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Comparação entre regressão linear, redes neurais artificiais e árvores de regressão para quantificação do impacto harmônico de múltiplas cargas em redes elétricas de distribuição. ; Comparison between linear regression, artificial neural networks and regression trees to quantify the harmonic impact of multiple loads on distribution networks.

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  • معلومة اضافية
    • Contributors:
      TOSTES, Maria Emília de Lima; http://lattes.cnpq.br/4197618044519148
    • بيانات النشر:
      Universidade Federal do Pará
      Brasil
      Instituto de Tecnologia
      UFPA
      Programa de Pós-Graduação em Engenharia Elétrica
    • الموضوع:
      2018
    • Collection:
      Universidade Federal do Pará: Repositório Institucional da UFPA
    • نبذة مختصرة :
      In recent years, the socio-economic development of the population, the growth of commercial and industrial sectors, as well as the ever-increasing installation of new electrical loads, have generated great evolution in demand of electricity consumption. In turn, to obtain more efficient systems, the manufacturers have produced equipment more energy efficient for residential, commercial and industrial use. However, these loads due their non-linearities, have contributed significantly to the increase in harmonic distortion levels of voltage and current, raising the concern of the power sector managers with respect to the power quality, mainly, due to the difficulty in the identification of the origin of the harmonic distortion. Therefore, to anticipate the harmonic effects and meet the current legislation, through computational techniques, this work emphasis is placed on the common coupling point (CCP) of consumers and utility, regardless of consumption characteristics and loads, to assess the harmonic impacts in his grid, besides comparing the reliability level of the techniques through the mean absolute error (MAE). The proposed methodology uses the Electrical Power Quality System (SISQEE) software that allows the use of three different computational techniques, such as Linear Regression, Artificial Neural Networks and Regression Trees, to evaluate the harmonic contribution of each feeder at the point of interest of the chosen electric grid. To prove the validity of the methodology, two case studies, based on real measurements at a university and at an industrial district, was carried out with a minimum sampling period of seven days using power quality analyzers, according to the distribution procedures by ANEEL (PRODIST). As a result of the power quality, it was verified how much each feeder impacts the voltage and current distortion at the CCP, besides classifying the feeders in relation to their respective impacts in the studied electrical grid. Also, as a result, the studies allowed the evaluation of ...
    • File Description:
      application/pdf
    • Relation:
      PAIXÃO JÚNIOR, Ulisses Caravalho. Comparação entre regressão linear, redes neurais artificiais e árvores de regressão para quantificação do impacto harmônico de múltiplas cargas em redes elétricas de distribuição. 2018. 131 f. Dissertação (Mestrado) - Universidade Federal do Pará, Instituto de Tecnologia, Belém, 2018. Programa de Pós-Graduação em Engenharia Elétrica. Disponível em: . Acesso em:.; http://repositorio.ufpa.br/jspui/handle/2011/10457
    • Rights:
      Acesso Aberto
    • الرقم المعرف:
      edsbas.A61571A9