Specialized genetic algorithm for transmission network expansion planning considering reliability
Autor(a) principal: | |
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Data de Publicação: | 2009 |
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/ISAP.2009.5352832 http://hdl.handle.net/11449/71476 |
Resumo: | This paper presents a methodology to solve the transmission network expansion planning problem (TNEP) considering reliability and uncertainty in the demand. The proposed methodology provides an optimal expansion plan that allows the power system to operate adequately with an acceptable level of reliability and in an enviroment with uncertainness. The reliability criterion limits the expected value of the reliability index (LOLE - Loss Of Load Expectation) of the expanded system. The reliability is evaluated for the transmission system using an analytical technique based in enumeration. The mathematical model is solved, in a efficient way, using a specialized genetic algorithm of Chu-Beasley modified. Detailed results from an illustrative example are presented and discussed. © 2009 IEEE. |
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Specialized genetic algorithm for transmission network expansion planning considering reliabilityGenetic algorithmMixed-integer non linear programmingReliabilityTransmission expansion planningAnalytical techniquesExpansion plansExpected valuesIllustrative examplesLoss of load expectationPower systemsReliability criterionReliability IndexTransmission network expansion planningTransmission systemsDynamic programmingElectric power transmissionElectric power transmission networksGenetic algorithmsInteger programmingIntelligent systemsLinearizationMathematical modelsOptimizationThis paper presents a methodology to solve the transmission network expansion planning problem (TNEP) considering reliability and uncertainty in the demand. The proposed methodology provides an optimal expansion plan that allows the power system to operate adequately with an acceptable level of reliability and in an enviroment with uncertainness. The reliability criterion limits the expected value of the reliability index (LOLE - Loss Of Load Expectation) of the expanded system. The reliability is evaluated for the transmission system using an analytical technique based in enumeration. The mathematical model is solved, in a efficient way, using a specialized genetic algorithm of Chu-Beasley modified. Detailed results from an illustrative example are presented and discussed. © 2009 IEEE.Department of Electrical Engineering Paulista State University - UNESP, Ilha Solteira, Sao Paulo, 15385-000Department of Electrical Engineering Paulista State University - UNESP, Ilha Solteira, Sao Paulo, 15385-000Universidade Estadual Paulista (Unesp)Garcés, Lina [UNESP]Romero, Rubén [UNESP]2014-05-27T11:24:34Z2014-05-27T11:24:34Z2009-12-09info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/ISAP.2009.53528322009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09.http://hdl.handle.net/11449/7147610.1109/ISAP.2009.53528322-s2.0-76549094515Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09info:eu-repo/semantics/openAccess2024-07-04T19:11:44Zoai:repositorio.unesp.br:11449/71476Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:08:07.476983Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Specialized genetic algorithm for transmission network expansion planning considering reliability |
title |
Specialized genetic algorithm for transmission network expansion planning considering reliability |
spellingShingle |
Specialized genetic algorithm for transmission network expansion planning considering reliability Garcés, Lina [UNESP] Genetic algorithm Mixed-integer non linear programming Reliability Transmission expansion planning Analytical techniques Expansion plans Expected values Illustrative examples Loss of load expectation Power systems Reliability criterion Reliability Index Transmission network expansion planning Transmission systems Dynamic programming Electric power transmission Electric power transmission networks Genetic algorithms Integer programming Intelligent systems Linearization Mathematical models Optimization |
title_short |
Specialized genetic algorithm for transmission network expansion planning considering reliability |
title_full |
Specialized genetic algorithm for transmission network expansion planning considering reliability |
title_fullStr |
Specialized genetic algorithm for transmission network expansion planning considering reliability |
title_full_unstemmed |
Specialized genetic algorithm for transmission network expansion planning considering reliability |
title_sort |
Specialized genetic algorithm for transmission network expansion planning considering reliability |
author |
Garcés, Lina [UNESP] |
author_facet |
Garcés, Lina [UNESP] Romero, Rubén [UNESP] |
author_role |
author |
author2 |
Romero, Rubén [UNESP] |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Garcés, Lina [UNESP] Romero, Rubén [UNESP] |
dc.subject.por.fl_str_mv |
Genetic algorithm Mixed-integer non linear programming Reliability Transmission expansion planning Analytical techniques Expansion plans Expected values Illustrative examples Loss of load expectation Power systems Reliability criterion Reliability Index Transmission network expansion planning Transmission systems Dynamic programming Electric power transmission Electric power transmission networks Genetic algorithms Integer programming Intelligent systems Linearization Mathematical models Optimization |
topic |
Genetic algorithm Mixed-integer non linear programming Reliability Transmission expansion planning Analytical techniques Expansion plans Expected values Illustrative examples Loss of load expectation Power systems Reliability criterion Reliability Index Transmission network expansion planning Transmission systems Dynamic programming Electric power transmission Electric power transmission networks Genetic algorithms Integer programming Intelligent systems Linearization Mathematical models Optimization |
description |
This paper presents a methodology to solve the transmission network expansion planning problem (TNEP) considering reliability and uncertainty in the demand. The proposed methodology provides an optimal expansion plan that allows the power system to operate adequately with an acceptable level of reliability and in an enviroment with uncertainness. The reliability criterion limits the expected value of the reliability index (LOLE - Loss Of Load Expectation) of the expanded system. The reliability is evaluated for the transmission system using an analytical technique based in enumeration. The mathematical model is solved, in a efficient way, using a specialized genetic algorithm of Chu-Beasley modified. Detailed results from an illustrative example are presented and discussed. © 2009 IEEE. |
publishDate |
2009 |
dc.date.none.fl_str_mv |
2009-12-09 2014-05-27T11:24:34Z 2014-05-27T11:24:34Z |
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/ISAP.2009.5352832 2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09. http://hdl.handle.net/11449/71476 10.1109/ISAP.2009.5352832 2-s2.0-76549094515 |
url |
http://dx.doi.org/10.1109/ISAP.2009.5352832 http://hdl.handle.net/11449/71476 |
identifier_str_mv |
2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09. 10.1109/ISAP.2009.5352832 2-s2.0-76549094515 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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_ |
1808129164227641344 |