Research on Maximum Power Point Tracking Control Method for Ship Photovoltaic System

Traditional ships rely on diesel engines, consume a large amount of fossil fuels, and seriously pollute the marine environment. Therefore, in order to cope with energy crisis and environmental pollution, it is urgent to use new energy such as solar energy. Although solar power generation has broad application prospects in the shipbuilding industry, its power generation efficiency is relatively low. To address these issues, the PID control algorithm based on BP neural network will be applied to the maximum power tracking (MPPT) of solar photovoltaic arrays, and the BP neural network will be used to accurately adjust the three parameters of KP, KI, and KD. Through experimental verification, the algorithm can achieve a maximum power of 482.5W in approximately 1.3s of the system. The PID control algorithm based on BP neural network has an average maximum power increase of 97.4W compared to the other four classic algorithms, about 20%, indicating significant efficiency of the algorithm; After stabilization, the tracking speed and accuracy were significantly improved. The photovoltaic system using this algorithm can achieve large-scale access on ships and has good MPPT performance in navigation environments.