Artificial neural networks for electricity consumption forecasting considering climatic factors

  • Authors:

  • Francisco David Moya Chaves

  • Affiliations:

  • Electrical Engineering Program, Faculty of Engineering, La Salle University, Bogotá, Colombia

  • Venue:
  • NN'10/EC'10/FS'10 Proceedings of the 11th WSEAS international conference on nural networks and 11th WSEAS international conference on evolutionary computing and 11th WSEAS international conference on Fuzzy systems
  • Year:
  • 2010

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Abstract

This work develops Artificial Neural Networks (ANN) models applied to predict the consumption forecasting considering climatic factors. It is intended to verify the influence of climatic factors on the electricity consumption forecasting through the ANN. The case study is applied in the Campinas city, Brazil. This work used Perceptron and Backpropagation ANN models. The specific goal is comparisons the performance of neural networks as an alternative to traditional forecasting methods. In this work were observed that despite direct or indirect influence of climatic factors on electricity consumption, a good prediction can be obtained using ANN without climatic factors.