Power Load Prediction Based on Fractal Theory

Liang Jian-Kai, Carlo Cattani and Song Wan-Qing

Advances in Mathematical Physics, 2015, vol. 2015, 1-6

Abstract:

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.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlamp:827238

DOI: 10.1155/2015/827238

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