Novo conjunto de indicadores de desempenho operacional para redes elétricas inteligentes por meio da Lógica fuzzy

Detalhes bibliográficos
Autor(a) principal: Rodrigues, Mauro Fonseca
Data de Publicação: 2020
Tipo de documento: Tese
Idioma: por
Título da fonte: Manancial - Repositório Digital da UFSM
Texto Completo: http://repositorio.ufsm.br/handle/1/22696
Resumo: Operational performance analysis is a multidisciplinary tool that allows the engineering systems manager to control the quality of services provided, as needed. For this operational tool to be effective, it is necessary to know the details of the processes involved and mathematically model metrics that bring representative responses from the goals established for the qualification of the system. In this work, the quality metrics established for the Telecommunications systems and the continuity of the Electricity Distribution services, inspected by Anatel and Aneel, respectively, were analyzed. The two methods have differences in schedules, evaluated periods and mathematical relationships. The two methods have differences in schedules, evaluated periods and mathematical relationships. In addition, they have few indexes listing their indicators. Thus, Fuzzy Logic was selected as a mathematical tool to relate the indicators currently practiced in order to create more comprehensive indices that can compose a new methodology for the analysis of operational performance for Smart Grids (REI). This methodology starts from the union of the current sets with their respective metrics, being organized in four main axes: specific indices, instant monitoring indices, new indicators and customer satisfaction. From these groups, indicators and indexes were developed to assess the quality of REI. Then, for the first grouping: indexes of establishment and continuity of data connection (REI01) and guarantee of the contracted transmission rate (REI02) and infrastructure quality indicator (REI07); for the second: indices of instantaneous capacity of individual interruptions (REI03), of instantaneous ability to calculate the frequency of individual interruptions (REI04), of instantaneous capacity of collective interruptions (REI05), of instantaneous ability to calculate the frequency of interruptions individual (REI06); for the third: indicators of the instantaneous data transfer rate (SMP10i / SCM4i) and the average monthly individual data transfer rate (SMP11i / SCM5i); and, for the fourth: the union of several current indicators and indices that make up customer satisfaction, such as drop rate (SMP7), maximum duration of continuous interruption (DMIC), user complaints rate (REL), number repair requests (RAI), consumer satisfaction Aneel (IASC), satisfaction survey and perceived quality Anatel (SCM and SMP). Equal data with different goals per company (DIC, for example) were normalized through the Indicator Unit Value (VUI) created. Through the Fuzzy Logic it was possible to implement the evaluation of the inputs from the goals stipulated by the current regulations, in levels established as stages or equivalent numerical quality levels, being: very bad (0 - 0.3), bad (0.2 - 0 , 6), good (0.5 - 0.9) and excellent (0.8 - 1). The fuzzifiers and defuzzifiers were tested with a REI, found in the bibliography, and with real data from a Brazilian region with an implanted REI, showing adherence in the evaluations and results obtained.
