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Generation of realistic scenarios for multi-agent simulation of electricity markets

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dc.contributor.authorSilva, Francisco
dc.contributor.authorTeixeira, Brígida
dc.contributor.authorPinto, Tiago
dc.contributor.authorSantos, Gabriel
dc.contributor.authorVale, Zita
dc.contributor.authorPraça, Isabel
dc.date.accessioned2017-01-24T16:52:22Z
dc.date.embargo2117
dc.date.issued2016
dc.description.abstractMost market operators provide daily data on several market processes, including the results of all market transactions. The use of such data by electricity market simulators is essential for simulations quality, enabling the modelling of market behaviour in a much more realistic and efficient way. RealScen (Realistic Scenarios Generator) is a tool that creates realistic scenarios according to the purpose of the simulation: representing reality as it is, or on a smaller scale but still as representative as possible. This paper presents a novel methodology that enables RealScen to collect real electricity markets information and using it to represent market participants, as well as modelling their characteristics and behaviours. This is done using data analysis combined with artificial intelligence. This paper analyses the way players' characteristics are modelled, particularly in their representation in a smaller scale, simplifying the simulation while maintaining the quality of results. A study is also conducted, comparing real electricity market values with the market results achieved using the generated scenarios. The conducted study shows that the scenarios can fully represent the reality, or approximate it through a reduced number of representative software agents. As a result, the proposed methodology enables RealScen to represent markets behaviour, allowing the study and understanding of the interactions between market entities, and the study of new markets by assuring the realism of simulations.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1016/j.energy.2016.09.096pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/9371
dc.language.isoengpt_PT
dc.publisherElsevierpt_PT
dc.relation.ispartofseriesEnergy;Vol. 116, Part 1,
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S0360544216313664pt_PT
dc.subjectData-Miningpt_PT
dc.subjectElectricity marketspt_PT
dc.subjectKnowledge discoverypt_PT
dc.subjectMachine learningpt_PT
dc.subjectMulti-agent simulationpt_PT
dc.subjectScenarios generationpt_PT
dc.titleGeneration of realistic scenarios for multi-agent simulation of electricity marketspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage139pt_PT
oaire.citation.issue1pt_PT
oaire.citation.startPage128pt_PT
oaire.citation.titleEnergypt_PT
oaire.citation.volume116pt_PT
person.familyNamePinto
person.familyNameVale
person.familyNamePraça
person.givenNameTiago
person.givenNameZita
person.givenNameIsabel
person.identifierR-000-T7J
person.identifier632184
person.identifier299522
person.identifier.ciencia-id2414-9B03-C4BB
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.ciencia-idC710-4218-1BFF
person.identifier.orcid0000-0001-8248-080X
person.identifier.orcid0000-0002-4560-9544
person.identifier.orcid0000-0002-2519-9859
person.identifier.ridT-2245-2018
person.identifier.ridA-5824-2012
person.identifier.ridK-8430-2014
person.identifier.scopus-author-id35219107600
person.identifier.scopus-author-id7004115775
person.identifier.scopus-author-id22734900800
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication8d58ddc0-1023-47c0-a005-129d412ce98d
relation.isAuthorOfPublicationff1df02d-0c0f-4db1-bf7d-78863a99420b
relation.isAuthorOfPublicationee4ecacd-c6c6-41e8-bca1-21a60ff05f50
relation.isAuthorOfPublication.latestForDiscoveryee4ecacd-c6c6-41e8-bca1-21a60ff05f50

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