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Advances in Mathematical Physics
Volume 2015, Article ID 827238, 6 pages
Research Article

Power Load Prediction Based on Fractal Theory

1College of Electronic & Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China
2Department of Mathematics (DIPMAT), University of Salerno, 84084 Fisciano, Italy

Received 1 August 2014; Accepted 7 September 2014

Academic Editor: Xiao-Jun Yang

Copyright © 2015 Liang Jian-Kai 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.

Supplementary Material

In this paper, we apply the fractal theory to predict the power load. According to the fractal interpolation method, we can calculate the affine coefficients of IFS, as shown in Table1.1.

According to load data July 8, 15, 21 in theTable1.2, fractal interpolation parameters of three similar days were calculated, we weight and average them to obtain IFS codes by the fractal interpolation. Then by benchmark interpolating points, we use the deterministic algorithm to get attractor, which can be considered as the prediction daily load curve fit by the historical data.

Using fractal interpolation function and improved deterministic iterative attractor algorithms, we can accurately predict the electric power load from the result.

  1. Supplementary Material