_PT
dc.publisherTaylor and Francispt_PT
dc.relationPOL/23575/2016pt_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.relationApoio à decisão para participação em mercados de energia elétrica
dc.relationAdaptive Decision support for Agents negotiation in electricity market and smart grid Power Transactions
dc.relation.publisherversionhttps://www.tandfonline.com/doi/full/10.1080/08839514.2018.1506971pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectArtificial Intelligencept_PT
dc.subjectElectricity Marketpt_PT
dc.subjectInertia Parameterpt_PT
dc.subjectParticle Swarm Optimizationpt_PT
dc.subjectPortfolio Optimizationpt_PT
dc.titleStrategic Particle Swarm Inertia Selection for Electricity Markets Participation Portfolio Optimizationpt_PT
dc.typejournal article
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.awardTitleApoio à decisão para participação em mercados de energia elétrica
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//SFRH%2FBD%2F133086%2F2017/PT
oaire.awardURIinfo:eu-repo/grantAgreement/EC/H2020/703689/EU
oaire.citation.endPage767pt_PT
oaire.citation.issue7-8pt_PT
oaire.citation.startPage745pt_PT
oaire.citation.titleApplied Artificial Intelligencept_PT
oaire.citation.volume32pt_PT
oaire.fundingStreamH2020
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/10.13039/501100008530
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.typearticlept_PT
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