A Robust Optimization for Day-ahead Microgrid Dispatch Considering Uncertainties

Bibliographic Details
Main Author: Borges, Nuno
Publication Date: 2017
Other Authors: Soares, João, Vale, Zita
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.22/17319
Summary: This paper presents a Particle Swarm Optimization (PSO) methodology to solve the problem of day-ahead microgrid (MG) dispatch with high penetration of Distributed Generation (DG) and considering uncertainties. The proposed methodology has the objective to satisfy demand aiming at obtaining the maximum profit, corresponding to the difference between the income and costs of the MG. This methodology considers the uncertainties associated with the production of electricity by the photovoltaic and wind sources. This uncertainty is modeled with the use of a robust approach in PSO. A case study is presented using a 21-bus MG from a real university campus in Portugal, and the projection of distributed energy resources based on the evolution scenario for the year 2050 managed by an aggregator.
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spelling A Robust Optimization for Day-ahead Microgrid Dispatch Considering UncertaintiesEnergy Resources ManagementMicrogridsParticle Swarm OptimizationRobust OptimizationThis paper presents a Particle Swarm Optimization (PSO) methodology to solve the problem of day-ahead microgrid (MG) dispatch with high penetration of Distributed Generation (DG) and considering uncertainties. The proposed methodology has the objective to satisfy demand aiming at obtaining the maximum profit, corresponding to the difference between the income and costs of the MG. This methodology considers the uncertainties associated with the production of electricity by the photovoltaic and wind sources. This uncertainty is modeled with the use of a robust approach in PSO. A case study is presented using a 21-bus MG from a real university campus in Portugal, and the projection of distributed energy resources based on the evolution scenario for the year 2050 managed by an aggregator.ElsevierREPOSITÓRIO P.PORTOBorges, NunoSoares, JoãoVale, Zita2021-03-09T11:25:58Z20172017-01-01T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10400.22/17319eng10.1016/j.ifacol.2017.08.521info: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:RCAAP2025-04-02T03:30:41Zoai:recipp.ipp.pt:10400.22/17319Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T00:59:12.113080Repositórios 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 Robust Optimization for Day-ahead Microgrid Dispatch Considering Uncertainties
title A Robust Optimization for Day-ahead Microgrid Dispatch Considering Uncertainties
spellingShingle A Robust Optimization for Day-ahead Microgrid Dispatch Considering Uncertainties
Borges, Nuno
Energy Resources Management
Microgrids
Particle Swarm Optimization
Robust Optimization
title_short A Robust Optimization for Day-ahead Microgrid Dispatch Considering Uncertainties
title_full A Robust Optimization for Day-ahead Microgrid Dispatch Considering Uncertainties
title_fullStr A Robust Optimization for Day-ahead Microgrid Dispatch Considering Uncertainties
title_full_unstemmed A Robust Optimization for Day-ahead Microgrid Dispatch Considering Uncertainties
title_sort A Robust Optimization for Day-ahead Microgrid Dispatch Considering Uncertainties
author Borges, Nuno
author_facet Borges, Nuno
Soares, João
Vale, Zita
author_role author
author2 Soares, João
Vale, Zita
author2_role author
author
dc.contributor.none.fl_str_mv REPOSITÓRIO P.PORTO
dc.contributor.author.fl_str_mv Borges, Nuno
Soares, João
Vale, Zita
dc.subject.por.fl_str_mv Energy Resources Management
Microgrids
Particle Swarm Optimization
Robust Optimization
topic Energy Resources Management
Microgrids
Particle Swarm Optimization
Robust Optimization
description This paper presents a Particle Swarm Optimization (PSO) methodology to solve the problem of day-ahead microgrid (MG) dispatch with high penetration of Distributed Generation (DG) and considering uncertainties. The proposed methodology has the objective to satisfy demand aiming at obtaining the maximum profit, corresponding to the difference between the income and costs of the MG. This methodology considers the uncertainties associated with the production of electricity by the photovoltaic and wind sources. This uncertainty is modeled with the use of a robust approach in PSO. A case study is presented using a 21-bus MG from a real university campus in Portugal, and the projection of distributed energy resources based on the evolution scenario for the year 2050 managed by an aggregator.
publishDate 2017
dc.date.none.fl_str_mv 2017
2017-01-01T00:00:00Z
2021-03-09T11:25:58Z
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/10400.22/17319
url http://hdl.handle.net/10400.22/17319
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1016/j.ifacol.2017.08.521
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 Elsevier
publisher.none.fl_str_mv Elsevier
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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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
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