Publication
Hybrid particle swarm optimization of electricity market participation portfolio
| dc.contributor.author | Faia, Ricardo | |
| dc.contributor.author | Pinto, Tiago | |
| dc.contributor.author | Vale, Zita | |
| dc.contributor.author | Corchado, Juan Manuel | |
| dc.date.accessioned | 2021-03-09T12:30:40Z | |
| dc.date.available | 2021-03-09T12:30:40Z | |
| dc.date.issued | 2017 | |
| dc.description.abstract | This paper proposes a novel hybrid particle swarm optimization methodology to solve the problem of optimal participation in multiple electricity markets. The decision time is usually very important when planning the participation in electricity markets. This environment is characterized by the time available to take action, since different electricity markets have specific rules, which requires participants to be able to adapt and plan their decisions in a short time. Using metaheuristic optimization, participants' time problems can be resolved, because these methods enable problems to be solved in a short time and with good results. This paper proposes a hybrid resolution method, which is based on the particle swarm optimization metaheuristic. An exact mathematical method, which solves a simplified, linearized, version of the problem, is used to generate the initial solution for the metaheuristic approach, with the objective of improving the quality of results without representing a significant increase of the execution time. | pt_PT |
| dc.description.sponsorship | This work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 703689 (project ADAPT) and No 641794 (project DREAM-GO); NetEfficity Project (P2020 − 18015); and UID/EEA/00760/2013 funded by FEDER Funds through COMPETE pro-gram and by National Funds through FCT. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.doi | 10.1109/SSCI.2017.8285218 | pt_PT |
| dc.identifier.isbn | 978-1-5386-2726-6 | |
| dc.identifier.uri | http://hdl.handle.net/10400.22/17329 | |
| dc.language.iso | eng | pt_PT |
| dc.publisher | IEEE | pt_PT |
| dc.relation | Adaptive Decision support for Agents negotiation in electricity market and smart grid Power Transactions | |
| dc.relation | Enabling Demand Response for short and real-time Efficient And Market Based smart Grid Operation - An intelligent and real-time simulation approach | |
| dc.relation.publisherversion | https://ieeexplore.ieee.org/document/8285218 | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | pt_PT |
| dc.subject | Artificial intelligence | pt_PT |
| dc.subject | Electricity markets | pt_PT |
| dc.subject | Hybrid resolution methods | pt_PT |
| dc.subject | Portfolio optimization | pt_PT |
| dc.subject | Metaheuristic optimization | pt_PT |
| dc.title | Hybrid particle swarm optimization of electricity market participation portfolio | pt_PT |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | Adaptive Decision support for Agents negotiation in electricity market and smart grid Power Transactions | |
| oaire.awardTitle | Enabling Demand Response for short and real-time Efficient And Market Based smart Grid Operation - An intelligent and real-time simulation approach | |
| oaire.awardURI | info:eu-repo/grantAgreement/EC/H2020/703689/EU | |
| oaire.awardURI | info:eu-repo/grantAgreement/EC/H2020/641794/EU | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/5876/UID%2FEEA%2F00760%2F2013/PT | |
| oaire.citation.conferencePlace | Honolulu, HI, USA | pt_PT |
| oaire.citation.endPage | 8 | pt_PT |
| oaire.citation.startPage | 1 | pt_PT |
| oaire.citation.title | IEEE Symposium Series on Computational Intelligence (SSCI 2017) | pt_PT |
| oaire.fundingStream | H2020 | |
| oaire.fundingStream | H2020 | |
| oaire.fundingStream | 5876 | |
| person.familyName | Pinto | |
| person.familyName | Vale | |
| person.givenName | Tiago | |
| person.givenName | Zita | |
| person.identifier | R-000-T7J | |
| person.identifier | 632184 | |
| person.identifier.ciencia-id | 2414-9B03-C4BB | |
| person.identifier.ciencia-id | 721B-B0EB-7141 | |
| person.identifier.orcid | 0000-0001-8248-080X | |
| person.identifier.orcid | 0000-0002-4560-9544 | |
| person.identifier.rid | T-2245-2018 | |
| person.identifier.rid | A-5824-2012 | |
| person.identifier.scopus-author-id | 35219107600 | |
| person.identifier.scopus-author-id | 7004115775 | |
| project.funder.identifier | http://doi.org/10.13039/501100008530 | |
| project.funder.identifier | http://doi.org/10.13039/501100008530 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | European Commission | |
| project.funder.name | European Commission | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | conferenceObject | pt_PT |
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