Repository logo
 
Publication

Data Mining Approach to support the Generation of Realistic Scenarios for Multi-Agent simulation of Electricity Markets

2014-12Conference object Restricted access
Simple item page
dc.contributor.authorTeixeira, Brígida
dc.contributor.authorSilva, Francisco
dc.contributor.authorPinto, Tiago
dc.contributor.authorPraça, Isabel
dc.contributor.authorSantos, Gabriel
dc.contributor.authorVale, Zita
dc.date.accessioned2015-05-07T10:23:46Z
dc.date.available2015-05-07T10:23:46Z
dc.date.issued2014-12
dc.description.abstractThis paper presents the Realistic Scenarios Generator (RealScen), a tool that processes data from real electricity markets to generate realistic scenarios that enable the modeling of electricity market players’ characteristics and strategic behavior. The proposed tool provides significant advantages to the decision making process in an electricity market environment, especially when coupled with a multi-agent electricity markets simulator. The generation of realistic scenarios is performed using mechanisms for intelligent data analysis, which are based on artificial intelligence and data mining algorithms. These techniques allow the study of realistic scenarios, adapted to the existing markets, and improve the representation of market entities as software agents, enabling a detailed modeling of their profiles and strategies. This work contributes significantly to the understanding of the interactions between the entities acting in electricity markets by increasing the capability and realism of market simulations.por
dc.identifier.doi10.1109/IA.2014.7009452
dc.identifier.urihttp://hdl.handle.net/10400.22/5962
dc.language.isoengpor
dc.publisherIEEEpor
dc.relation.ispartofseriesIA;2014
dc.relation.publisherversionhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=7009452&queryText%3DData+Mining+Approach+to+support+the+Generation+of+Realistic+Scenarios+for+Multi-Agent+simulation+of+Electricity+Marketspor
dc.subjectData-Miningpor
dc.subjectElectricity Marketspor
dc.subjectKnowledge Discovery in Databasespor
dc.subjectMachine Learningpor
dc.subjectMulti-Agent Simulationpor
dc.subjectScenarios Generationpor
dc.titleData Mining Approach to support the Generation of Realistic Scenarios for Multi-Agent simulation of Electricity Marketspor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceOrlando, Florida, USApor
oaire.citation.endPage15por
oaire.citation.startPage8por
oaire.citation.titleIA 2014 – Intelligent Agents (IA) at the IEEE SSCI 2014 (IEEE Symposium Series on Computational Intelligence)por
person.familyNamePinto
person.familyNamePraça
person.familyNameVale
person.givenNameTiago
person.givenNameIsabel
person.givenNameZita
person.identifierR-000-T7J
person.identifier299522
person.identifier632184
person.identifier.ciencia-id2414-9B03-C4BB
person.identifier.ciencia-idC710-4218-1BFF
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0001-8248-080X
person.identifier.orcid0000-0002-2519-9859
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridT-2245-2018
person.identifier.ridK-8430-2014
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id35219107600
person.identifier.scopus-author-id22734900800
person.identifier.scopus-author-id7004115775
rcaap.rightsclosedAccesspor
rcaap.typeconferenceObjectpor
relation.isAuthorOfPublication8d58ddc0-1023-47c0-a005-129d412ce98d
relation.isAuthorOfPublicationee4ecacd-c6c6-41e8-bca1-21a60ff05f50
relation.isAuthorOfPublicationff1df02d-0c0f-4db1-bf7d-78863a99420b
relation.isAuthorOfPublication.latestForDiscovery8d58ddc0-1023-47c0-a005-129d412ce98d

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
COM_BTeixeira_2015_GECAD.pdf
Size:
184.86 KB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

ISEP – GECAD – Comunicações em eventos científicos