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Optimization of Electricity Markets Participation with Simulated Annealing

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dc.contributor.authorFaia, R.
dc.contributor.authorPinto, Tiago
dc.contributor.authorVale, Zita
dc.date.accessioned2021-03-09T16:30:19Z
dc.date.available2021-03-09T16:30:19Z
dc.date.issued2016
dc.description.abstractThe electricity markets environment has changed completely with the introduction of renewable energy sources in the energy distribution systems. With such alterations, preventing the system from collapsing required the development of tools to avoid system failure. In this new market environment competitiveness increases, new and different power producers have emerged, each of them with different characteristics, although some are shared for all of them, such as the unpredictability. In order to battle the unpredictability, the power supplies of this nature are supported by techniques of artificial intelligence that enables them crucial information for participation in the energy markets. In electricity markets any player aims to get the best profit, but is necessary have knowledge of the future with a degree of confidence leading to possible build successful actions. With optimization techniques based on artificial intelligence it is possible to achieve results in considerable time so that producers are able to optimize their profits from the sale of Electricity. Nowadays, there are many optimization problems where there are no that cannot be solved with exact methods, or where deterministic methods are computationally too complex to implement. Heuristic optimization methods have, thus, become a promising solution. In this paper, a simulated annealing based approach is used to solve the portfolio optimization problem for multiple electricity markets participation. A case study based on real electricity markets data is presented, and the results using the proposed approach are compared to those achieved by a previous implementation using particle swarm optimization.pt_PT
dc.description.sponsorshipThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 641794pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1007/978-3-319-40159-1_3pt_PT
dc.identifier.isbn978-3-319-40159-1
dc.identifier.urihttp://hdl.handle.net/10400.22/17358
dc.language.isoengpt_PT
dc.publisherSpringerpt_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.relation.publisherversionhttps://link.springer.com/chapter/10.1007%2F978-3-319-40159-1_3pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectArtificial intelligencept_PT
dc.subjectElectricity marketspt_PT
dc.subjectPortfolio optimizationpt_PT
dc.subjectSimulated annealingpt_PT
dc.titleOptimization of Electricity Markets Participation with Simulated Annealingpt_PT
dc.typeconference object
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.awardURIinfo:eu-repo/grantAgreement/EC/H2020/641794/EU
oaire.citation.conferencePlaceSeville, Spainpt_PT
oaire.citation.endPage39pt_PT
oaire.citation.startPage27pt_PT
oaire.citation.title14th International Conference on Practical Applications of Agents and Multiagent Systems (PAAMS 2016)pt_PT
oaire.citation.volume473pt_PT
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.nameEuropean Commission
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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relation.isAuthorOfPublication8d58ddc0-1023-47c0-a005-129d412ce98d
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relation.isProjectOfPublication4a092e97-cc2f-4f57-8d3c-cf1709963516
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