Metodologia para identificação de perdas não técnicas em unidades consumidoras localizadas em áreas rurais com cultivo de arroz irrigado
Ano de defesa: | 2021 |
---|---|
Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | , |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal de Santa Maria
Centro de Tecnologia |
Programa de Pós-Graduação: |
Programa de Pós-Graduação em Engenharia Elétrica
|
Departamento: |
Engenharia Elétrica
|
País: |
Brasil
|
Palavras-chave em Português: | |
Palavras-chave em Inglês: | |
Área do conhecimento CNPq: | |
Link de acesso: | http://repositorio.ufsm.br/handle/1/23725 |
Resumo: | Non-technical losses are one of the biggest problems faced by companies in the energy sector, since they directly affect the financial revenues of concessionaires, the security of electrical systems and the quality of electricity supply to consumers. They are associated with errors in readings and measurements, clandestine connections to the secondary distribution network and fraud in meters. In rural feeders, the problem of non-technical losses becomes more complex, as the large extensions of the distribution networks and the presence of consumers located in remote or difficult-to-access regions make it difficult for inspection teams to investigation. Furthermore, rural consumers are extremely relevant for concessionaires, as they represent a significant portion of electricity consumption, due to irrigation systems installed with pumps and motors with high active power and used practically continuously during the crop period. This work presents a proposal for the identification of non-technical losses in consumers located in rural areas with irrigated rice cultivation. The methodology developed in this study based on the correlation of electricity consumption patterns and the characteristics of planting areas and irrigation systems. The methodology employs in the structure of its algorithm, the k-Means and Random Forest methods, for the development of the data clustering and classification stages, respectively, being used as inputs, monthly records of billed energy from a set of rural consumers areas. Furthermore, the algorithm has the capacity to estimate the consumption of electricity, based on referential information of some variables that make up the irrigation systems and the cultivated planted areas for a certain crop. The validation of the proposed methodology was accomplished in a group of seven rural consumers located in the West Frontier Region of the state of Rio Grande do Sul. In order to verify for possible irregularities, indicators referring to the class and the comparison between actual and estimated consumptions for each consumer were evaluated. The results demonstrated the proper operation of the model, indicating five suspected cases of occurrences of non-technical losses. |
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2022-02-23T18:15:31Z2022-02-23T18:15:31Z2021-12-10http://repositorio.ufsm.br/handle/1/23725Non-technical losses are one of the biggest problems faced by companies in the energy sector, since they directly affect the financial revenues of concessionaires, the security of electrical systems and the quality of electricity supply to consumers. They are associated with errors in readings and measurements, clandestine connections to the secondary distribution network and fraud in meters. In rural feeders, the problem of non-technical losses becomes more complex, as the large extensions of the distribution networks and the presence of consumers located in remote or difficult-to-access regions make it difficult for inspection teams to investigation. Furthermore, rural consumers are extremely relevant for concessionaires, as they represent a significant portion of electricity consumption, due to irrigation systems installed with pumps and motors with high active power and used practically continuously during the crop period. This work presents a proposal for the identification of non-technical losses in consumers located in rural areas with irrigated rice cultivation. The methodology developed in this study based on the correlation of electricity consumption patterns and the characteristics of planting areas and irrigation systems. The methodology employs in the structure of its algorithm, the k-Means and Random Forest methods, for the development of the data clustering and classification stages, respectively, being used as inputs, monthly records of billed energy from a set of rural consumers areas. Furthermore, the algorithm has the capacity to estimate the consumption of electricity, based on referential information of some variables that make up the irrigation systems and the cultivated planted areas for a certain crop. The validation of the proposed methodology was accomplished in a group of seven rural consumers located in the West Frontier Region of the state of Rio Grande do Sul. In order to verify for possible irregularities, indicators referring to the class and the comparison between actual and estimated consumptions for each consumer were evaluated. The results demonstrated the proper operation of the model, indicating five suspected cases of occurrences of non-technical losses.As perdas não técnicas são um dos maiores problemas enfrentados pelas empresas do setor energético, uma vez que, afetam diretamente as receitas financeiras das concessionárias, a segurança nos sistemas elétricos e a qualidade no fornecimento