Analysis and Comparison of Adaptive P&O and Adaptive Gradient Ascent Based MPP Techniques for PV Integrated Systems under Dynamic Operating Conditions

Abstract

Photovoltaic (PV) power generation is fundamentally dependent on environmental conditions, which makes continuous operation at the maximum power point a challenging task. This paper compares two adaptive maximum power point tracking (MPPT) techniques applied to a PV system integrated with battery energy storage and a dynamic DC load. The system uses a DC-DC boost converter for PV interfacing and a bidirectional DC-DC converter which is connected to a battery and used to regulate a 220 V DC bus with the help of a PI control strategy. An adaptive perturb and observe technique with variable step size adjustment and an adaptive gradient ascent method based on power slope information are two MPPT algorithms that are analyzed. The comparison is done to analyze which method gives faster convergence to the maximum power point and which method has less steady-state oscillations. Based on this comparison, the adaptive Gradient Ascent method demonstrates superior performance. Simulation results show that the adaptive gradient ascent method is evaluated under varying irradiance levels and load conditions, including surplus generation, and battery assisted supply. The results show that the method is able to track the maximum power point effectively under all conditions. It provides faster convergence to the maximum power point with reduced steady-state oscillations, improving overall system performance. The study confirms that adaptive MPPT methods are effective for PV battery based DC systems under real-world conditions.