Performance enhancement of solar PV systems applying P&O assisted Flower Pollination Algorithm (FPA)

In recent years, designing reliable and practically feasible Maximum Power Point Tracking (MPPT) techniques to maximize the power output of PV power plants has become a crucial research objective. Further, to counteract the inimitable PV operating conditions, numerous bio-inspired metaheuristic algorithms have been proposed in literature; that are predominantly complex and difficult to implement. On the other hand, the age old Perturb and Observe (P&O) technique is way superior owing to its simplicity, robustness and reduced switching stress. In this context, bio inspired methods assisted by P&O can be a viable solution to enhance the efficiency and reliability of MPPT algorithms. Unfortunately, the potential of hybrid techniques is less explored in literature and moreover, the strategy utilized to switch between bio-inspired and P&O method is rather superficial; that has not been proven judicially. Therefore, in this article, a new FPA method assisted by P&O is proposed. A new switching strategy is incorporated and validated in this work to achieve effective utilization of both FPA and P&O algorithms. More importantly, the transition is only initiated when global power regions are initially explored with FPA. Further, for truthful comparison, the results of FPA-P&O are compared with recently proven Enhanced Leader Particle Swarm Optimization (ELPSO) and conventional PSO methods.