MPPT Photovoltaic Power Optimization Method and System Based on Photovoltaic Modules

Abstract

This application discloses an MPPT photovoltaic power optimization method and system based on photovoltaic modules.The method comprises: collecting photovoltaic signals and analyzing the collected signals;predicting future trends in illumination and temperature changes based on deep learning algorithms by learning from historical data and real-time environmental data,and generating a corresponding power point prediction model; utilizing edge computing devices to process the data locally and implement control,and real-time adjusting the output power of the photovoltaic modules according to the generated MPPT control strategy; optimizing the installation layout of the photovoltaic modules through reinforcement learning algorithms.By introducing a deep learning model combined with dynamic step size adjustment and perturbation and observation strategies,this method achieves precise and efficient tracking of the maximum power point for photovoltaic systems in complex environments, effectively improving the stability and response speed of power output.

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