Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.22/14937 |
Resumo: | A new era of cleaner distributed generators, like wind and solar, dispersed along the distribution network are gaining great importance and contributing to the environment and political goals. However, the variability and intermittency of those generators pose new complexities and challenges to the network planning. This research paper proposes an innovative stochastic methodology to deal with the expansion planning of large distribution networks in a smart grid context with high penetration of distributed renewable energy sources and considering the seasonal impact. Also, new power lines locations and types, the size and the location of energy storage systems are considered in the optimization. A distribution network with 180 buses located in Portugal considering high distributed generators penetration is used to illustrate the application of the proposed methodology. The results demonstrate the advantage of the stochastic model when compared with a deterministic formulation, avoiding the need for larger investments in new lines and energy storage systems. |
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Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generationDistribution networksEnergy storage systemsPlanningRenewable energy sourcesSmart gridStochastic systemsA new era of cleaner distributed generators, like wind and solar, dispersed along the distribution network are gaining great importance and contributing to the environment and political goals. However, the variability and intermittency of those generators pose new complexities and challenges to the network planning. This research paper proposes an innovative stochastic methodology to deal with the expansion planning of large distribution networks in a smart grid context with high penetration of distributed renewable energy sources and considering the seasonal impact. Also, new power lines locations and types, the size and the location of energy storage systems are considered in the optimization. A distribution network with 180 buses located in Portugal considering high distributed generators penetration is used to illustrate the application of the proposed methodology. The results demonstrate the advantage of the stochastic model when compared with a deterministic formulation, avoiding the need for larger investments in new lines and energy storage systems.This work has received funding from the EU's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAM-GO); from FEDER Funds through COMPETE program; from National Funds through FCT under the project UID/EEA/00760/2019 and from the project PTDC/EEI-EEE/28983/2017 - CENERGETIC. Bruno Canizes is supported by FCT Funds through SFRH/BD/110678/2015 PhD scholarship.ElsevierRepositório Científico do Instituto Politécnico do PortoCanizes, BrunoSoares, JoãoLezama, FernandoSilva, CátiaVale, ZitaCorchado, Juan Manuel20192119-01-01T00:00:00Z2019-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/14937eng10.1016/j.renene.2019.02.006info:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-13T12:58:38Zoai:recipp.ipp.pt:10400.22/14937Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:34:44.441779Repositório 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 |
Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation |
title |
Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation |
spellingShingle |
Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation Canizes, Bruno Distribution networks Energy storage systems Planning Renewable energy sources Smart grid Stochastic systems |
title_short |
Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation |
title_full |
Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation |
title_fullStr |
Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation |
title_full_unstemmed |
Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation |
title_sort |
Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation |
author |
Canizes, Bruno |
author_facet |
Canizes, Bruno Soares, João Lezama, Fernando Silva, Cátia Vale, Zita Corchado, Juan Manuel |
author_role |
author |
author2 |
Soares, João Lezama, Fernando Silva, Cátia Vale, Zita Corchado, Juan Manuel |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Repositório Científico do Instituto Politécnico do Porto |
dc.contributor.author.fl_str_mv |
Canizes, Bruno Soares, João Lezama, Fernando Silva, Cátia Vale, Zita Corchado, Juan Manuel |
dc.subject.por.fl_str_mv |
Distribution networks Energy storage systems Planning Renewable energy sources Smart grid Stochastic systems |
topic |
Distribution networks Energy storage systems Planning Renewable energy sources Smart grid Stochastic systems |
description |
A new era of cleaner distributed generators, like wind and solar, dispersed along the distribution network are gaining great importance and contributing to the environment and political goals. However, the variability and intermittency of those generators pose new complexities and challenges to the network planning. This research paper proposes an innovative stochastic methodology to deal with the expansion planning of large distribution networks in a smart grid context with high penetration of distributed renewable energy sources and considering the seasonal impact. Also, new power lines locations and types, the size and the location of energy storage systems are considered in the optimization. A distribution network with 180 buses located in Portugal considering high distributed generators penetration is used to illustrate the application of the proposed methodology. The results demonstrate the advantage of the stochastic model when compared with a deterministic formulation, avoiding the need for larger investments in new lines and energy storage systems. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019 2019-01-01T00:00:00Z 2119-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.22/14937 |
url |
http://hdl.handle.net/10400.22/14937 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1016/j.renene.2019.02.006 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/embargoedAccess |
eu_rights_str_mv |
embargoedAccess |
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: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 |
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1799131439707455488 |