Maximum Power Point Tracking Method of Photovoltaic Power Generation System Based on Convolutional Neural Network
The conventional maximum power point tracking method is mainly based on the analysis of photovoltaic power generation characteristics.Due to the influence of complex lighting conditions,the maximum power point tracking results have certain deviations.Therefore,this paper designs the maximum power point tracking method of photovoltaic power generation system based on convolutional neural network.By extracting the output characteristics of the maximum power point of photovoltaic power generation system,the power-voltage change of photovoltaic array is analyzed,and the voltage disturbance equation of the maximum power point is constructed to determine the position of the maximum power point of photovoltaic power generation system.The maximum power point tracking control circuit is constructed based on convolutional neural network,and the output voltage is changed by adjusting the duty cycle of the circuit to track the maximum power point in real time.The comparative experiments show that the tracking accuracy of this method is higher and it can be applied to real life.
convolutional neural networkphotovoltaic power generationmaximum power point trackingsunshine intensity
NETL
NSTL
万方数据
