A Sensitivity Analysis of PSO Parameters Solving the P2P Electricity Market Problem

Detalhes bibliográficos
Autor(a) principal: Vieira, Miguel
Data de Publicação: 2022
Outros Autores: Faia, Ricardo, Lezama, Fernando, Canizes, Bruno, Vale, Zita
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10400.22/22474
Resumo: Energy community markets have emerged to promote prosumers' active participation and empowerment in the electrical power system. These initiatives allow prosumers to transact electricity locally without an intermediary such as an aggregator. However, it is necessary to implement optimization methods that determine the best transactions within the energy community, obtaining the best solution under these models. Particle Swarm Optimization (PSO) fits this type of problem well because it allows reaching results in short optimization times. Furthermore, applying this metaheuristic to the problem is easy compared to other available optimization tools. In this work, we provide a sensitivity analysis of the impact of different parameters of PSO in solving an energy community market problem. As a result, the combination of parameters that lead to the best results is obtained, demonstrating the effectiveness of PSO solving different case studies.
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spelling A Sensitivity Analysis of PSO Parameters Solving the P2P Electricity Market ProblemLocal electricity marketsParticle Swarm OptimizationPeer-to-Peer transactionsSensitivity analysisSwarm intelligenceEnergy community markets have emerged to promote prosumers' active participation and empowerment in the electrical power system. These initiatives allow prosumers to transact electricity locally without an intermediary such as an aggregator. However, it is necessary to implement optimization methods that determine the best transactions within the energy community, obtaining the best solution under these models. Particle Swarm Optimization (PSO) fits this type of problem well because it allows reaching results in short optimization times. Furthermore, applying this metaheuristic to the problem is easy compared to other available optimization tools. In this work, we provide a sensitivity analysis of the impact of different parameters of PSO in solving an energy community market problem. As a result, the combination of parameters that lead to the best results is obtained, demonstrating the effectiveness of PSO solving different case studies.IEEEREPOSITÓRIO P.PORTOVieira, MiguelFaia, RicardoLezama, FernandoCanizes, BrunoVale, Zita2023-03-14T10:56:38Z20222022-01-01T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10400.22/22474eng10.1109/CEC55065.2022.9870290info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-04-02T03:32:42Zoai:recipp.ipp.pt:10400.22/22474Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T00:59:50.326232Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv A Sensitivity Analysis of PSO Parameters Solving the P2P Electricity Market Problem
title A Sensitivity Analysis of PSO Parameters Solving the P2P Electricity Market Problem
spellingShingle A Sensitivity Analysis of PSO Parameters Solving the P2P Electricity Market Problem
Vieira, Miguel
Local electricity markets
Particle Swarm Optimization
Peer-to-Peer transactions
Sensitivity analysis
Swarm intelligence
title_short A Sensitivity Analysis of PSO Parameters Solving the P2P Electricity Market Problem
title_full A Sensitivity Analysis of PSO Parameters Solving the P2P Electricity Market Problem
title_fullStr A Sensitivity Analysis of PSO Parameters Solving the P2P Electricity Market Problem
title_full_unstemmed A Sensitivity Analysis of PSO Parameters Solving the P2P Electricity Market Problem
title_sort A Sensitivity Analysis of PSO Parameters Solving the P2P Electricity Market Problem
author Vieira, Miguel
author_facet Vieira, Miguel
Faia, Ricardo
Lezama, Fernando
Canizes, Bruno
Vale, Zita
author_role author
author2 Faia, Ricardo
Lezama, Fernando
Canizes, Bruno
Vale, Zita
author2_role author
author
author
author
dc.contributor.none.fl_str_mv REPOSITÓRIO P.PORTO
dc.contributor.author.fl_str_mv Vieira, Miguel
Faia, Ricardo
Lezama, Fernando
Canizes, Bruno
Vale, Zita
dc.subject.por.fl_str_mv Local electricity markets
Particle Swarm Optimization
Peer-to-Peer transactions
Sensitivity analysis
Swarm intelligence
topic Local electricity markets
Particle Swarm Optimization
Peer-to-Peer transactions
Sensitivity analysis
Swarm intelligence
description Energy community markets have emerged to promote prosumers' active participation and empowerment in the electrical power system. These initiatives allow prosumers to transact electricity locally without an intermediary such as an aggregator. However, it is necessary to implement optimization methods that determine the best transactions within the energy community, obtaining the best solution under these models. Particle Swarm Optimization (PSO) fits this type of problem well because it allows reaching results in short optimization times. Furthermore, applying this metaheuristic to the problem is easy compared to other available optimization tools. In this work, we provide a sensitivity analysis of the impact of different parameters of PSO in solving an energy community market problem. As a result, the combination of parameters that lead to the best results is obtained, demonstrating the effectiveness of PSO solving different case studies.
publishDate 2022
dc.date.none.fl_str_mv 2022
2022-01-01T00:00:00Z
2023-03-14T10:56:38Z
dc.type.driver.fl_str_mv conference object
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.22/22474
url http://hdl.handle.net/10400.22/22474
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1109/CEC55065.2022.9870290
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IEEE
publisher.none.fl_str_mv IEEE
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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