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dc.contributor.authorDelgadillo Vega, Andrés Ramiroes-ES
dc.contributor.authorGallego Vega, Luis Eduardoes-ES
dc.contributor.authorDuarte, Oscares-ES
dc.contributor.authorJiménez, Dianaes-ES
dc.contributor.authorCamargo, Marthaes-ES
dc.date.accessioned2016-01-15T11:27:35Z
dc.date.available2016-01-15T11:27:35Z
dc.date.issued2008-07-20es_ES
dc.identifier.urihttp://hdl.handle.net/11531/5628
dc.descriptionCapítulos en libroses_ES
dc.description.abstractes-ES
dc.description.abstractIn this paper, a model of the Colombian electricity market is implemented using the Agent-based Computational Economics (ACE) methodology. The paper propose a methodology to model the offer price behavior of generation companies upon the actual colombian market structure and the effects in market prices and agents’ profits. This model is based on a learning algorithm that uses some soft computing techniques to face the discovery of a complex function among offer prices, power system variables and profits. In addition, this methodology allows the agents to improve their offer strategies by maximizing their own profits. Finally, the paper presents some results obtained from the model about the behavior of spot prices and agents profits.en-GB
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoen-GBes_ES
dc.publisherSin editorial (Pittsburgh, Estados Unidos de América)es_ES
dc.rightses_ES
dc.rights.uries_ES
dc.sourceLibro: IEEE Power & Energy Society General Meeting - IEEE PES GM 2008, Página inicial: 1-7, Página final:es_ES
dc.subject.otherInstituto de Investigación Tecnológica (IIT)es_ES
dc.titleAgent Learning Methodology for Generators in an Electricity Marketes_ES
dc.typeinfo:eu-repo/semantics/bookPartes_ES
dc.description.versioninfo:eu-repo/semantics/publishedVersiones_ES
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses_ES
dc.keywordses-ES
dc.keywordsAgent-based Computational Economics, Genetic Algorithms, Artificial Neural Networks, Electricity Market.en-GB


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