A Combined Adaptive Coefficient Particle Swarm Optimization MPPT approach and TT configured PV Array to Enhance Maximum Power under PSC

The primary challenge to building integrated PV system is partial shadowing since it severely impairs the output power, efficiency and mismatch power loss. To mitigate the effect of PSC, a robust MPPT controller is desirable to identify the maximum power point (MPPT) during partial shading. Various conventional (P&O, InC etc.) and optimization algorithms are described in literature, but they are unsuccessful to identify GMP among multiple peaks. This paper proposes an adaptive coefficients Particle Swarm Optimization (ACPSO) MPPT technique for the new triple-tied (TT) configured PV system to improve the maximum power under PSCs. Unlike a conventional PSO, the coefficients are made adaptive in the proposed technique for fast convergence and better identification of local and global peaks. The proposed work is carried out in MATLAB/Simulink platform. Also, the performance of proposed work is compared with P&O, Grey-Wolf Optimization (GWO), Cuckoo Search (CS), and Particle Swarm Optimization (PSO) techniques in terms of tracked GMP, convergence time or tracking speed and efficiency. The results also demonstrate the superiority of proposed MPPT technique when compared to other MPPT techniques.