Power Load Prediction Based on Fractal Theory

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Liang Jian-Kai ; Carlo Cattani ; Song Wan-Qing (2015)
  • Publisher: Hindawi Limited
  • Journal: Advances in Mathematical Physics (issn: 1687-9120, eissn: 1687-9139)
  • Related identifiers: doi: 10.1155/2015/827238
  • Subject: Physics | QC1-999 | Article Subject

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.
  • References (14)
    14 references, page 1 of 2

    Hippert, H. S., Pedreira, E. C., Souza, C. R.. Neural networks for short-term load forecasting: a review and evaluation. IEEE Transactions on Power Systems. 2001; 16 (1): 44-55

    Hong, W.-C.. Chaotic particle swarm optimization algorithm in a support vector regression electric load forecasting model. Energy Conversion and Management. 2009; 50 (1): 105-117

    Zhang, Q., Lai, K., Niu, D.. Optimization combination forecast method of SVM and WNN for power load forecasting. : 249-253

    Duan, Q. C., Zeng, Y., Huang, D. W., Duan, P., Liu, D.. Short-term power load forecast based on particle swarm optimization with extended memory and support vector regression. Power System Protection and Control. 2012; 40 (2): 40-44

    Shen, H., Ma, B., Liu, F.. Study on power system load characteristics based on fractal theory. Zhejiang Electric Power. 2007; 2 (2): 15-17

    Yamahara, M., Noguchi, T., Okawa, M., Yamada, N.. The relationship between subjective sleep disturbance and complexity of 24-hour activity utilizing fractal theory in psychiatric inpatients. Sleep and Biological Rhythms. 2009; 7 (1): 11-16

    Prieto, M. D., Espinosa, A. G., Riba Ruiz, J.-R., Urresty, J. C., Ortega, J. A.. Feature Extraction of demagnetization faults in permanent-magnet synchronous motors based on box-counting fractal dimension. IEEE Transactions on Industrial Electronics. 2011; 58 (5): 1594-1605

    Navascués, M. A., Sebastián, M. V.. Generalization of Hermite functions by fractal interpolation. Journal of Approximation Theory. 2004; 131 (1): 19-29

    Xue-Yang, S., Yu-Cheng, X.. Research on development character of middle and small size fault structure in DongPang mine field on fractal theory. : 170-174

    Darmanto, T., Suwardi, I. S., Munir, R.. Cyclical metamorphic animation of fractal images based on a family of multi-transitional IFS code approach. : 231-234

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