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spelling Novo conjunto de indicadores de desempenho operacional para redes elétricas inteligentes por meio da Lógica fuzzyNew group of operational performance indicators for smart grids through fuzzy LogicRede elétrica inteligenteIndicadores de continuidadeTelecomunicaçõesIndicadores operacionaisLógica fuzzyDistribuição de energia elétricaSmart gridsContinuity indicatorsTelecommunicationsOperational indicatorsFuzzy logicElectricity distributionCNPQ::ENGENHARIAS::ENGENHARIA ELETRICAOperational performance analysis is a multidisciplinary tool that allows the engineering systems manager to control the quality of services provided, as needed. For this operational tool to be effective, it is necessary to know the details of the processes involved and mathematically model metrics that bring representative responses from the goals established for the qualification of the system. In this work, the quality metrics established for the Telecommunications systems and the continuity of the Electricity Distribution services, inspected by Anatel and Aneel, respectively, were analyzed. The two methods have differences in schedules, evaluated periods and mathematical relationships. The two methods have differences in schedules, evaluated periods and mathematical relationships. In addition, they have few indexes listing their indicators. Thus, Fuzzy Logic was selected as a mathematical tool to relate the indicators currently practiced in order to create more comprehensive indices that can compose a new methodology for the analysis of operational performance for Smart Grids (REI). This methodology starts from the union of the current sets with their respective metrics, being organized in four main axes: specific indices, instant monitoring indices, new indicators and customer satisfaction. From these groups, indicators and indexes were developed to assess the quality of REI. Then, for the first grouping: indexes of establishment and continuity of data connection (REI01) and guarantee of the contracted transmission rate (REI02) and infrastructure quality indicator (REI07); for the second: indices of instantaneous capacity of individual interruptions (REI03), of instantaneous ability to calculate the frequency of individual interruptions (REI04), of instantaneous capacity of collective interruptions (REI05), of instantaneous ability to calculate the frequency of interruptions individual (REI06); for the third: indicators of the instantaneous data transfer rate (SMP10i / SCM4i) and the average monthly individual data transfer rate (SMP11i / SCM5i); and, for the fourth: the union of several current indicators and indices that make up customer satisfaction, such as drop rate (SMP7), maximum duration of continuous interruption (DMIC), user complaints rate (REL), number repair requests (RAI), consumer satisfaction Aneel (IASC), satisfaction survey and perceived quality Anatel (SCM and SMP). Equal data with different goals per company (DIC, for example) were normalized through the Indicator Unit Value (VUI) created. Through the Fuzzy Logic it was possible to implement the evaluation of the inputs from the goals stipulated by the current regulations, in levels established as stages or equivalent numerical quality levels, being: very bad (0 - 0.3), bad (0.2 - 0 , 6), good (0.5 - 0.9) and excellent (0.8 - 1). The fuzzifiers and defuzzifiers were tested with a REI, found in the bibliography, and with real data from a Brazilian region with an implanted REI, showing adherence in the evaluations and results obtained.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESA análise de desempenho operacional é uma ferramenta multidisciplinar que permite ao gestor de sistemas de Engenharia uma forma de controlar a qualidade dos serviços prestados ou fornecidos, conforme a necessidade. Para que essa ferramenta operacional tenha efetividade é necessário conhecer os detalhes dos processos envolvidos e modelar matematicamente métricas que tragam respostas representativas a partir de metas estabelecidas para qualificação do sistema. Neste trabalho, foram analisadas as métricas de qualidade estabelecidas para os sistemas de Telecomunicações e de continuidade dos serviços de Distribuição de Energia Elétrica, fiscalizados por Anatel e Aneel, respectivamente. Os dois métodos possuem divergências em horários, períodos avaliados e relações matemáticas. Além disso, possuem poucos índices relacionando seus indicadores. Assim, foi selecionada a Lógica Fuzzy, como ferramenta matemática, para relacionar os indicadores atualmente praticados de forma a criar índices mais abrangentes que possam compor uma nova metodologia de análise de desempenho operacional para