Artificial Hornet Colony Algorithm Design for MPPT of Partial Shading Photovoltaic Power Conversion Systems

This paper proposes a novel artificial hornet colony (AHC) algorithm for solving the maximum power point tracking (MPPT) control problem to address the challenges posed by the multi‐peak characteristics of the power‐voltage curve in a photovoltaic (PV) power conversion system under partial shading conditions. This AHC algorithm mimics the behavior of hornet colonies to defend their nest by searching the location with the highest concentration of intruders to sting out. In detail, through the patrolling, alerting, and attacking behavior, the location with the highest threat level from intruders is efficiently and quickly found to chase away the intruders. Due to efficient global searching capability and avoiding local optima, the AHC algorithm is able to be applied on the MPPT control of the PV power conversion system in a fast and accurate manner. In comparison with traditional heuristic algorithm‐based methods, the proposed method is validated with superior performance in convergence speed and environmental adaptability. The results demonstrate that the AHC algorithm provides an effective solution for improving energy conversion efficiency of PV power systems under partial shading conditions. The benefits related to traditional methods are also shown in the simulation results.