REAL TIME HARMONIC ESTIMATION BASED ON ARTIFICIAL NEURAL NETWORK, ETHERNET AND GPS TECHNOLOGY

摘要

A new real time harmonic estimation approach based on adaptive neural network, GPS technology and distributed Ethernet is proposed in this paper. The method uses adaptive neural network to estimate the amplitudes and angles of the distorted current in power system. Only half-cycle harmonic current signal is used as the input of the neural network. In order to improve the accuracy of harmonic source identification, GPS (Global Positioning System) is used as the synchronization signal for the embedded measurement system based on digital signal processor (DSP). The sample selection and training methods of artificial neural network are explained and the hardware structure of the embedded harmonic identification system is given. RTDS (Real-Time Digital Simulator) simulation results illustrate the effectiveness of the proposed approach.