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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/69253
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dc.contributor.authorDa Silva, Armando M. Leite-
dc.contributor.authorCassula, Agnelo M.-
dc.contributor.authorNascimento, Luiz C.-
dc.contributor.authorFreire Jr., José C.-
dc.contributor.authorSacramento, Cleber E.-
dc.contributor.authorGuimarães, Ana Carolina R.-
dc.date.accessioned2014-05-27T11:22:03Z-
dc.date.accessioned2016-10-25T18:23:00Z-
dc.date.available2014-05-27T11:22:03Z-
dc.date.available2016-10-25T18:23:00Z-
dc.date.issued2006-12-01-
dc.identifierhttp://dx.doi.org/10.1109/PMAPS.2006.360423-
dc.identifier.citation2006 9th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS.-
dc.identifier.urihttp://hdl.handle.net/11449/69253-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/69253-
dc.description.abstractRegulatory 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. © Copyright KTH 2006.en
dc.language.isoeng-
dc.sourceScopus-
dc.subjectDistribution reliability-
dc.subjectMarkov chains-
dc.subjectMonte Carlo simulation-
dc.subjectObject-oriented programming-
dc.subjectCanning-
dc.subjectComputational efficiency-
dc.subjectComputer programming languages-
dc.subjectCosmic ray detectors-
dc.subjectDistributed parameter networks-
dc.subjectDistribution of goods-
dc.subjectElectric power distribution-
dc.subjectElectric power systems-
dc.subjectElectric power transmission networks-
dc.subjectLaws and legislation-
dc.subjectLocal area networks-
dc.subjectMonte Carlo methods-
dc.subjectObject oriented programming-
dc.subjectPower transmission-
dc.subjectProbability-
dc.subjectPumps-
dc.subjectRisk assessment-
dc.subjectUnified Modeling Language-
dc.subjectApplied (CO)-
dc.subjectBalance (weighting)-
dc.subjectcase studies-
dc.subjectComputational techniques-
dc.subjectCustomer services-
dc.subjectdistribution networks-
dc.subjectDistribution system reliability-
dc.subjectDistribution systems-
dc.subjectElectric power utilities-
dc.subjectFinancial risks-
dc.subjectIn order-
dc.subjectinternational conferences-
dc.subjectMaximum continuous interruption duration (MCID)-
dc.subjectMonte Carlo (MC)-
dc.subjectMonte Carlo Simulation (MCS)-
dc.subjectPerformance-based regulation (PBR)-
dc.subjectpower systems-
dc.subjectProbabilistic methods-
dc.subjectRegulatory Authority (RA)-
dc.subjectReliability index (RI)-
dc.subjectsystem reliability-
dc.subjectUnified Modeling (UML)-
dc.subjectProbability distributions-
dc.titleChronological Monte Carlo-based assessment of distribution system reliabilityen
dc.typeoutro-
dc.contributor.institutionIEEE-
dc.contributor.institutionUniversidade Federal de Itajubá (UNIFEI)-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionCEMIG -Companhia Energética de Minas Gerais-
dc.description.affiliationIEEE-
dc.description.affiliationPower System Eng. Group Federal University, Itajubá UNIFEI, MG-
dc.description.affiliationSão Paulo State University UNESP, Guaratinguetá, SP-
dc.description.affiliationExpansion Planning Dept. CEMIG -Companhia Energética de Minas Gerais, Belo-Horizonte, MG-
dc.description.affiliationUnespSão Paulo State University UNESP, Guaratinguetá, SP-
dc.identifier.doi10.1109/PMAPS.2006.360423-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartof2006 9th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS-
dc.identifier.scopus2-s2.0-46149100501-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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