摘要
根据电力系统中非正弦周期电流的分解形式 ,提出了一种基于正交三角级数神经网络的谐波检测方法。方法能同时检测出非正弦周期电流中的基波分量与各次谐波分量的幅值和相位以及有功电流和无功电流。通过仿真实例验证 ,该方法能够把整数次谐波进行有效分离 。
Based on the neural network of orthogonal trigonometric series,an approach for h armonics measurement in power systems is presented in this paper.Using this meth od, the fundamental component and harmonics can be detected simultaneously with less data quantity. The simulation results validate that harmonics can be separa ted from a signal with high accuracy by the method developed in the paper.
出处
《电力系统及其自动化学报》
CSCD
2004年第6期44-47,共4页
Proceedings of the CSU-EPSA
基金
海军工程大学科学研究基金项目 (HGDJJ0 3 0 0 1)
关键词
三角级数
正交性
神经网络
谐波检测
trigonometric series
orthogonality
neural netwo rk
harmonics measurement
