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A Firework-Based GMPPT with Variable Sampling Time for PV Systems

机译:一种基于烟花的光伏系统可变采样时间GMPPT

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摘要

Photovoltaic systems have a nonlinear characteristic in which there is one optimum operating point called Maximum Power Point (MPP). However, when PV panels are partially shaded by surrounding objects, there are several MPPs, of which one of them is Global MPP (GMPP). Therefore, conventional Maximum Power Point Tracking (MPPT) algorithms get trapped into local MPPs. As a result, a multitude of Global MPPT (GMPPT) algorithms have been proposed. An outstanding GMPPT algorithm as well as the fast-tracking speed should find GMPP in complicated shading patterns where not only there are lots of MPPs, but also the peaks are close together. Therefore, in this paper, a novel GMPPT based on firework algorithm is proposed which is able to find GMPP in complicated shading patterns with fast tracking speed. Moreover, the firework is combined with Perturb-and-Observe (PO) algorithm to reduce the computational effort in a way that the firework is only used to recognize GMPP; afterwards, PO algorithm completes the tracking. Furthermore, the variable sampling time technique, based on the system settling time, speeds up the tracking process considerably. Finally, the proposed method is compared with previous works, simulated, and implemented on an experimental setup to prove its superiority.
机译:光伏系统具有非线性特性,其中有一个称为最大功率点 (MPP) 的最佳工作点。然而,当光伏板被周围物体部分遮挡时,有几个MPP,其中一个是Global MPP(GMPP)。因此,传统的最大功率点跟踪 (MPPT) 算法被困在本地 MPP 中。因此,提出了多种全局MPPT(GMPPT)算法。出色的GMPPT算法以及快速的跟踪速度应该在复杂的阴影模式中找到GMPP,其中不仅有很多MPP,而且峰很接近。因此,该文提出了一种基于烟花算法的GMPPT,该算法能够快速跟踪复杂阴影图案中的GMPP。此外,烟花与扰动和观察(P&O)算法相结合,以减少计算工作量,使烟花仅用于识别GMPP;之后,P&O算法完成跟踪。此外,基于系统建立时间的可变采样时间技术大大加快了跟踪过程。最后,将所提方法与前人进行了对比,在实验装置上进行了仿真和实施,证明了其优越性。

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