Decentralized AC power flow for real-time multi-TSO power system operation
Autor(a) principal: | |
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Data de Publicação: | 2010 |
Outros Autores: | , , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/195967 |
Resumo: | This paper adjusts decentralized OPF optimization to the AC power flow problem in power systems with interconnected areas operated by diferent transmission system operators (TSO). The proposed methodology allows finding the operation point of a particular area without explicit knowledge of network data of the other interconnected areas, being only necessary to exchange border information related to the tie-lines between areas. The methodology is based on the decomposition of the first-order optimality conditions of the AC power flow, which is formulated as a nonlinear programming problem. To allow better visualization of the concept of independent operation of each TSO, an artificial neural network have been used for computing border information of the interconnected TSOs. A multi-area Power Flow tool can be seen as a basic building block able to address a large number of problems under a multi-TSO competitive market philosophy. The IEEE RTS-96 power system is used in order to show the operation and effectiveness of the decentralized AC Power Flow. |
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Decentralized AC power flow for real-time multi-TSO power system operationMulti-area power systemsdecomposition methodsdecentralized coordinationpower flowneural networksThis paper adjusts decentralized OPF optimization to the AC power flow problem in power systems with interconnected areas operated by diferent transmission system operators (TSO). The proposed methodology allows finding the operation point of a particular area without explicit knowledge of network data of the other interconnected areas, being only necessary to exchange border information related to the tie-lines between areas. The methodology is based on the decomposition of the first-order optimality conditions of the AC power flow, which is formulated as a nonlinear programming problem. To allow better visualization of the concept of independent operation of each TSO, an artificial neural network have been used for computing border information of the interconnected TSOs. A multi-area Power Flow tool can be seen as a basic building block able to address a large number of problems under a multi-TSO competitive market philosophy. The IEEE RTS-96 power system is used in order to show the operation and effectiveness of the decentralized AC Power Flow.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Universidad Tecnologica de Pereira (Colombia)Univ Tecnol Pereira, Elect Engn Program, Pereira, ColombiaUniv Estadual Paulista, Elect Power Syst Planning Lab, Sao Paulo, BrazilUNESP Univ Estadual Paulista, Fac Engenharia Ilha Solteira, Elect Power Syst Planning Lab, Sao Paulo, BrazilIIT, Dept Elect & Comp Engn, Chicago, IL USAUniv Estadual Paulista, Elect Power Syst Planning Lab, Sao Paulo, BrazilUNESP Univ Estadual Paulista, Fac Engenharia Ilha Solteira, Elect Power Syst Planning Lab, Sao Paulo, BrazilUniversidad Tecnologica de Pereira (Colombia): BEX 1202/06-5IeeeUniv Tecnol PereiraUniversidade Estadual Paulista (Unesp)IITGranada, Mauricio [UNESP]Rider, Marcos J. [UNESP]Mantovani, J. R. S. [UNESP]Shahidehpour, M.IEEE2020-12-10T18:47:52Z2020-12-10T18:47:52Z2010-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject7Ieee Power And Energy Society General Meeting 2010. New York: Ieee, 7 p., 2010.1944-9925http://hdl.handle.net/11449/195967WOS:000287611900128Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIeee Power And Energy Society General Meeting 2010info:eu-repo/semantics/openAccess2024-07-04T19:11:28Zoai:repositorio.unesp.br:11449/195967Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:30:12.322177Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Decentralized AC power flow for real-time multi-TSO power system operation |
title |
Decentralized AC power flow for real-time multi-TSO power system operation |
spellingShingle |
Decentralized AC power flow for real-time multi-TSO power system operation Granada, Mauricio [UNESP] Multi-area power systems decomposition methods decentralized coordination power flow neural networks |
title_short |
Decentralized AC power flow for real-time multi-TSO power system operation |
title_full |
Decentralized AC power flow for real-time multi-TSO power system operation |
title_fullStr |
Decentralized AC power flow for real-time multi-TSO power system operation |
title_full_unstemmed |
Decentralized AC power flow for real-time multi-TSO power system operation |
title_sort |
Decentralized AC power flow for real-time multi-TSO power system operation |
author |
Granada, Mauricio [UNESP] |
author_facet |
Granada, Mauricio [UNESP] Rider, Marcos J. [UNESP] Mantovani, J. R. S. [UNESP] Shahidehpour, M. IEEE |
author_role |
author |
author2 |
Rider, Marcos J. [UNESP] Mantovani, J. R. S. [UNESP] Shahidehpour, M. IEEE |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Univ Tecnol Pereira Universidade Estadual Paulista (Unesp) IIT |
dc.contributor.author.fl_str_mv |
Granada, Mauricio [UNESP] Rider, Marcos J. [UNESP] Mantovani, J. R. S. [UNESP] Shahidehpour, M. IEEE |
dc.subject.por.fl_str_mv |
Multi-area power systems decomposition methods decentralized coordination power flow neural networks |
topic |
Multi-area power systems decomposition methods decentralized coordination power flow neural networks |
description |
This paper adjusts decentralized OPF optimization to the AC power flow problem in power systems with interconnected areas operated by diferent transmission system operators (TSO). The proposed methodology allows finding the operation point of a particular area without explicit knowledge of network data of the other interconnected areas, being only necessary to exchange border information related to the tie-lines between areas. The methodology is based on the decomposition of the first-order optimality conditions of the AC power flow, which is formulated as a nonlinear programming problem. To allow better visualization of the concept of independent operation of each TSO, an artificial neural network have been used for computing border information of the interconnected TSOs. A multi-area Power Flow tool can be seen as a basic building block able to address a large number of problems under a multi-TSO competitive market philosophy. The IEEE RTS-96 power system is used in order to show the operation and effectiveness of the decentralized AC Power Flow. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010-01-01 2020-12-10T18:47:52Z 2020-12-10T18:47:52Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
Ieee Power And Energy Society General Meeting 2010. New York: Ieee, 7 p., 2010. 1944-9925 http://hdl.handle.net/11449/195967 WOS:000287611900128 |
identifier_str_mv |
Ieee Power And Energy Society General Meeting 2010. New York: Ieee, 7 p., 2010. 1944-9925 WOS:000287611900128 |
url |
http://hdl.handle.net/11449/195967 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Ieee Power And Energy Society General Meeting 2010 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
7 |
dc.publisher.none.fl_str_mv |
Ieee |
publisher.none.fl_str_mv |
Ieee |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128662617194496 |