Power Load Prediction Based on Fractal Theory

• Main Authors: Liang Jian-Kai, Carlo Cattani, Song Wan-Qing
• Format: Article
• Language: English
• Published: Hindawi Limited 2015-01-01
• Series: Advances in Mathematical Physics
• Online Access: http://dx.doi.org/10.1155/2015/827238

The basic theories of load forecasting on the power system are summarized. Fractal theory, which is a new algorithm applied to load forecasting, is introduced. Based on the fractal dimension and fractal interpolation function theories, the correlation algorithms are applied to the model of short-term load forecasting. According to the process of load forecasting, the steps of every process are designed, including load data preprocessing, similar day selecting, short-term load forecasting, and load curve drawing. The attractor is obtained using an improved deterministic algorithm based on the fractal interpolation function, a day’s load is predicted by three days’ historical loads, the maximum relative error is within 3.7%, and the average relative error is within 1.6%. The experimental result shows the accuracy of this prediction method, which has a certain application reference value in the field of short-term load prediction.