Long term electricity consumption forecast in Brazil: A fuzzy logic approach |
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| Institution: | 1. Electrical Engineering Department, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), 22451-900 Rio de Janeiro, Rio de Janeiro, Brazil;2. Industrial Engineering Department, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), 22451-900 Rio de Janeiro, Rio de Janeiro, Brazil;3. State University of Rio de Janeiro (UERJ), 20550-900 Rio de Janeiro, Rio de Janeiro, Brazil;1. Dep. de Ing. Electrónica, de Sistemas Electrónicos y Automática, Universidad de Huelva.;2. Groupo de Control Inteligente, Universidad Politécnica de Madrid, Centro de Automatización y Robótica UPM - CSIC;1. Electrical Engineering Department, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro, RJ 22453-900, Brazil;2. Mathematics Department, Federal Rural University of Rio de Janeiro, BR 465, KM 7, Seropédica, RJ 23897-000, Brazil;3. Industrial Engineering Department, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro, RJ 22453-900, Brazil;4. Institute of Energy, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro, RJ 22453-900, Brazil;5. Posgraduate Programme in Metrology, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro, RJ 22453-900, Brazil;1. Electrical Engineering Department, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rua Marquês de São Vicente 255, Gávea, 22453-900, Rio de Janeiro, RJ, Brazil;2. Mathematics Department, Federal Rural University of Rio de Janeiro (UFRRJ), BR-465, Km 7, 23890-000, Seropédica, RJ, Brazil;3. Industrial Engineering Department, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rua Marquês de São Vicente 255, Gávea, 22453-900, Rio de Janeiro, RJ, Brazil;4. Institute of Energy, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rua Marquês de São Vicente 255, Gávea, 22453-900, Rio de Janeiro, RJ, Brazil;1. Electrical Engineering Department, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rua Marquês de São Vicente 255, Gávea, 22453-900, Rio de Janeiro, RJ, Brazil;2. Industrial Engineering Department, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rua Marquês de São Vicente 255, Gávea, 22453-900, Rio de Janeiro, RJ, Brazil |
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| Abstract: | The energy companies are always facing the challenge of producing more accurate load forecasts. A fuzzy logic methodology is proposed in order to extract rules from the input variables and provide Brazil's long-term annual electricity demand forecasts. In recent literature, the formulation of these types of models has been limited to treating the explanatory variables in the univariate form, or involving only the GDP. This study proposes an extension of this model, starting with population and the GDP additional value. The proposed model is compared with the official projections. The obtained results are quite promising. |
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| Keywords: | Forecasting Energy Fuzzy sets Wang–Mendel |
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