基于ICOA-P&O算法的MPPT控制研究  

Research on MPPT Control Based on ICOA-P&O Algorithm

作　　者：王金玉[1] 李新宇 董秀波 WANG Jinyu;LI Xinyu;DONG Xiubo(School of Electrical and Information Engineering,Northeast Petroleum University,Daqing 163318,China;Daqing Kunlun Investment and Operation Co.,Ltd.,Daqing 163318,China)

机构地区：[1]东北石油大学电气信息工程学院,大庆163318 [2]大庆昆仑投资运营有限公司,大庆163318

出　　处：《自动化与仪表》2025年第4期6-10,28,共6页Automation & Instrumentation

基　　金：国家自然科学基金项目(62203106)。

摘　　要：在光伏阵列发生局部遮荫时会出现多个功率极值点,传统的MPPT控制算法以及一般的优化算法不能够准确地跟踪光伏最大功率点(MPP),进而导致整个光伏系统的效率降低。小龙虾优化算法(COA)是2023年提出的一种优化算法,该文针对光伏阵列功率多峰值的问题,选取对应的多峰值函数对小龙虾算法与其他优化算法进行测试,验证了小龙虾算法的优异性能。为了应对光伏MPP跟踪的实际问题,提出了一种改进小龙虾算法(ICOA)与二分步长的扰动观察法(P&O)相结合的复合算法跟踪MPP,通过在Simulink中模拟静态遮荫与动态遮荫,验证了所提算法可以快速准确地跟踪到MPP。There are multiple power extreme points when the PV array is partially shading,and the traditional MPPT control algorithm and the general optimization algorithm cannot accurately track the maximum power point(MPP)of the PV,which leads to the reduction of the efficiency of the entire PV system.Crayfish optimization algorithm(COA)is an optimization algorithm proposed in 2023,this paper selects the corresponding multi-peak function to test the crayfish algorithm and other optimization algorithms for the problem of multiple peaks of photovoltaic array power,and verifies the excellent performance of the crayfish algorithm.In order to deal with the practical problems of photovoltaic MPP tracking,a composite algorithm combining the improved crayfish optimization algorithm(ICOA)with the two-step disturbance observation method(P&O)is proposed to track MPP.By simulating static shading and dynamic shading in Simulink,it is verified that the proposed algorithm can track MPP quickly and accurately.

关 键 词：小龙虾算法 扰动观察 局部遮荫 最大功率点跟踪 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TM615[自动化与计算机技术—控制科学与工程]