Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/4897
Full metadata record
DC FieldValueLanguage
dc.contributor.authorPinto,Ten
dc.contributor.authorVale,Zen
dc.contributor.authorPraca,Ien
dc.contributor.authorEduardo Piresen
dc.contributor.authorLopes,Fen
dc.date.accessioned2017-12-22T23:26:07Z-
dc.date.available2017-12-22T23:26:07Z-
dc.date.issued2015en
dc.identifier.urihttp://repositorio.inesctec.pt/handle/123456789/4897-
dc.identifier.urihttp://dx.doi.org/10.3390/en8099817en
dc.description.abstractThis paper presents a decision support methodology for electricity market players' bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method's adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts' negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems' technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players' decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operatorMIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts' negotiations.en
dc.languageengen
dc.relation5777en
dc.rightsinfo:eu-repo/semantics/embargoedAccessen
dc.titleDecision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learningen
dc.typearticleen
dc.typePublicationen
Appears in Collections:CRIIS - Articles in International Journals

Files in This Item:
File Description SizeFormat 
P-00G-S9D.pdf
  Restricted Access
869.15 kBAdobe PDFView/Open Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.