Application of Local Linear Wavelet Neural Network in Short Term Electric Load Forecasting

نویسندگان

  • Prasanta Kumar Pany
  • S. P. Ghoshal
  • T. W. S Chow
  • M Sforna
  • M. Caciotta
  • H. S. Hippert
  • C. E. Pedreira
  • H. Takara
  • K. Uezato
  • J. W. Taylor
  • L. M. Saini
چکیده

The electrical deregulated market increases the need for short-term load forecast algorithms in order to assists electrical utilities in activities such as planning , operating and controlling electric energy systems. Methodologies based on regression methods have been widely used with satisfactory results. However, this type of approach has some shortcomings. This paper proposes a shortterm load forecast methodology based on Artificial Intelligence techniques. The work presented in this paper makes use of local linear wavelet neural networks (LLWNN) to find the electric load for a given period, with a certain confidence level.

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تاریخ انتشار 2012