Hybrid Adaptive MPPT Algorithm with Intelligent Exploration and Dither-Based Tracking for PV Systems

This paper proposes an improved maximum power point tracking (MPPT) approach by developing a hybrid Perturb and Observe (P&O) and Incremental Conductance (INC) algorithm based on adaptive control, considering both existing influential perturbations, such as temperature and insolation changes, and integrating the kinks. The proposed method leverages P&O's fast decision-making capability for dynamic response and INC's slope estimation technique for higher precision around the maximum power point (MPP). Moreover, dither-gradient estimation and an adaptive exploration strategy are included to make the model more robust against noise and local maxima in partial shading. The controller works in two coordinated modes—Track and Explore—for achieving rapid convergence as well as steady-state stability. The oscillations are suppressed, and re-explorations can be made when the environment changes a lot, with a combination of dynamic reference power, exponential moving average (EMA) filtering, and irradiance-drop detection. The MATLAB/simulation results verified that the introduced hybrid P&O–Inc algorithm provides faster MPP tracking, better steady-state performance, and better tracking ability in PSC as well as under changing irradiances than other conventional detached MPPT methods.