Conference Paper

Load forecasting in the user side using wavelet-ANFIS

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Abstract

At present, the intelligent energy management systems (IEMS) are used to maximiz the relation between productivity and cost using a variety of energy sources. In this work, we present a method of short-time load forecasting, using the ANFIS model and a component of preprocessing based in the discrete wavelet transform; the models was implemented in the user-side, analyzing real data of a factory in order to test the proposed algorithm.

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... The prediction based on the artificial neural networks, was widely accepted by the scientific and engineering spheres, becoming the most widespread technique for the load forecasting. There are several scientific publications that prove the quality and robustness of predictions based on neural networks (Chen et al., 1996;Giacometto et al., 2012;Hippert et al., 2001;Lino et al., 2016). ...
... The period under review belongs to winter of 2014 and was: One day (4 th of February), one week (3 rd to 9 th of February) and two weeks (3 rd to 16 th of February). The results are satisfactory considering that the maximum value of MAPE in the forecast studies of this type should not exceed 5% (Giacometto et al., 2012;Hippert et al., 2001).at this point was small: 0.70%. ...
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An expert system based algorithm
  • S Rahman
  • R Bhatnagar
S. Rahman, and R. Bhatnagar, "An expert system based algorithm