Mathematical decomposition technique applied to the probabilistic power flow problem
Autor(a) principal: | |
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Data de Publicação: | 2011 |
Outros Autores: | , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/TDC-LA.2010.5762874 http://hdl.handle.net/11449/72446 |
Resumo: | In this paper a framework based on the decomposition of the first-order optimality conditions is described and applied to solve the Probabilistic Power Flow (PPF) problem in a coordinated but decentralized way in the context of multi-area power systems. The purpose of the decomposition framework is to solve the problem through a process of solving smaller subproblems, associated with each area of the power system, iteratively. This strategy allows the probabilistic analysis of the variables of interest, in 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. An efficient method for probabilistic analysis, considering uncertainty in n system loads, is applied. The proposal is to use a particular case of the point estimate method, known as Two-Point Estimate Method (TPM), rather than the traditional approach based on Monte Carlo simulation. The main feature of the TPM is that it only requires resolve 2n power flows for to obtain the behavior of any random variable. An iterative coordination algorithm between areas is also presented. This algorithm solves the Multi-Area PPF problem in a decentralized way, ensures the independent operation of each area and integrates the decomposition framework and the TPM appropriately. The IEEE RTS-96 system is used in order to show the operation and effectiveness of the proposed approach and the Monte Carlo simulations are used to validation of the results. © 2011 IEEE. |
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Mathematical decomposition technique applied to the probabilistic power flow problemdecentralized coordinationDecomposition methodsMA-PPFmulti-area power systemsprobabilistic power flowDecentralized coordinationMulti area power systemsProbabilistic power flowAlgorithmsComputer simulationElectric power transmissionKnowledge managementMonte Carlo methodsPower transmissionProbability distributionsRandom variablesThermoelectric powerUncertainty analysisProblem solvingIn this paper a framework based on the decomposition of the first-order optimality conditions is described and applied to solve the Probabilistic Power Flow (PPF) problem in a coordinated but decentralized way in the context of multi-area power systems. The purpose of the decomposition framework is to solve the problem through a process of solving smaller subproblems, associated with each area of the power system, iteratively. This strategy allows the probabilistic analysis of the variables of interest, in 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. An efficient method for probabilistic analysis, considering uncertainty in n system loads, is applied. The proposal is to use a particular case of the point estimate method, known as Two-Point Estimate Method (TPM), rather than the traditional approach based on Monte Carlo simulation. The main feature of the TPM is that it only requires resolve 2n power flows for to obtain the behavior of any random variable. An iterative coordination algorithm between areas is also presented. This algorithm solves the Multi-Area PPF problem in a decentralized way, ensures the independent operation of each area and integrates the decomposition framework and the TPM appropriately. The IEEE RTS-96 system is used in order to show the operation and effectiveness of the proposed approach and the Monte Carlo simulations are used to validation of the results. © 2011 IEEE.Department of Electrical Engineering Universidad Tecnológica de PereiraElectric Power System Planning Laboratory UNESPFaculdade de Engenharia de Ilha Solteira UNESP - Universidade Estadual PaulistaElectric Power System Planning Laboratory UNESPFaculdade de Engenharia de Ilha Solteira UNESP - Universidade Estadual PaulistaUniversidad Tecnológica de PereiraUniversidade Estadual Paulista (Unesp)Mauricio, Granada E. [UNESP]Rider, Marcos J. [UNESP]Mantovani, J. R S [UNESP]2014-05-27T11:25:53Z2014-05-27T11:25:53Z2011-05-31info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject139-146http://dx.doi.org/10.1109/TDC-LA.2010.57628742010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA 2010, p. 139-146.http://hdl.handle.net/11449/7244610.1109/TDC-LA.2010.57628742-s2.0-799575605080614021283361265Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA 2010info:eu-repo/semantics/openAccess2024-07-04T19:11:27Zoai:repositorio.unesp.br:11449/72446Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:00:25.906639Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Mathematical decomposition technique applied to the probabilistic power flow problem |
