A Method Based on Wavelet Neural Network for Power System Short Term Load Forecasting

Abstract:

The short-term load of Power System is uncertain and the daily-load signal spectrum is continuous. The approach of Wavelet Neural Network (WNN) is proposed by combing the wavelet transform (WT) and neural network. By the WT, the time-based short-term load sequence can be decomposed into different scales sequences, which is used to training the BP neural network. The short-term load is forecasted by the trained BP neural network. Select the load of a random day in Lianyungang to study, according to the numerical simulation results, the method proves to achieve good performances.

• Periodical: Applied Mechanics and Materials (Volume 521)
• Pages: 303-306
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.521.303
• Online since: February 2014
• Authors: Hong Mei Zhong, Jie Liu, Qi Fang Chen, Nian Liu
• Keywords: Neural Network (NN), Short-Term Load Forecasting, Wavelet Transformation

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