Dynamic distribution system reconfiguration considering distributed renewable energy sources and energy storage systems
Autor(a) principal: | |
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Data de Publicação: | 2022 |
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/11328/4422 |
Resumo: | Electric power systems are in state of transition as they attempt to evolve to meet new challenges provided by growing environmental concerns, increases in the penetration of distributed renewable energy sources (DRES) as well as the challenges associated with integrating new technologies to enable smart grids. New techniques to improve the electrical power system, including the distribution system, are thus needed. One such technique is dynamic distribution system reconfiguration (DNSR), which involves altering the network topology during operation, providing significant benefits regarding the increased integration of DRES. This paper lays out an improved model which aimed to optimize the system operation in a coordinated way, where DRES, energy storage systems (ESS) and DNSR are considered as well as the uncertainty of these resources. The objective function was modeled to incentivize the uptake of DRES by considering the cost of emissions to incentivize the decarbonization of the power system. Also, the switching costs were modeled to consider not only the switching, but also the cost of degradation of these mechanisms in the system operation. Two systems are used to validate the model, the IEEE 119-bus system, and a real system in São Miguel Island. The results of this paper show that using DNSR, DRES, and ESS can lead to a significant 59% reduction in energy demand through a 24-hour period. In addition, using these technologies results in a healthier, more efficient, and higher quality system. This shows the benefits of using a variety of smart grid technologies in a coordinated manner. |
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Dynamic distribution system reconfiguration considering distributed renewable energy sources and energy storage systemsDistribution systemsEnergy storage systems (ESSs)Renewable power generationStochastic mixed-integer linear programming (SMILP)Electric power systems are in state of transition as they attempt to evolve to meet new challenges provided by growing environmental concerns, increases in the penetration of distributed renewable energy sources (DRES) as well as the challenges associated with integrating new technologies to enable smart grids. New techniques to improve the electrical power system, including the distribution system, are thus needed. One such technique is dynamic distribution system reconfiguration (DNSR), which involves altering the network topology during operation, providing significant benefits regarding the increased integration of DRES. This paper lays out an improved model which aimed to optimize the system operation in a coordinated way, where DRES, energy storage systems (ESS) and DNSR are considered as well as the uncertainty of these resources. The objective function was modeled to incentivize the uptake of DRES by considering the cost of emissions to incentivize the decarbonization of the power system. Also, the switching costs were modeled to consider not only the switching, but also the cost of degradation of these mechanisms in the system operation. Two systems are used to validate the model, the IEEE 119-bus system, and a real system in São Miguel Island. The results of this paper show that using DNSR, DRES, and ESS can lead to a significant 59% reduction in energy demand through a 24-hour period. In addition, using these technologies results in a healthier, more efficient, and higher quality system. This shows the benefits of using a variety of smart grid technologies in a coordinated manner.IEEE2022-09-06T09:27:30Z2022-09-01T00:00:00Z2022-09info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/11328/4422eng1932-8184 (Print)1937-9234 (Electronic)10.1109/JSYST.2021.3135716Santos, Sérgio F.Gough, MatthewFitiwi, Desta Z.Pogeira, JoséShafie-khah, MiadrezaCatalão, João P. S.info: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:RCAAP2023-06-15T02:13:05ZPortal AgregadorONG |
dc.title.none.fl_str_mv |
Dynamic distribution system reconfiguration considering distributed renewable energy sources and energy storage systems |
title |
Dynamic distribution system reconfiguration considering distributed renewable energy sources and energy storage systems |
spellingShingle |
Dynamic distribution system reconfiguration considering distributed renewable energy sources and energy storage systems Santos, Sérgio F. Distribution systems Energy storage systems (ESSs) Renewable power generation Stochastic mixed-integer linear programming (SMILP) |
title_short |
Dynamic distribution system reconfiguration considering distributed renewable energy sources and energy storage systems |
title_full |
Dynamic distribution system reconfiguration considering distributed renewable energy sources and energy storage systems |
title_fullStr |
Dynamic distribution system reconfiguration considering distributed renewable energy sources and energy storage systems |
title_full_unstemmed |
Dynamic distribution system reconfiguration considering distributed renewable energy sources and energy storage systems |
title_sort |
Dynamic distribution system reconfiguration considering distributed renewable energy sources and energy storage systems |
author |
Santos, Sérgio F. |
author_facet |
Santos, Sérgio F. Gough, Matthew Fitiwi, Desta Z. Pogeira, José Shafie-khah, Miadreza Catalão, João P. S. |
author_role |
author |
author2 |
Gough, Matthew Fitiwi, Desta Z. Pogeira, José Shafie-khah, Miadreza Catalão, João P. S. |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Santos, Sérgio F. Gough, Matthew Fitiwi, Desta Z. Pogeira, José Shafie-khah, Miadreza Catalão, João P. S. |
dc.subject.por.fl_str_mv |
Distribution systems Energy storage systems (ESSs) Renewable power generation Stochastic mixed-integer linear programming (SMILP) |
topic |
Distribution systems Energy storage systems (ESSs) Renewable power generation Stochastic mixed-integer linear programming (SMILP) |
description |
Electric power systems are in state of transition as they attempt to evolve to meet new challenges provided by growing environmental concerns, increases in the penetration of distributed renewable energy sources (DRES) as well as the challenges associated with integrating new technologies to enable smart grids. New techniques to improve the electrical power system, including the distribution system, are thus needed. One such technique is dynamic distribution system reconfiguration (DNSR), which involves altering the network topology during operation, providing significant benefits regarding the increased integration of DRES. This paper lays out an improved model which aimed to optimize the system operation in a coordinated way, where DRES, energy storage systems (ESS) and DNSR are considered as well as the uncertainty of these resources. The objective function was modeled to incentivize the uptake of DRES by considering the cost of emissions to incentivize the decarbonization of the power system. Also, the switching costs were modeled to consider not only the switching, but also the cost of degradation of these mechanisms in the system operation. Two systems are used to validate the model, the IEEE 119-bus system, and a real system in São Miguel Island. The results of this paper show that using DNSR, DRES, and ESS can lead to a significant 59% reduction in energy demand through a 24-hour period. In addition, using these technologies results in a healthier, more efficient, and higher quality system. This shows the benefits of using a variety of smart grid technologies in a coordinated manner. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-09-06T09:27:30Z 2022-09-01T00:00:00Z 2022-09 |
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/11328/4422 |
url |
http://hdl.handle.net/11328/4422 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1932-8184 (Print) 1937-9234 (Electronic) 10.1109/JSYST.2021.3135716 |
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:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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repository.mail.fl_str_mv |
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1777302557349117952 |