An improved photovoltaic maximum power point tracking technique-based model predictive control for fast atmospheric conditions

In this article, an enhanced maximum power point tracking (MPPT) technique for photovoltaic (PV) systems is presented. The proposed MPPT is designed for fast-changing operating conditions, where the conventional methods suffer from divergence (drift) under such conditions. Mainly, the reason for divergence in the traditional methods is the confusion between power change due to the perturbation of the control parameter and power variation because of the atmospheric conditions. Therefore, and to differentiate between these cases, additional control loops are added to the conventional perturb and observe (P&O) method to enhance its behavior. Furthermore, in our suggested scheme, the finite-set model predictive control (FS-MPC) principle is integrated with the proposed algorithm to enhance its transient performance. However, and to decrease the computational effort, the prediction stage (including cost function calculation) is eliminated. The suggested methodology is compared with the conventional FS-MPC for evaluation using experimental results at different atmospheric conditions (static and dynamic radiation).