Abstract

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 short- term 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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