de energia elétrica para os consumidores. As mesmas, estão associadas a erros de leituras e medições, ligações clandestinas a rede secundária de distribuição e fraudes em medidores. Em alimentadores rurais, o problema das perdas não técnicas torna-se mais complexo, pois as grandes extensões das redes de distribuição e a presença de unidades consumidores alocadas em regiões remotas ou de difícil acesso, dificultam a fiscalização pelas equipes de inspeções. Além disso, os consumidores rurais são extremamente relevantes para as distribuidoras, pois representam uma parcela significativa do consumo de energia elétrica, devido aos sistemas de irrigação instalados com bombas e motores de elevada potência ativa e utilizados de maneira praticamente contínua durante o período da safra. Este trabalho apresenta uma proposta para a identificação de perdas não técnicas em unidades consumidoras localizadas em áreas rurais com cultivo de arroz irrigado. A metodologia desenvolvida nesse estudo, é baseada na correlação dos padrões de consumos de energia elétrica e das características das áreas de plantio e dos sistemas de irrigação. A metodologia emprega na estrutura de seu algoritmo, os métodos de k-Means e Random Forest, para o desenvolvimento das etapas de agrupamento e classificação de dados, respectivamente, sendo utilizados como entradas, registros mensais de energia faturada de um conjunto de consumidores rurais. Além disso, o algoritmo tem a capacidade de estimar o consumo de energia elétrica, a partir de informações referenciais de algumas variáveis que compõem os sistemas de irrigação e das áreas de plantio cultivadas para uma determinada safra. A validação da metodologia proposta foi realizada em um conjunto de sete unidades consumidoras rurais localizadas na Região da Fronteira Oeste do estado do Rio Grande do Sul. Para verificar possíveis irregularidades, foram avaliados indicadores referentes a classe e a comparação entre consumos reais e estimados para cada consumidor. Os resultados demonstraram a operação adequada do modelo, indicando cinco casos suspeitos de ocorrências de perdas não técnicas.porUniversidade Federal de Santa MariaCentro de TecnologiaPrograma de Pós-Graduação em Engenharia ElétricaUFSMBrasilEngenharia ElétricaAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAgrupamentoClassificaçãoEstimativa de consumoPerdas não técnicasSistemas de irrigaçãoUnidades consumidoras ruraisk-MeansRandom forestClassificationClusteringConsumption estimateIrrigation systemsNon-technical lossesRandom forestRural consumersCNPQ::ENGENHARIAS::ENGENHARIA ELETRICAMetodologia para identificação de perdas não técnicas em unidades consumidoras localizadas em áreas rurais com cultivo de arroz irrigadoMethodology for identifying non-technical losses in consumers located in rural areas with irrigated rice cultivationinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisBernardon, Daniel Pinheirohttp://lattes.cnpq.br/6004612278397270Gastaldini, Cristiane CauduroPrade, Lúcio Renêhttp://lattes.cnpq.br/9628766057181569Eichkoff, Henrique Silveira300400000007600600600425ebf67-3fcd-4c31-8378-e6edab478375c7d18991-f684-4e97-b0aa-c771f7a2f70e4e112eab-d54b-4b2e-924c-f01de5731f449e128670-2d9a-484a-a622-4c1e6e7c9855reponame:Manancial - Repositório Digital da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805http://repositorio.ufsm.br/bitstream/1/23725/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81956http://repositorio.ufsm.br/bitstream/1/23725/3/license.txt2f0571ecee68693bd5cd3f17c1e075dfMD53ORIGINALDIS_PPGEE_2021_EICHKOFF_HENRIQUE.pdfDIS_PPGEE_2021_EICHKOFF_HENRIQUE.pdfDissertação de mestradoapplication/pdf4988806http://repositorio.ufsm.br/bitstream/1/23725/1/DIS_PPGEE_2021_EICHKOFF_HENRIQUE.pdf01ef93c7fe0b2c64b34bcdf03a240829MD511/237252022-02-23 15:17:07.245oai:repositorio.ufsm.br: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ório Institucionalhttp://repositorio.ufsm.br/PUBhttp://repositorio.ufsm.br/oai/requestopendoar:39132022-02-23T18:17:07Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.por.fl_str_mv |
Metodologia para identificação de perdas não técnicas em unidades consumidoras localizadas em áreas rurais com cultivo de arroz irrigado |
dc.title.alternative.eng.fl_str_mv |
Methodology for identifying non-technical losses in consumers located in rural areas with irrigated rice cultivation |
title |
Metodologia para identificação de perdas não técnicas em unidades consumidoras localizadas em áreas rurais com cultivo de arroz irrigado |
spellingShingle |
Metodologia para identificação de perdas não técnicas em unidades consumidoras localizadas em áreas rurais com cultivo de arroz irrigado Eichkoff, Henrique Silveira Agrupamento Classificação Estimativa de consumo Perdas não técnicas Sistemas de irrigação Unidades consumidoras rurais k-Means Random forest Classification Clustering Consumption estimate Irrigation systems Non-technical losses Random forest Rural consumers CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA |
title_short |
Metodologia para identificação de perdas não técnicas em unidades consumidoras localizadas em áreas rurais com cultivo de arroz irrigado |
title_full |
Metodologia para identificação de perdas não técnicas em unidades consumidoras localizadas em áreas rurais com cultivo de arroz irrigado |
title_fullStr |
Metodologia para identificação de perdas não técnicas em unidades consumidoras localizadas em áreas rurais com cultivo de arroz irrigado |
