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 systemto, 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.

中文翻译：

---

太阳能抽水系统的最佳FoF-MPPT

本文力求通过分数阶模糊最大功率点跟踪（FoF-MPPT）控制和灰狼优化（GWO）技术来提高光伏（PV）水泵系统的效率。分数演算已用于提供PV水泵系统的增强模型，以准确地描述其非线性特征。此外，应用了三个元启发式优化器来调整拟议的FoF-MPPT，粒子群优化（PSO），蚁群优化（ACO）和GWO的参数。FoF-MPPT经过了严格的测试，并与“扰动和观察”（PO），增量电导（INC）和FL-MPPT控制器进行了比较。利用提出的优化算法，针对不同的控制技术，开发并仿真了基于MATLAB-Simscape的光伏水泵系统的物理模型。在快速变化的天气条件下评估了光伏水泵系统的响应，以证明与传统算法相比，优化的FoF-MPPT的有效性。比较研究的可靠性已经在不同工作条件下的几个瞬态跟踪和稳态性能指标中得到了强调。仿真结果通过干扰抑制和鲁棒性分析，证明了所提出的基于启发式优化的FL-MPPT和FoF-MPPT控制在不同气候条件下的有效性能。比较研究的可靠性已经在不同工作条件下的几个瞬态跟踪和稳态性能指标中得到了强调。仿真结果通过干扰抑制和鲁棒性分析，证明了所提出的基于启发式优化的FL-MPPT和FoF-MPPT控制在不同气候条件下的有效性能。比较研究的可靠性已经在不同工作条件下的几个瞬态跟踪和稳态性能指标中得到了强调。仿真结果通过干扰抑制和鲁棒性分析，证明了所提出的基于启发式优化的FL-MPPT和FoF-MPPT控制在不同气候条件下的有效性能。