Power Line Carrier Noise Immunity And Channel Estimation Method Under High Proportion Of New Energy Access

With the rapid development of new power systems,important changes have taken place in my country’s energy system structure.New energy equipment such as large-scale distributed photovoltaics,energy storage,and charging piles are connected to low-voltage distribution networks,which intensifies the distribution network in terms of voltage levels,network topology,equipment access type and other issues.Power line communication(PLC)is a power communication method widely used in low-voltage distribution networks.However,with the continuous access of large-scale new energy to low-voltage distribution networks,the environment of PLC channels is even worse,and the channel characteristics The time-varying nature is stronger,and the noise interference is complicated and serious,which brings severe challenges to the reliable transmission of the PLC network.Therefore,it is very important to study the PLC anti-noise and channel estimation methods under the high proportion of new energy access.This paper first analyzes the research status of power line noise reduction technology and channel estimation at home and abroad,and points out the shortcomings of the existing noise reduction technology and channel estimation methods in the scenario where a high proportion of new energy is connected to the low-voltage distribution network.Secondly,the PLC channel transmission characteristics and channel characteristics under the high proportion of new energy access are studied.Aiming at the ring network or grid network structure that may appear in the distribution network,a PLC channel modeling method based on information nodes is given to overcome the traditional channel modeling methods are only suitable for insufficient tree-like network structures.The typical noise of the power line channel under the operation of power electronics is analyzed again,the improved method of the Wegener distribution and the Wegener cross-interference term is introduced,and the time-frequency analysis of the power line noise is completed based on the Wegener distribution.Then based on the relevant theory of wavelet transform and artificial neural network,an adaptive filtering algorithm based on discrete wavelet transform and artificial neural network is proposed,and the individual model and combined model are respectively introduced to reduce the noise of the power line channel,and this method is compared with the traditional compared with the discrete wavelet transform method,the simulation results show that this method has a good noise reduction effect,and significantly improves the signal-to-noise ratio of the signal after noise reduction.Finally,the channel estimation criterion is introduced,and the traditional channel estimation method based on the pilot frequency is analyzed.On this basis,a linear minimum mean square error channel estimation method based on the improved particle swarm optimization algorithm is proposed,and the calculation of the method is complex.Degree analysis,the simulation results show that the proposed method solves the problems of particle stagnation and local optimum in the traditional particle swarm optimization algorithm,significantly improve the performance of the traditional linear minimum mean square error channel estimation method,and significantly reduce the mean square error value and computational complexity.In addition,the algorithm is compared with advanced channel estimation methods,and the simulation results show that the algorithm has great advantages.