Power Load Prediction Based on Fractal Theory. (19th March 2015)

• Record Type: Journal Article
• Authors: Jian-Kai, Liang; Cattani, Carlo; Wan-Qing, Song
• Other Names: Yang Xiao-Jun Academic Editor.
• Is Part Of: Advances in mathematical physics. Volume 2015(2015)
• Publication Date: 2015-03-19
• Subjects: Mathematical physics -- Periodicals; Mathematical physics; Periodicals; 530.15
• DOI: 10.1155/2015/827238
• Languages: English
• ISSNs: 1687-9120

Abstract

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.