as Redes Elétricas Inteligentes (REI). Esta metodologia parte da união dos conjuntos atuais com suas respectivas métricas, sendo organizada em quatro eixos principais: índices específicos, índices de monitoramento instantâneo, indicadores novos e satisfação do cliente. A partir desses grupos, foram desenvolvidos indicadores e índices para avaliar a qualidade da REI. Então, para o primeiro agrupamento: índices de estabelecimento e continuidade da conexão de dados (REI01) e de garantia da taxa de transmissão contratada (REI02) e indicador de qualidade da infraestrutura (REI07); para o segundo: índices de capacidade instantânea de interrupções individuais (REI03), de capacidade instantânea de apurar a frequência de interrupções individuais (REI04), de capacidade de apuração instantânea de interrupções coletivas (REI05), de capacidade instantânea de apurar a frequência de interrupções individuais (REI06); para o terceiro: indicadores da taxa instantânea de transferência de dados (SMP10i/SCM4i) e da taxa média mensal de transferência de dados individual (SMP11i/SCM5i); e, para o quarto: a união de vários indicadores e índices atuais que compõem a satisfação do cliente, como taxa de queda de ligações (SMP7), duração máxima de interrupção contínua (DMIC), taxa de reclamações dos usuários (REL), número de solicitações de reparo (RAI), satisfação do consumidor Aneel (IASC), pesquisa de satisfação e qualidade percebida Anatel (SCM e SMP). Dados iguais com metas distintas por empresa (DIC, por exemplo) foram normalizados através do Valor Unitário de Indicador (VUI) criado. Através da Lógica Fuzzy foi possível implementar a avaliação das entradas a partir das metas estipuladas pelos regulamentos atuais, em níveis estabelecidos como estágios ou níveis de qualidade numéricos equivalentes, sendo: péssimo (0 – 0,3), ruim (0,2 – 0,6), bom (0,5 – 0,9) e excelente (0,8 – 1). Os fuzzificadores e defuzzificadores foram testados com uma REI, encontrada na bibliografia, e com dados reais de uma região brasileira com REI implantada, mostrando aderência nas avaliações e resultados obtidos.Universidade Federal de Santa MariaBrasilEngenharia ElétricaUFSMPrograma de Pós-Graduação em Engenharia ElétricaCentro de TecnologiaAbaide, Alzenira da Rosahttp://lattes.cnpq.br/2427825596072142Canha, Luciane NevesBernardon, Daniel PinheiroKnak Neto, NelsonBinelo, Manuel OsorioRodrigues, Mauro Fonseca2021-11-03T19:51:56Z2021-11-03T19:51:56Z2020-08-14info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfhttp://repositorio.ufsm.br/handle/1/22696porAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessreponame:Manancial - Repositório Digital da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSM2022-08-09T12:20:48Zoai:repositorio.ufsm.br:1/22696Biblioteca Digital de Teses e Dissertaçõeshttps://repositorio.ufsm.br/ONGhttps://repositorio.ufsm.br/oai/requestatendimento.sib@ufsm.br||tedebc@gmail.comopendoar:2022-08-09T12:20:48Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM)false
dc.title.none.fl_str_mv Novo conjunto de indicadores de desempenho operacional para redes elétricas inteligentes por meio da Lógica fuzzy
New group of operational performance indicators for smart grids through fuzzy Logic
title Novo conjunto de indicadores de desempenho operacional para redes elétricas inteligentes por meio da Lógica fuzzy
spellingShingle Novo conjunto de indicadores de desempenho operacional para redes elétricas inteligentes por meio da Lógica fuzzy
Rodrigues, Mauro Fonseca
Rede elétrica inteligente
Indicadores de continuidade
Telecomunicações
Indicadores operacionais
Lógica fuzzy
Distribuição de energia elétrica
Smart grids
Continuity indicators
Telecommunications
Operational indicators
Fuzzy logic
Electricity distribution
CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
title_short Novo conjunto de indicadores de desempenho operacional para redes elétricas inteligentes por meio da Lógica fuzzy
title_full Novo conjunto de indicadores de desempenho operacional para redes elétricas inteligentes por meio da Lógica fuzzy
title_fullStr Novo conjunto de indicadores de desempenho operacional para redes elétricas inteligentes por meio da Lógica fuzzy
title_full_unstemmed Novo conjunto de indicadores de desempenho operacional para redes elétricas inteligentes por meio da Lógica fuzzy
title_sort Novo conjunto de indicadores de desempenho operacional para redes elétricas inteligentes por meio da Lógica fuzzy
author Rodrigues, Mauro Fonseca
author_facet Rodrigues, Mauro Fonseca
author_role author
dc.contributor.none.fl_str_mv Abaide, Alzenira da Rosa
http://lattes.cnpq.br/2427825596072142
Canha, Luciane Neves
Bernardon, Daniel Pinheiro
Knak Neto, Nelson
Binelo, Manuel Osorio
