Dynamic distribution system reconfiguration considering distributed renewable energy sources and energy storage systems

Detalhes bibliográficos
Autor(a) principal: Santos, Sérgio F.
Data de Publicação: 2022
Outros Autores: Gough, Matthew, Fitiwi, Desta Z., Pogeira, José, Shafie-khah, Miadreza, Catalão, João P. S.
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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spelling 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
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