MPPT control technology based on the GWO-VINC algorithm - Yan, Chang; Lei, Guoping; Cai, Li; He, Chao; Dai, Nina; Jiang, Zhou; Wu, Jiacheng; Li, Shenghao (Frontiers in Energy Research, 2023)
It is a challenging task to accurately track the global maximum power point (GMPP) in a changing environment in widely used photovoltaic(PV) systems. So far, a variety of maximum power point (MPP) tracking algorithms have been used in solar PV power systems the classical algorithm is simple and fast to track the speed effectively in a constant environment, but it can get stuck at an extreme point in a variable environment, however, the bio-intelligence algorithm is helpful to find the global optimum, the disadvantage is that it takes more time to track the GMPP. In this paper, the variable step conductivities increment method (VINC) is combined with the Grey Wolf Optimization (GWO) algorithm. The global search is performed by GWO first, and then the precise search is performed by VINC when it is close to the global optimization. In this way, the GMPP can be tracked quickly and accurately under the condition of variable environment. In order to check the robustness of the proposed algorithm, the Grey Wolf optimization algorithm and VINC are compared and analyzed. The results show that the proposed technique is simple, efficient and has high power tracking efficiency. The tracking efficiency of static shading, dynamic shading under simulation and static shading and dynamic shading under experiment are 99.80%, 98.82%, 99.43% and 98.51%, respectively. The tracking time of simulation and experiment is 46.49% and 89.34% faster than that of GWO and VINC technology, respectively. The proposed method has improved the tracking time and tracking efficiency, less algorithm parameters, simple calculation process, low complexity, and low requirements on hardware.