Application of frequency optimization neural network method on power line communication

Abstract

The quality of broadband power line carrier communication mainly depends on the carrier communication frequency. However, there is a lack of fast and effective optimal carrier frequency selection method. One frequency selection method based on frequency point optimization neural network is proposed by this paper. This method combines transmission line theory and voltage partial reflection theory to build a power line carrier channel mathematical model of the distribution network. The input frequency point sample set is used as the training set of the frequency point optimization neural network to obtain a neural network model that can predict the local optimal frequency point set. Then the actual distribution network is taken as an example for simulation analysis. When inputting any frequency range, the model outputs the corresponding optimal frequency point set. Simulation results show that the algorithm saves a lot of input impedance or channel strength testing time, while the error rate is limited to about 3%.