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Journal of Engineering
Volume 2013, Article ID 760860, 7 pages
http://dx.doi.org/10.1155/2013/760860
Research Article

A Simple Hybrid Model for Short-Term Load Forecasting

1Mathematics Department, GVP College of Engineering for Women, Visakhapatnam 530048, India
2Engineering Mathematics Department, A.U College of Engineering, Visakhapatnam 530003, India

Received 28 October 2012; Revised 21 May 2013; Accepted 4 June 2013

Academic Editor: Haranath Kar

Copyright © 2013 Suseelatha Annamareddi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The paper proposes a simple hybrid model to forecast the electrical load data based on the wavelet transform technique and double exponential smoothing. The historical noisy load series data is decomposed into deterministic and fluctuation components using suitable wavelet coefficient thresholds and wavelet reconstruction method. The variation characteristics of the resulting series are analyzed to arrive at reasonable thresholds that yield good denoising results. The constitutive series are then forecasted using appropriate exponential adaptive smoothing models. A case study performed on California energy market data demonstrates that the proposed method can offer high forecasting precision for very short-term forecasts, considering a time horizon of two weeks.