dc.contributor.author.fl_str_mv Rodrigues, Mauro Fonseca
dc.subject.por.fl_str_mv Rede elétrica inteligente
Indicadores de continuidade
Telecomunicações
Indicadores operacionais
Lógica fuzzy
Distribuição de energia elétrica
Smart grids
Continuity indicators
Telecommunications
Operational indicators
Fuzzy logic
Electricity distribution
CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
topic Rede elétrica inteligente
Indicadores de continuidade
Telecomunicações
Indicadores operacionais
Lógica fuzzy
Distribuição de energia elétrica
Smart grids
Continuity indicators
Telecommunications
Operational indicators
Fuzzy logic
Electricity distribution
CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
description Operational performance analysis is a multidisciplinary tool that allows the engineering systems manager to control the quality of services provided, as needed. For this operational tool to be effective, it is necessary to know the details of the processes involved and mathematically model metrics that bring representative responses from the goals established for the qualification of the system. In this work, the quality metrics established for the Telecommunications systems and the continuity of the Electricity Distribution services, inspected by Anatel and Aneel, respectively, were analyzed. The two methods have differences in schedules, evaluated periods and mathematical relationships. The two methods have differences in schedules, evaluated periods and mathematical relationships. In addition, they have few indexes listing their indicators. Thus, Fuzzy Logic was selected as a mathematical tool to relate the indicators currently practiced in order to create more comprehensive indices that can compose a new methodology for the analysis of operational performance for Smart Grids (REI). This methodology starts from the union of the current sets with their respective metrics, being organized in four main axes: specific indices, instant monitoring indices, new indicators and customer satisfaction. From these groups, indicators and indexes were developed to assess the quality of REI. Then, for the first grouping: indexes of establishment and continuity of data connection (REI01) and guarantee of the contracted transmission rate (REI02) and infrastructure quality indicator (REI07); for the second: indices of instantaneous capacity of individual interruptions (REI03), of instantaneous ability to calculate the frequency of individual interruptions (REI04), of instantaneous capacity of collective interruptions (REI05), of instantaneous ability to calculate the frequency of interruptions individual (REI06); for the third: indicators of the instantaneous data transfer rate (SMP10i / SCM4i) and the average monthly individual data transfer rate (SMP11i / SCM5i); and, for the fourth: the union of several current indicators and indices that make up customer satisfaction, such as drop rate (SMP7), maximum duration of continuous interruption (DMIC), user complaints rate (REL), number repair requests (RAI), consumer satisfaction Aneel (IASC), satisfaction survey and perceived quality Anatel (SCM and SMP). Equal data with different goals per company (DIC, for example) were normalized through the Indicator Unit Value (VUI) created. Through the Fuzzy Logic it was possible to implement the evaluation of the inputs from the goals stipulated by the current regulations, in levels established as stages or equivalent numerical quality levels, being: very bad (0 - 0.3), bad (0.2 - 0 , 6), good (0.5 - 0.9) and excellent (0.8 - 1). The fuzzifiers and defuzzifiers were tested with a REI, found in the bibliography, and with real data from a Brazilian region with an implanted REI, showing adherence in the evaluations and results obtained.
publishDate 2020
dc.date.none.fl_str_mv 2020-08-14
2021-11-03T19:51:56Z
2021-11-03T19:51:56Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://repositorio.ufsm.br/handle/1/22696
url http://repositorio.ufsm.br/handle/1/22696
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Santa Maria
Brasil
Engenharia Elétrica
UFSM
Programa de Pós-Graduação em Engenharia Elétrica
Centro de Tecnologia
publisher.none.fl_str_mv Universidade Federal de Santa Maria
Brasil
Engenharia Elétrica
UFSM
Programa de Pós-Graduação em Engenharia Elétrica
Centro de Tecnologia
dc.source.none.fl_str_mv reponame:Manancial - Repositório Digital da UFSM
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
reponame_str Manancial - Repositório Digital da UFSM
collection Manancial - Repositório Digital da UFSM
repository.name.fl_str_mv Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM)
repository.mail.fl_str_mv atendimento.sib@ufsm.br||tedebc@gmail.com
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