MODELING AND EVALUATION OF MPPT ALGORITHMS FOR PHOTOVOLTAIC WATER PUMPING SYSTEM USING BRUSHLESS DC MOTOR

MODELING AND EVALUATION OF MPPT ALGORITHMS FOR PHOTOVOLTAIC WATER PUMPING SYSTEM USING BRUSHLESS DC MOTOR

This paper presents a comprehensive modeling and evaluation study comparing two popular Maximum Power Point Tracking (MPPT) techniques, the Perturb and Observe (P&O) algorithm and the Cuckoo Search(C-S) algorithm, for a photovoltaic water pumping system (PV-WPS) that utilizes a brushless direct current (BLDC) motor. The efficient utilization of solar energy in photovoltaic water pumping systems is crucial for sustainable and cost-effective water supply in remote areas. The study begins by developing a mathematical model for (PV-WPS), taking into account the electrical characteristics of the PV array, the BLDC motor, and the water pump. The P&O is a conventional and extensively used MPPT technique, and the Cuckoo Search algorithm, a nature-inspired optimization algorithm, is implemented and integrated into the system model. Simulations are conducted using MATLAB/Simulink to assess and compare the execution of both MPPT algorithms under various environmental conditions. The evaluation criteria include tracking efficiency, steady-state oscillation, convergence time, and robustness to partial shading. The results demonstrate that both algorithms effectively track the MPP, thereby improving the overall system efficiency. However, the Cuckoo Search algorithm exhibits superior performance in faster convergence, reduced oscillations, and enhanced robustness against partial shading.