title_full_unstemmed |
Metodologia para identificação de perdas não técnicas em unidades consumidoras localizadas em áreas rurais com cultivo de arroz irrigado |
title_sort |
Metodologia para identificação de perdas não técnicas em unidades consumidoras localizadas em áreas rurais com cultivo de arroz irrigado |
author |
Eichkoff, Henrique Silveira |
author_facet |
Eichkoff, Henrique Silveira |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Bernardon, Daniel Pinheiro |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/6004612278397270 |
dc.contributor.referee1.fl_str_mv |
Gastaldini, Cristiane Cauduro |
dc.contributor.referee2.fl_str_mv |
Prade, Lúcio Renê |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/9628766057181569 |
dc.contributor.author.fl_str_mv |
Eichkoff, Henrique Silveira |
contributor_str_mv |
Bernardon, Daniel Pinheiro Gastaldini, Cristiane Cauduro Prade, Lúcio Renê |
dc.subject.por.fl_str_mv |
Agrupamento Classificação Estimativa de consumo Perdas não técnicas Sistemas de irrigação Unidades consumidoras rurais |
topic |
Agrupamento Classificação Estimativa de consumo Perdas não técnicas Sistemas de irrigação Unidades consumidoras rurais k-Means Random forest Classification Clustering Consumption estimate Irrigation systems Non-technical losses Random forest Rural consumers CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA |
dc.subject.eng.fl_str_mv |
k-Means Random forest Classification Clustering Consumption estimate Irrigation systems Non-technical losses Random forest Rural consumers |
dc.subject.cnpq.fl_str_mv |
CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA |
description |
Non-technical losses are one of the biggest problems faced by companies in the energy sector, since they directly affect the financial revenues of concessionaires, the security of electrical systems and the quality of electricity supply to consumers. They are associated with errors in readings and measurements, clandestine connections to the secondary distribution network and fraud in meters. In rural feeders, the problem of non-technical losses becomes more complex, as the large extensions of the distribution networks and the presence of consumers located in remote or difficult-to-access regions make it difficult for inspection teams to investigation. Furthermore, rural consumers are extremely relevant for concessionaires, as they represent a significant portion of electricity consumption, due to irrigation systems installed with pumps and motors with high active power and used practically continuously during the crop period. This work presents a proposal for the identification of non-technical losses in consumers located in rural areas with irrigated rice cultivation. The methodology developed in this study based on the correlation of electricity consumption patterns and the characteristics of planting areas and irrigation systems. The methodology employs in the structure of its algorithm, the k-Means and Random Forest methods, for the development of the data clustering and classification stages, respectively, being used as inputs, monthly records of billed energy from a set of rural consumers areas. Furthermore, the algorithm has the capacity to estimate the consumption of electricity, based on referential information of some variables that make up the irrigation systems and the cultivated planted areas for a certain crop. The validation of the proposed methodology was accomplished in a group of seven rural consumers located in the West Frontier Region of the state of Rio Grande do Sul. In order to verify for possible irregularities, indicators referring to the class and the comparison between actual and estimated consumptions for each consumer were evaluated. The results demonstrated the proper operation of the model, indicating five suspected cases of occurrences of non-technical losses. |
publishDate |
2021 |
dc.date.issued.fl_str_mv |
2021-12-10 |
dc.date.accessioned.fl_str_mv |
2022-02-23T18:15:31Z |
dc.date.available.fl_str_mv |
2022-02-23T18:15:31Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/masterThesis |
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masterThesis |
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http://repositorio.ufsm.br/handle/1/23725 |
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http://repositorio.ufsm.br/handle/1/23725 |
dc.language.iso.fl_str_mv |
por |
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por |
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300400000007 |
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600 600 600 |
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Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
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Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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openAccess |
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Universidade Federal de Santa Maria Centro de Tecnologia |
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Programa de Pós-Graduação em Engenharia Elétrica |
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UFSM |
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Brasil |
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Engenharia Elétrica |
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Universidade Federal de Santa Maria Centro de Tecnologia |
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