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  • 标题:Power Load Prediction Based on Fractal Theory
  • 本地全文:下载
  • 作者:Liang Jian-Kai ; Carlo Cattani ; Song Wan-Qing
  • 期刊名称:Advances in Mathematical Physics
  • 印刷版ISSN:1687-9120
  • 电子版ISSN:1687-9139
  • 出版年度:2015
  • 卷号:2015
  • DOI:10.1155/2015/827238
  • 出版社:Hindawi Publishing Corporation
  • 摘要: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.
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