节点文献
基于松鼠算法的光伏最大功率点追踪研究
Research on Photovoltaic Maximum Power Point Tracking Based on Squirrel Algorithm
【摘要】 面对因遮光而处在部分阴影状态下的太阳能光伏阵列,其输出功率特征曲线从单峰变成多峰,传统的最大功率点追踪技术在这种情形下显现出收敛速度慢、震荡幅度范围大和收敛精度低等问题。针对这些问题,将松鼠觅食算法运用到太阳能光伏阵列多峰值MPPT控制系统中。首先构建处于局部遮阴情况下的太阳能光伏阵列模型,连接到Boost电路,将算法中松鼠的位置对应为开关管的占空比,通过算法的迭代更新调整占空比来实现MPPT控制。通过建立仿真验证,相比于传统启发式粒子群算法,松鼠觅食算法在应对局部阴影情况下的收敛速度提高3.5倍,追踪效率提升0.1%,且震荡期间产出能量更高。
【Abstract】 To the problems such as slow convergence speed, large oscillation amplitude range and low convergence accuracy that the traditional maximum power point tracking technology shows when the output power characteristic curve changes from single-peak to multi-peak for the solar photovoltaic arrays partially shaded, the research applied the squirrel search algorithm(SSA) to the multi-peak MPPT control system of solar photovoltaic arrays. Firstly, the solar photovoltaic array model under local shading was constructed and connected to the Boost circuit. With the position of the squirrel in the algorithm corresponding to the duty cycle of the switch tube, the MPPT control was realized by adjusting the duty cycle through the iterative update of the algorithm. Compared with the traditional PSO algorithm, the convergence speed of the SSA algorithm and the tracking efficiency were increased by 3.5 times and 0.1% respectively and the energy output during oscillation was higher than that of the traditional PSO algorithm.
- 【文献出处】 安徽理工大学学报(自然科学版) ,Journal of Anhui University of Science and Technology(Natural Science) , 编辑部邮箱 ,2022年04期
- 【分类号】TM615
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