一种基于改进羊群算法的光伏系统最大功率跟踪策略

A Maximum Power Point Tracking Strategy for Photovoltaic System Based on Improved Sheep Behaviors Optimization

针对传统控制算法在局部遮蔽条件下无法持续准确地跟踪最大输出功率点,提出一种基于改进羊群算法的光伏系统最大功率跟踪策略.在羊群算法中引入扰动算子、反向种群和自适应放牧概率,以增强算法的局部开发能力,提高算法的寻优精度.均匀光照、局部遮蔽和变照度3种条件下的实验结果表明,改进羊群算法在不同环境条件下均能持续稳定地跟踪最大功率点,在收敛时间和收敛精度上均有较大优势,验证了该算法在最大功率点跟踪控制中的可行性.

Aiming at the fact that traditional control algorithm cannot continuously and accurately track the maximum power point under the condition of partial shading,a strategy for photovoltaic systems based on improved sheep behaviors optimization was proposed.Disturbance operator,reverse position and adaptive factor were introduced in sheep behaviors optimization to enhance the local development ability,and improve the optimization accuracy of the algorithm.The experimental results under the conditions of uniform illumination,partial shading and variable irradiation show that the improved sheep behaviors optimization can steadily track the maximum power point under different environmental conditions,and the algorithm has greater advantages in convergence time and convergence accuracy,verifying the feasibility of this algorithm in the maximum power point tracking control.