SEABASS - System Enhanced Alternatives with Battery Storage Systems
Autor(a) principal: | |
---|---|
Data de Publicação: | 2020 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/10216/132957 |
Resumo: | In this paper, an optimization model is presented for the solving a multi period operation problem for battery energy storage systems, and an investment analysis. The batteries are installed in a distribution medium voltage grid environment, in which stochastic consumption and dispersed generation profiles were considered, as well as penalty factors for power flow and technical grid constrains. Since the problem is characterized to have a large dimension, with dependences between time periods, the optimization requires a model with high efficiency and low computational weight. The solution presented is an alternative variant of Benders decomposition, with connected multi time stages called dual dynamic programming, that allows the division of the main problem in smaller subproblems, that are easier to solve separately. An integral linear programing model was also implemented to compare the results between both approaches. The results suggest that the utilization of the dual dynamic programming, in this case study, increased the computational performance, as well as good battery operation solutions. |
id |
RCAP_2d84781909c6464b521d3ceabcce2fac |
---|---|
oai_identifier_str |
oai:repositorio-aberto.up.pt:10216/132957 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
SEABASS - System Enhanced Alternatives with Battery Storage SystemsEngenharia electrotécnica, electrónica e informáticaElectrical engineering, Electronic engineering, Information engineeringIn this paper, an optimization model is presented for the solving a multi period operation problem for battery energy storage systems, and an investment analysis. The batteries are installed in a distribution medium voltage grid environment, in which stochastic consumption and dispersed generation profiles were considered, as well as penalty factors for power flow and technical grid constrains. Since the problem is characterized to have a large dimension, with dependences between time periods, the optimization requires a model with high efficiency and low computational weight. The solution presented is an alternative variant of Benders decomposition, with connected multi time stages called dual dynamic programming, that allows the division of the main problem in smaller subproblems, that are easier to solve separately. An integral linear programing model was also implemented to compare the results between both approaches. The results suggest that the utilization of the dual dynamic programming, in this case study, increased the computational performance, as well as good battery operation solutions.2020-07-212020-07-21T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://hdl.handle.net/10216/132957TID:202594645engRicardo Jorge Novais da Costainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T16:15:24Zoai:repositorio-aberto.up.pt:10216/132957Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:40:01.970373Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
SEABASS - System Enhanced Alternatives with Battery Storage Systems |
title |
SEABASS - System Enhanced Alternatives with Battery Storage Systems |
spellingShingle |
SEABASS - System Enhanced Alternatives with Battery Storage Systems Ricardo Jorge Novais da Costa Engenharia electrotécnica, electrónica e informática Electrical engineering, Electronic engineering, Information engineering |
title_short |
SEABASS - System Enhanced Alternatives with Battery Storage Systems |
title_full |
SEABASS - System Enhanced Alternatives with Battery Storage Systems |
title_fullStr |
SEABASS - System Enhanced Alternatives with Battery Storage Systems |
title_full_unstemmed |
SEABASS - System Enhanced Alternatives with Battery Storage Systems |
title_sort |
SEABASS - System Enhanced Alternatives with Battery Storage Systems |
author |
Ricardo Jorge Novais da Costa |
author_facet |
Ricardo Jorge Novais da Costa |
author_role |
author |
dc.contributor.author.fl_str_mv |
Ricardo Jorge Novais da Costa |
dc.subject.por.fl_str_mv |
Engenharia electrotécnica, electrónica e informática Electrical engineering, Electronic engineering, Information engineering |
topic |
Engenharia electrotécnica, electrónica e informática Electrical engineering, Electronic engineering, Information engineering |
description |
In this paper, an optimization model is presented for the solving a multi period operation problem for battery energy storage systems, and an investment analysis. The batteries are installed in a distribution medium voltage grid environment, in which stochastic consumption and dispersed generation profiles were considered, as well as penalty factors for power flow and technical grid constrains. Since the problem is characterized to have a large dimension, with dependences between time periods, the optimization requires a model with high efficiency and low computational weight. The solution presented is an alternative variant of Benders decomposition, with connected multi time stages called dual dynamic programming, that allows the division of the main problem in smaller subproblems, that are easier to solve separately. An integral linear programing model was also implemented to compare the results between both approaches. The results suggest that the utilization of the dual dynamic programming, in this case study, increased the computational performance, as well as good battery operation solutions. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-07-21 2020-07-21T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10216/132957 TID:202594645 |
url |
https://hdl.handle.net/10216/132957 |
identifier_str_mv |
TID:202594645 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799136306354192384 |