title |
Mathematical decomposition technique applied to the probabilistic power flow problem |
spellingShingle |
Mathematical decomposition technique applied to the probabilistic power flow problem Mauricio, Granada E. [UNESP] decentralized coordination Decomposition methods MA-PPF multi-area power systems probabilistic power flow Decentralized coordination Multi area power systems Probabilistic power flow Algorithms Computer simulation Electric power transmission Knowledge management Monte Carlo methods Power transmission Probability distributions Random variables Thermoelectric power Uncertainty analysis Problem solving |
title_short |
Mathematical decomposition technique applied to the probabilistic power flow problem |
title_full |
Mathematical decomposition technique applied to the probabilistic power flow problem |
title_fullStr |
Mathematical decomposition technique applied to the probabilistic power flow problem |
title_full_unstemmed |
Mathematical decomposition technique applied to the probabilistic power flow problem |
title_sort |
Mathematical decomposition technique applied to the probabilistic power flow problem |
author |
Mauricio, Granada E. [UNESP] |
author_facet |
Mauricio, Granada E. [UNESP] Rider, Marcos J. [UNESP] Mantovani, J. R S [UNESP] |
author_role |
author |
author2 |
Rider, Marcos J. [UNESP] Mantovani, J. R S [UNESP] |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidad Tecnológica de Pereira Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Mauricio, Granada E. [UNESP] Rider, Marcos J. [UNESP] Mantovani, J. R S [UNESP] |
dc.subject.por.fl_str_mv |
decentralized coordination Decomposition methods MA-PPF multi-area power systems probabilistic power flow Decentralized coordination Multi area power systems Probabilistic power flow Algorithms Computer simulation Electric power transmission Knowledge management Monte Carlo methods Power transmission Probability distributions Random variables Thermoelectric power Uncertainty analysis Problem solving |
topic |
decentralized coordination Decomposition methods MA-PPF multi-area power systems probabilistic power flow Decentralized coordination Multi area power systems Probabilistic power flow Algorithms Computer simulation Electric power transmission Knowledge management Monte Carlo methods Power transmission Probability distributions Random variables Thermoelectric power Uncertainty analysis Problem solving |
description |
In this paper a framework based on the decomposition of the first-order optimality conditions is described and applied to solve the Probabilistic Power Flow (PPF) problem in a coordinated but decentralized way in the context of multi-area power systems. The purpose of the decomposition framework is to solve the problem through a process of solving smaller subproblems, associated with each area of the power system, iteratively. This strategy allows the probabilistic analysis of the variables of interest, in 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. An efficient method for probabilistic analysis, considering uncertainty in n system loads, is applied. The proposal is to use a particular case of the point estimate method, known as Two-Point Estimate Method (TPM), rather than the traditional approach based on Monte Carlo simulation. The main feature of the TPM is that it only requires resolve 2n power flows for to obtain the behavior of any random variable. An iterative coordination algorithm between areas is also presented. This algorithm solves the Multi-Area PPF problem in a decentralized way, ensures the independent operation of each area and integrates the decomposition framework and the TPM appropriately. The IEEE RTS-96 system is used in order to show the operation and effectiveness of the proposed approach and the Monte Carlo simulations are used to validation of the results. © 2011 IEEE. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-05-31 2014-05-27T11:25:53Z 2014-05-27T11:25:53Z |
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 |
http://dx.doi.org/10.1109/TDC-LA.2010.5762874 2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA 2010, p. 139-146. http://hdl.handle.net/11449/72446 10.1109/TDC-LA.2010.5762874 2-s2.0-79957560508 0614021283361265 |
url |
http://dx.doi.org/10.1109/TDC-LA.2010.5762874 http://hdl.handle.net/11449/72446 |
identifier_str_mv |
2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA 2010, p. 139-146. 10.1109/TDC-LA.2010.5762874 2-s2.0-79957560508 0614021283361265 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA 2010 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
139-146 |
dc.source.none.fl_str_mv |
Scopus 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_ |
1808128592638377984 |