Optimal Reactive Power Planning Using Risk Analysis

Detalhes bibliográficos
Autor(a) principal: Lopez, Julio C. [UNESP]
Data de Publicação: 2013
Outros Autores: Mantovani, J. R. S. [UNESP], Contreras Sanz, Javier, Munoz, Jose I., IEEE
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/PESMG.2013.6672114
http://hdl.handle.net/11449/113624
Resumo: In this paper, the optimal reactive power planning problem under risk is presented. The classical mixed-integer nonlinear model for reactive power planning is expanded into two stage stochastic model considering risk. This new model considers uncertainty on the demand load. The risk is quantified by a factor introduced into the objective function and is identified as the variance of the random variables. Finally numerical results illustrate the performance of the proposed model, that is applied to IEEE 30-bus test system to determine optimal amount and location for reactive power expansion.
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spelling Optimal Reactive Power Planning Using Risk AnalysisMean-variancereactive power planningstochastic programmingtwo - stageuncertaintyIn this paper, the optimal reactive power planning problem under risk is presented. The classical mixed-integer nonlinear model for reactive power planning is expanded into two stage stochastic model considering risk. This new model considers uncertainty on the demand load. The risk is quantified by a factor introduced into the objective function and is identified as the variance of the random variables. Finally numerical results illustrate the performance of the proposed model, that is applied to IEEE 30-bus test system to determine optimal amount and location for reactive power expansion.Sao Paulo State Univ UNESP, Dept Elect Engn, Ilha Solteira, SP, BrazilSao Paulo State Univ UNESP, Dept Elect Engn, Ilha Solteira, SP, BrazilIeeeUniversidade Estadual Paulista (Unesp)Lopez, Julio C. [UNESP]Mantovani, J. R. S. [UNESP]Contreras Sanz, JavierMunoz, Jose I.IEEE2014-12-03T13:11:50Z2014-12-03T13:11:50Z2013-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject5http://dx.doi.org/10.1109/PESMG.2013.66721142013 IEEE Power and Energy Society General Meeting (pes). New York: IEEE, 5 p., 2013.1944-9925http://hdl.handle.net/11449/113624WOS:0003318743000450614021283361265Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2013 IEEE Power And Energy Society General Meeting (pes)0,328info:eu-repo/semantics/openAccess2021-10-23T21:44:11Zoai:repositorio.unesp.br:11449/113624Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T21:44:11Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Optimal Reactive Power Planning Using Risk Analysis
title Optimal Reactive Power Planning Using Risk Analysis
spellingShingle Optimal Reactive Power Planning Using Risk Analysis
Lopez, Julio C. [UNESP]
Mean-variance
reactive power planning
stochastic programming
two - stage
uncertainty
title_short Optimal Reactive Power Planning Using Risk Analysis
title_full Optimal Reactive Power Planning Using Risk Analysis
title_fullStr Optimal Reactive Power Planning Using Risk Analysis
title_full_unstemmed Optimal Reactive Power Planning Using Risk Analysis
title_sort Optimal Reactive Power Planning Using Risk Analysis
author Lopez, Julio C. [UNESP]
author_facet Lopez, Julio C. [UNESP]
Mantovani, J. R. S. [UNESP]
Contreras Sanz, Javier
Munoz, Jose I.
IEEE
author_role author
author2 Mantovani, J. R. S. [UNESP]
Contreras Sanz, Javier
Munoz, Jose I.
IEEE
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Lopez, Julio C. [UNESP]
Mantovani, J. R. S. [UNESP]
Contreras Sanz, Javier
Munoz, Jose I.
IEEE
dc.subject.por.fl_str_mv Mean-variance
reactive power planning
stochastic programming
two - stage
uncertainty
topic Mean-variance
reactive power planning
stochastic programming
two - stage
uncertainty
description In this paper, the optimal reactive power planning problem under risk is presented. The classical mixed-integer nonlinear model for reactive power planning is expanded into two stage stochastic model considering risk. This new model considers uncertainty on the demand load. The risk is quantified by a factor introduced into the objective function and is identified as the variance of the random variables. Finally numerical results illustrate the performance of the proposed model, that is applied to IEEE 30-bus test system to determine optimal amount and location for reactive power expansion.
publishDate 2013
dc.date.none.fl_str_mv 2013-01-01
2014-12-03T13:11:50Z
2014-12-03T13:11:50Z
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/PESMG.2013.6672114
2013 IEEE Power and Energy Society General Meeting (pes). New York: IEEE, 5 p., 2013.
1944-9925
http://hdl.handle.net/11449/113624
WOS:000331874300045
0614021283361265
url http://dx.doi.org/10.1109/PESMG.2013.6672114
http://hdl.handle.net/11449/113624
identifier_str_mv 2013 IEEE Power and Energy Society General Meeting (pes). New York: IEEE, 5 p., 2013.
1944-9925
WOS:000331874300045
0614021283361265
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2013 IEEE Power And Energy Society General Meeting (pes)
0,328
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 5
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_ 1803046304616546304

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