Maximum Power Point Tracking of Photovoltaic Array Under Partial Shaded Conditions Based on Improved Grey Wolf Algorithm

The power and voltage curves of photovoltaic array in local shadow display a state with multiple peaks, the traditional maximum power point tracking control method is no longer suitable, so the improved grey wolf optimization algorithm is proposed. In this method, a nonlinear convergence factor equation is proposed, and dimension learning-based hunting strategy is adopted to improve the convergence speed and search diversity of the algorithm, which helps the algorithm to track the maximum power point faster and more accurately. Simulation results show that the improved algorithm has higher convergence speed, tracking efficiency and success rate.