Recent technologies associated with solar photovoltaic (PV) systems tend to depend mostly on irradiance. In a PV array, the distribution of irradiance is unequal varying from module to module under partial shading (PS) conditions. Because of the PS of the PV array; the number of peaks in power–voltage ( $P$ – $V$ ) characteristics increases. In such cases, it would be difficult to track the highest peak or global peak (GP) point of $P$ – $V$ curve using traditional maximum power point tracking (MPPT) algorithms, such as perturb and observe (P&O), hill climbing (HC), and incremental conductance (INC). However, these work effectively only under constant irradiance conditions, i.e., to track single peak $P$ – $V$ curves. However, in order to track the GP point of $P$ – $V$ curves, the conventional JAYA algorithm is used, but it takes more tracking oscillations and convergence time due to fewer control parameters. To overcome the drawbacks of the JAYA algorithm, this article proposes a JAYA algorithm based on the Lévy flight (JAYA-LF) under static and dynamic conditions of PV array. The performance of the proposed algorithm is examined through MATLAB/SIMULINK and from experiments with the designed prototype. The results observed by the proposed algorithm are then compared with conventional JAYA and particle swarm optimization (PSO) algorithm to show the superiority and better performance of the algorithm that combines JAYA with Levy flight.

中文翻译：

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基于Lévy Flight的光伏系统局部遮光下全局MPPT的JAYA算法

与太阳能光伏 (PV) 系统相关的最新技术往往主要依赖于辐照度。在光伏阵列中，在部分遮蔽 (PS) 条件下，不同模块的辐照度分布是不均等的。因为光伏阵列的PS；功率电压峰值的数量（ $P$ —— $V$ ) 特性增加。在这种情况下，很难跟踪最高峰或全局峰值 (GP) 点。 $P$ —— $V$ 曲线使用传统的最大功率点跟踪 (MPPT) 算法，例如扰动观察 (P&O)、爬山 (HC) 和增量电导 (INC)。然而，这些仅在恒定辐照度条件下有效工作，即跟踪单峰 $P$ —— $V$ 曲线。但是，为了跟踪 GP 点 $P$ —— $V$ 曲线，使用传统的 JAYA 算法，但由于控制参数较少，需要更多的跟踪振荡和收敛时间。为了克服JAYA算法的不足，本文提出了一种基于Lévy飞行的JAYA算法（JAYA-LF）在光伏阵列静态和动态条件下。所提出算法的性能通过 MATLAB/SIMULINK 和设计原型的实验进行了检查。然后将所提出的算法观察到的结果与传统的 JAYA 和粒子群优化 (PSO) 算法进行比较，以显示 JAYA 与 Levy 飞行相结合的算法的优越性和更好的性能。