摘要
利用小波变换对功角数据进行处理，并用人工神经网络来识别系统中的相关发电机组，能取得较传统的相关识别方法更高的等值精度．以东北电网作算例，证明利用该方法进行电力系统动态等值有很好的效果．利用小波变换和人工神经网络进行发电机相关识别，为电力系统动态等值提供了一种新的方法，也为动态等值实时化提供了一条新思路．
This paper uses wavelet transform to process the data of power angle,and identifies the coherent generators by using artificial neural network which is more accurate than that of traditional coherency identification.Taking the northeast China power system as an example to prove that the reduction effect is very good by using this method.This paper presents a new method for dynamic reduction by using wavelet transformation and artificial neural network to identify the coherent generators.lt also presents a new idea of on line dynamic reduction.
出处
《武汉水利电力大学学报》
CSCD
1998年第5期47-50,71,共5页
Engineering Journal of Wuhan University
关键词
小波变换
动态等值
人工神经网络
电力系统
coherency
wavelet transform
Kohonen neural network
power angle
dynamic reduction
