Comparative Study of MPPT Optimization in Dual‐Stage PV Systems: PSO‐Integrated P&O and IC Techniques

The maximum power point tracking (MPPT) is one of the most vital equipment of photovoltaic (PV) systems for maximum power extraction from PV systems under dynamic conditions. In this paper, we present a comparative study of hybrid MPPT algorithm that combines particle swarm optimization (PSO) along with classical perturb and observe (P&O) and incremental conductance (IC) techniques. The hybrid methods change the step size based on solar irradiance and temperature variations to improve the dynamic performance of the DC–DC boost converter. A dual‐stage PV system is constructed and tested under various environmental conditions to evaluate the effectiveness of both methods. The simulation results show that normal P&O and IC algorithms were able to track 95% efficiently. On the contrary, the P&O + PSO approach tracks 98% efficiently. The hybrid IC + PSO algorithm shows the best tracking efficiency of 99.9%, thereby proving its performance on environmental changes. According to the results, PSO‐based hybrid MPPT methods are effective to enhance energy yield. Among these, IC + PSO is the most robust and accurate for real‐time PV power optimization.