基于改进LGWO-INC算法的MPPT控制研究
Research on MPPT Control Based on Improved LGWO-INC Algorithm
王金玉 1赵付佳 1王士勇2
作者信息
- 1. 东北石油大学 电气信息工程学院,大庆 163318
- 2. 中油电能电力技术服务公司脱硫分公司,大庆 163318
- 折叠
摘要
光伏发电阵列板在局部遮阴下会产生多个功率峰值,传统算法难以准确快速追踪光伏最大功率点(maximum power point,MPP),该文提出一种基于莱维飞行灰狼算法(Levy grey wolf optimization,LGWO)与电导增量法(incremental conductance,INC)结合的复合算法追寻MPP,莱维飞行帮助灰狼算法跳出局部最优,搜寻MPP附近时,切换电导增量算法减少系统振荡,在静态与动态局部遮阴下通过Simulink进行光伏并网仿真验证.研究结果显示,所提复合算法收敛效果快速精确,并且符合并网谐波(total harmonic distortion,THD)含量要求,可保证系统的稳定运行.
Abstract
Multiple power peaks can be generated by photovoltaic arrays under local shade,which makes it difficult for traditional algorithms to accurately and quickly track photovoltaic maximum power point(MPP).This paper pro-poses a composite algorithm based on Levy grey wolf optimization(LGWO)and incremental conductance(INC)meth-ods to track the MPP.The Levy flight assists the grey wolf algorithm in escaping local optima,and when searching near the MPP,switching to the incremental conductance algorithm reduces system oscillations.Through Simulink sim-ulations of photovoltaic grid-connected systems under static and dynamic partial shading conditions,the research re-sults demonstrate that the proposed composite algorithm achieves rapid and accurate convergence,meets the require-ments for total harmonic distortion(THD)content in grid connection,and ensures the stable operation of the system.
关键词
灰狼算法/电导增量/莱维飞行/局部遮阴/最大功率Key words
gray wolf algorithm/conductance increment/Levy flight/partial shading/maximum power引用本文复制引用
出版年
2024
NETL
NSTL
万方数据