基于局部发电障碍检测下的光伏MPPT研究

冯鸥1; 2; 易灵芝2; 周东访3; 周喜明4

基于局部发电障碍检测下的光伏MPPT研究

引用本文：冯鸥1,2，易灵芝2，周东访3，周喜明4.基于局部发电障碍检测下的光伏MPPT研究[J].计算技术与自动化,2023,(2):50-56

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作者	单位
冯鸥1,2，易灵芝2，周东访3，周喜明4	（1.湖南理工职业技术学院，湖南湘潭 411105；2.湘潭大学自动化与电子信息学院，湖南湘潭 411105；3.湘潭大学基建处，湖南湘潭 411105；4.江西省九江市国家电网，江西九江 332000）

中文摘要:当外界环境变化或光伏电池内部局部发电障碍时，光伏阵列输出曲线呈现多峰。针对传统算法易陷入局部峰值，而智能优化算法易跟踪到全局最优，提出了一种基于迭代步长累积的粒子群算法。该算法结合扰动观察法检测思想，通过步长渐进变化靠近全局最大功率点。仿真结果验证该算法能够实时在单峰和多峰环境下变化下跟踪到全局最优，输出功率精度高且稳定，收敛速度快。

中文关键词:粒子群算法最大功率点局部发电障碍

Research on Photovoltaic MPPT Based on Local Generation Obstacle Detection

Abstract:When the external environment changes or local power generation obstacles inside the photovoltaic cell, the output curve of the photovoltaic array presents multi peaks. In view of the fact that the traditional algorithm is easy to fall into local peak and the intelligent optimization algorithm is easy to track the global optimization, a particle swarm optimization algorithm based on iterative step accumulation is proposed. Combined with the detection idea of disturbance observation method, the algorithm approaches the global maximum power point through the gradual change of step size. Simulation results show that the algorithm can track the global optimization in real time under the changes of single peak and multi peak environment, with high and stable output power accuracy and fast convergence speed.

keywords:particle swarm optimization maximum power point local power generation obstacle

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