Research on MPPT Based on Gray Wolf Algorithm improved by Levy Flight

Abstract

In the late iteration of the gray wolf algorithm, the convergence results will have low accuracy becased of the elite retention.When implementing MPPT control, the maximum power point of the photovoltaic array cannot be accurately tracked, and it is easy to fall into the local optimum. Therefore, this paper proposes gray wolf algorithm improved with Levy flight applied to MPPT control. The algorithm introduces the Levy flight to search the head wolf position globally, then uses the group optimization of the gray wolf algorithm and the random walk of Levy flight to improve the tracking speed and accuracy of the MPPT controller. In the simulation experiment, the algorithm is modeled and verified by setting different lighting conditions. Finally, it is compared with the conductance increment method, modified hybrid method of grey wolf optimization and golden-section optimization, the original gray wolf algorithm. The results show that the algorithm meets the requirements of fast tracking speed, high accuracy and stability in MPPT control.