A Robust Optimization for Day-ahead Microgrid Dispatch Considering Uncertainties
| Main Author: | |
|---|---|
| Publication Date: | 2017 |
| Other Authors: | , |
| 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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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 |
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2017 2017-01-01T00:00:00Z 2021-03-09T11:25:58Z |
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conference object |
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info:eu-repo/semantics/publishedVersion |
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publishedVersion |
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http://hdl.handle.net/10400.22/17319 |
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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 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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Elsevier |
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Elsevier |
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