Chronological Monte Carlo-based assessment of distribution system reliability

Detalhes bibliográficos
Autor(a) principal: Leite da Silva, Armando M.
Data de Publicação: 2006
Outros Autores: Cassula, Agnelo M. [UNESP], Nascimento, Luiz C., Freire, Jose C. [UNESP], Sacramento, Cleber E., Guimaraes, Ana Carolina R., IEEE
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://hdl.handle.net/11449/194665
Resumo: Regulatory authorities in many countries, in order to maintain an acceptable balance between appropriate customer service qualities and costs, are introducing a performance-based regulation. These regulations impose penalties, and in some cases rewards, which introduce a component of financial risk to an electric power utility due to the uncertainty associated with preserving a specific level of system reliability. In Brazil, for instance, one of the reliability indices receiving special attention by the utilities is the Maximum Continuous Interruption Duration per customer (MCID). This paper describes a chronological Monte Carlo simulation approach to evaluate probability distributions of reliability indices, including the MCID, and the corresponding penalties. In order to get the desired efficiency, modern computational techniques are used for modeling (UML - Unified Modeling Language) as well as for programming (Object- Oriented Programming). Case studies on a simple distribution network and on real Brazilian distribution systems are presented and discussed.
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spelling Chronological Monte Carlo-based assessment of distribution system reliabilitydistribution reliabilityobject-oriented programmingMarkov chainsMonte Carlo simulationRegulatory authorities in many countries, in order to maintain an acceptable balance between appropriate customer service qualities and costs, are introducing a performance-based regulation. These regulations impose penalties, and in some cases rewards, which introduce a component of financial risk to an electric power utility due to the uncertainty associated with preserving a specific level of system reliability. In Brazil, for instance, one of the reliability indices receiving special attention by the utilities is the Maximum Continuous Interruption Duration per customer (MCID). This paper describes a chronological Monte Carlo simulation approach to evaluate probability distributions of reliability indices, including the MCID, and the corresponding penalties. In order to get the desired efficiency, modern computational techniques are used for modeling (UML - Unified Modeling Language) as well as for programming (Object- Oriented Programming). Case studies on a simple distribution network and on real Brazilian distribution systems are presented and discussed.Fed Univ, Power Syst Eng Grp, Itajuba, MG, BrazilSao Paulo State Univ, UNESP, Guaratingueta, SP, BrazilCEMIG, Expans Planing Dept, Belo Horizonte, MG, BrazilSao Paulo State Univ, UNESP, Guaratingueta, SP, BrazilIeeeFed UnivUniversidade Estadual Paulista (Unesp)CEMIGLeite da Silva, Armando M.Cassula, Agnelo M. [UNESP]Nascimento, Luiz C.Freire, Jose C. [UNESP]Sacramento, Cleber E.Guimaraes, Ana Carolina R.IEEE2020-12-10T16:33:43Z2020-12-10T16:33:43Z2006-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject1165-11712006 International Conference On Probabilistic Methods Applied To Power Systems, Vols 1 And 2. New York: Ieee, p. 1165-1171, 2006.http://hdl.handle.net/11449/194665WOS:000246355900182Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2006 International Conference On Probabilistic Methods Applied To Power Systems, Vols 1 And 2info:eu-repo/semantics/openAccess2021-10-22T19:57:48Zoai:repositorio.unesp.br:11449/194665Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:02:01.813627Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Chronological Monte Carlo-based assessment of distribution system reliability
title Chronological Monte Carlo-based assessment of distribution system reliability
spellingShingle Chronological Monte Carlo-based assessment of distribution system reliability
Leite da Silva, Armando M.
distribution reliability
object-oriented programming
Markov chains
Monte Carlo simulation
title_short Chronological Monte Carlo-based assessment of distribution system reliability
title_full Chronological Monte Carlo-based assessment of distribution system reliability
title_fullStr Chronological Monte Carlo-based assessment of distribution system reliability
title_full_unstemmed Chronological Monte Carlo-based assessment of distribution system reliability
title_sort Chronological Monte Carlo-based assessment of distribution system reliability
author Leite da Silva, Armando M.
author_facet Leite da Silva, Armando M.
Cassula, Agnelo M. [UNESP]
Nascimento, Luiz C.
Freire, Jose C. [UNESP]
Sacramento, Cleber E.
Guimaraes, Ana Carolina R.
IEEE
author_role author
author2 Cassula, Agnelo M. [UNESP]
Nascimento, Luiz C.
Freire, Jose C. [UNESP]
Sacramento, Cleber E.
Guimaraes, Ana Carolina R.
IEEE
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Fed Univ
Universidade Estadual Paulista (Unesp)
CEMIG
dc.contributor.author.fl_str_mv Leite da Silva, Armando M.
Cassula, Agnelo M. [UNESP]
Nascimento, Luiz C.
Freire, Jose C. [UNESP]
Sacramento, Cleber E.
Guimaraes, Ana Carolina R.
IEEE
dc.subject.por.fl_str_mv distribution reliability
object-oriented programming
Markov chains
Monte Carlo simulation
topic distribution reliability
object-oriented programming
Markov chains
Monte Carlo simulation
description Regulatory authorities in many countries, in order to maintain an acceptable balance between appropriate customer service qualities and costs, are introducing a performance-based regulation. These regulations impose penalties, and in some cases rewards, which introduce a component of financial risk to an electric power utility due to the uncertainty associated with preserving a specific level of system reliability. In Brazil, for instance, one of the reliability indices receiving special attention by the utilities is the Maximum Continuous Interruption Duration per customer (MCID). This paper describes a chronological Monte Carlo simulation approach to evaluate probability distributions of reliability indices, including the MCID, and the corresponding penalties. In order to get the desired efficiency, modern computational techniques are used for modeling (UML - Unified Modeling Language) as well as for programming (Object- Oriented Programming). Case studies on a simple distribution network and on real Brazilian distribution systems are presented and discussed.
publishDate 2006
dc.date.none.fl_str_mv 2006-01-01
2020-12-10T16:33:43Z
2020-12-10T16:33:43Z
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 2006 International Conference On Probabilistic Methods Applied To Power Systems, Vols 1 And 2. New York: Ieee, p. 1165-1171, 2006.
http://hdl.handle.net/11449/194665
WOS:000246355900182
identifier_str_mv 2006 International Conference On Probabilistic Methods Applied To Power Systems, Vols 1 And 2. New York: Ieee, p. 1165-1171, 2006.
WOS:000246355900182
url http://hdl.handle.net/11449/194665
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2006 International Conference On Probabilistic Methods Applied To Power Systems, Vols 1 And 2
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 1165-1171
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
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