光伏系统
布谷鸟
布谷鸟搜索
最大功率点跟踪
计算机科学
算法
控制理论(社会学)
电气工程
工程类
人工智能
电压
生物
控制(管理)
逆变器
粒子群优化
动物
作者
Xiaodong Liu,Hairong Zou
标识
DOI:10.1088/1742-6596/2814/1/012001
摘要
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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