Research on Photovoltaic Maximum Power Point Tracking Based on Neural Network Algorithm
In view of the situation that the light intensity decreases rapidly with the external environment,due to the fixed step size of the conductance increment method,it is impossible to respond quickly and track the maximum power point of photovoltaic cells,so the algorithm of tracking the maximum power of neural network is proposed.The algorithm improves the traditional conductance increment method,optimizes the maximum power point tracking(MPPT),takes the light intensity and temperature as the input variables,and sets two hidden layers for the neural network training,and outputs the reference voltage under the maximum photovoltaic power.The simulation results show that the tracking accuracy of the algorithm is more than 98.5%,which can significantly improve the energy conversion efficiency of the photovoltaic system under the changing light intensity.
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