An improved maximum power point tracking (MPPT) algorithm based on the fusion firefly algorithm (FFA) with a novel simplified propagation process (SPP) for photovoltaic (PV) systems under partial shading conditions (PSCs) is proposed in this study. By integrating the neighborhood attraction firefly algorithm (NaFA) and simplified firefly algorithm (SFA), the proposed FFA is capable of tracking the global maximum power points (GMPPs) with high accuracy. In addition, the proposed SPP process reduces the sampling events by omitting redundant propagations, thereby accelerating the tracking speed and reducing the energy loss and oscillations during the sampling process. The performance of the proposed FFA and the speed improvement using the SPP process were simulated using MATLAB software and verified with a hardware evaluation system. Experimental results confirmed that the proposed FFA algorithm offers high accuracy and efficiency with rapid tracking speed. In addition, the proposed SPP process is capable of significantly reducing the sampling events not only when integrating it with the FFA, but also with other conventional FA algorithms.

中文翻译：

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部分遮蔽条件下光伏MPPT的简化传播融合萤火虫算法

提出了一种基于融合萤火虫算法（FFA）的改进的最大功率点跟踪（MPPT）算法，该算法在部分阴影条件（PSC）下为光伏（PV）系统提供了新颖的简化传播过程（SPP）。通过集成邻域吸引力萤火虫算法（NaFA）和简化萤火虫算法（SFA），提出的FFA能够高精度地跟踪全局最大功率点（GMPP）。此外，建议的SPP过程通过省略冗余传播来减少采样事件，从而加快跟踪速度并减少采样过程中的能量损失和振荡。使用MATLAB软件对建议的FFA的性能和SPP流程的速度提高进行了仿真，并通过硬件评估系统进行了验证。实验结果证明，本文提出的FFA算法具有较高的精度和效率，跟踪速度也很快。另外，所提出的SPP过程不仅在与FFA集成时，而且与其他常规FA算法集成时，都能够显着减少采样事件。