Affiliations: [a] Faculty of Electronic Engineering, Menofia University, Menouf, Egypt
| [b] School of Engineering and Applied Science, Nile University, Sheikh Zayed City, Giza, Egypt
| [c] Smart Engineering Systems Research Center (SESC), Nile University, Sheikh Zayed City, Giza, Egypt
| [d] Robotics and Internet-of-Things Lab (RIOTU), Prince Sultan University, Riyadh, Saudi Arabia
| [e] Faculty of Computers and Artificial Intelligence, Benha University, Benha, Egypt
Abstract: This paper seeks to improve the efficiency of photovoltaic (PV) water pumping system using Fractional-order Fuzzy Maximum Power Point Tracking (FoF-MPPT) control and Gray Wolf Optimization (GWO) technique. The fractional calculus has been used to provide an enhanced model of PV water pumping system to, accurately, describe its nonlinear characteristics. Moreover, three metaheuristic optimizers are applied to tune the parameters of the proposed FoF-MPPT, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and the GWO. The FoF-MPPT is intensively tested and compared to the Perturb and Observe (PO), the Incremental Conductance (INC) and the FL-MPPT controllers. A MATLAB-Simscape based physical model of the PV water pumping system has been developed and simulated for different control techniques with the proposed optimization algorithms. The response of the PV water pumping systems is evaluated under rapidly changing weather conditions to prove the effectiveness of the optimized FoF-MPPT compared to the conventional algorithms. The reliability of the comparative study has been emphasized in terms of several transient tracking and steady- state performance indices under different operating conditions. The simulation results show the effective performance of the proposed metaheuristic optimized FL-MPPT and FoF-MPPT control under different climatic conditions with disturbance rejection and robustness analysis.
Keywords: Optimal Fractional Order Control, Fractional Order Systems, optimal control, Maximum Power Point Tracking
