摘要
基于神经网络的非线性映射特性,提出了一种适用于直接电流控制的静止无功发生器检测无功和谐波电流的方法。首先建立了神经网络预测模型,最后明确了该种方法的算法。该方法具有实时、准确、能自适应跟踪电力系统负荷的变化的特点。
Basing on the image character of nonlinearity of neural network, the article introduces a method of detecting reactive and harmonic current which is fit for SVG＇ s control by direct current. At first the prediction model of neural network is creating and finally the algorithm of this method was establishing. The method has the feature that real- time, accurate and self- adaptable follow the change of electric system＇s load.
出处
《煤矿机械》
北大核心
2006年第1期42-44,共3页
Coal Mine Machinery
关键词
无功补偿
静止无功发生器
神经网络
谐波检测
reactive compencation
static VAR generator
neural network
harmonic analying
