Photovoltaic MPPT based on improved Cuckoo algorithm

Xiaodong Liu and Hairong Zou
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Abstract

Photovoltaic power generation is susceptible to external factors such as light, resulting in a reduction in the actual efficiency of photovoltaic power generation. However, the traditional maximum power point tracking technology has the characteristics of slow convergence speed and poor accuracy. In order to improve the above problems, a new photovoltaic maximum power control algorithm with an improved cuckoo algorithm is proposed. By adjusting the iterative step size in the cuckoo algorithm and changing the probability of finding the bird nest, the iterative convergence speed is accelerated, and the global optimization ability is increased. Finally, the algorithm is applied to the maximum power tracking, and the simulation model is built on the Matlab/Simulink platform. After comparing the standard Cuckoo algorithm with the improved Cuckoo algorithm under static and dynamic conditions, the simulation results show that the improved Cuckoo algorithm has more advantages in maximum power tracking speed and accuracy.
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基于改进型 Cuckoo 算法的光伏 MPPT
光伏发电容易受到光照等外部因素的影响,导致光伏发电的实际效率降低。然而,传统的最大功率点跟踪技术具有收敛速度慢、精度差等特点。为了改善上述问题,本文提出了一种采用改进型杜鹃算法的新型光伏最大功率控制算法。通过调整布谷鸟算法的迭代步长和改变寻找鸟巢的概率,加快了迭代收敛速度,提高了全局优化能力。最后,将该算法应用于最大功率跟踪,并在 Matlab/Simulink 平台上建立了仿真模型。在静态和动态条件下比较了标准布谷鸟算法和改进布谷鸟算法后,仿真结果表明改进布谷鸟算法在最大功率跟踪速度和精度方面更具优势。
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