Design of Distributed Photovoltaic Control System Based on Radial Basis Function Neural Network
With the popularization of photovoltaic energy in the power system,the high proportion of photovoltaic integration has brought a series of challenges to the distribution network,such as voltage fluctuations and power flow reversal.In order to solve these problems,such as voltage fluctuations and power flow backflow caused by high proportion of photovoltaic access in the distribution network,a radial basis function neural network was studied to achieve global optimal approximation of the photovoltaic distribution network,and a series of improvements were made to design a new distributed photovoltaic control system.The experimental results show that experts have high evaluations of the system's performance indicators,with average scores of 88.1,85.3,and 84.4 for pre-diction accuracy,control speed,and stability.The proposed photovoltaic regulation system has the advantages of high regulation accu-racy and good stability,and has important theoretical significance and application value.