An Improved Maximum Power Point Tracking of PV Source Using Parametric Estimation

Traditional MPPT methods often rely perturbations based on fixed algorithms to track varying characteristics of Photovoltaic (PV) modules due to climatic conditions, which generate significant ripple in PV voltage and current. Proposed parametric esstimation allows for real time adjustment of control parameters based on the actual operating conditions of the PV Module. The work presents on the extraction and formulation of unknown parameters of PV Module with help of known parameters (irradiance, temperature, open circuit voltage, short circuit current) to create a Single diode PV Model. The identified unknown parameters are then utilized within an MPPT control algorithm to dynamically adjust the operating point of the PV module. The unknown parameters are solved using iterative method and Voltage reference for PI controller to operate at maximum power point at different irradiance, temperature computed, which is given as the reference to a PI controller. Proposed methodology contributes better results, which was tested in simulation environment. Further, a data driven model is also developed for PV Module using regression-based AI technique and compared with proposed method.