Maximum power point tracking control of photovoltaic systems using a hybrid improved whale particle swarm optimization algorithm

Maximum power point tracking (MPPT) control techniques are commonly employed to maximize the benefits and enhance the operational efficiency of photovoltaic systems in challenging outdoor environments. However, when the photovoltaic array is subjected to partial shading conditions, the conventional MPPT methods exhibit inadequate global maximum power point (GMPP) tracking performance. To this end, in this study, an effective MPPT control method for photovoltaic systems is proposed based on a hybrid improved whale particle swarm optimization algorithm (IWPOA). The control method integrates the advantages of the Improved Whale Optimization Algorithm (IWOA) and the Particle Swarm Algorithm (PSO) with additional control and stochastic elements. Validation analysis under a variety of conditions reveals that IWPOA significantly improves MPPT, achieving a tracking speed of approximately 0.13 s, which represents a 18.75-53.57% enhancement over other comparative algorithms. The mean tracking accuracy of IWPOA is 99.21%, and it offers superior tracking stability, making it suitable for diverse applications in MPPT.