小波神经网络及其在电力负荷预测中应用概述

小波神经网络是建立在小波理论基础上的一种新型前馈神经网络，具有许多优良特性。本文介绍小波神经网络的构成原理、设计方法和优点，分析小波神经网络在电力负荷预测领域的研究和应用现状。文中所指小波神经网络的优点，例如所需网络节点少和预测精度高，已经在电力负荷预测研究中得到验证。将小波神经网络应用于电力负荷预测的成果是令人鼓舞的。但是小波神经网络也存在收敛性差等缺点，还需要进一步研究适合小波神经网络的算法，以提高其性能。

Overview of Wavelet Neural Network and Its Application in Power Load Forecasting

Wavelet neural network (WNN) is a novel feed-forward neural network based on wavelet theory,and it possesses several excellent features.This paper introduces the basic theory,designing methods and virtues of WNN.The current research and application of WNN in power load forecasting is discussed in detail.The paper points out that the advantages of WNN,such as requiring less network nodes and achieving accurate forecasting,are validated in power load forecasting research,and it is proved that the application of WNN in power load forecasting is encouraging.But WNN also has some shortcomings,such as poor convergence performance,and further investigations should be conducted on the algorithm of WNN to improve its performance.