中文摘要：

电力系统短期负荷具有非常大的不确定性,而其日负荷信号的频谱具有连续变化的特性.从信号频谱分析角度,对日负荷信息进行建模分析,并通过小波变换,将日负荷数据分解为不同尺度上的投影子序列,用子序列作为小波神经网络的训练样本,然后用训练好的神经网络模型对电力系统的短期负荷进行预测.在Matlab仿真软件中,采用某市某线路的某日负荷数据对算法进行仿真验证,取得了较好的预测结果.

英文摘要：

The short-term load of power system has uncertainty,and the daily load signal spectrum varies continuously.The paper proposes s method of wavelet neural network （WNN） which combines wavelet transform （WT） and neural network,gives the modeling and analysis on the daily load through the spectrum of loads,and decomposes the short-term load time-based sequence into different scales sequence by WT,which is used to train WNN.Based on which the short-term load forecasting is carried out by using the trained WNN.At the end,the numerical simulation results of the daily load data from a transmission line in Lianyungang verify the effectiveness of the method proposed in this paper.