杨家梁, 魏霞, 程志江, 朱菊萍. 改进差分进化的光伏最大功率点跟踪[J]. 现代电力. DOI: 10.19725/j.cnki.1007-2322.2022.0391
引用本文: 杨家梁, 魏霞, 程志江, 朱菊萍. 改进差分进化的光伏最大功率点跟踪[J]. 现代电力. DOI: 10.19725/j.cnki.1007-2322.2022.0391
YANG Jialiang, WEI Xia, CHENG Zhijiang, ZHU Juping. Photovoltaic Maximum Power Point Tracking with Improved Differential Evolution[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2022.0391
Citation: YANG Jialiang, WEI Xia, CHENG Zhijiang, ZHU Juping. Photovoltaic Maximum Power Point Tracking with Improved Differential Evolution[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2022.0391

改进差分进化的光伏最大功率点跟踪

Photovoltaic Maximum Power Point Tracking with Improved Differential Evolution

  • 摘要: 针对现有差分进化算法在局部遮阴情况下跟踪速度慢的问题,提出一种新的改进差分进化算法的光伏发电系统最大功率点跟踪控制策略。首先,引入三角突变策略,并将其嵌入传统差分进化算法的交叉公式当中,避免因迭代前后输出相同的占空比造成重复采样功率的情况。其次,引入自适应比例因子策略,以加强个体的收敛性。最后,通过奖励惩罚机制平衡所提算法的全局开发和局部探索能力。仿真结果表明,与对比文献的差分进化算法相比,改进算法在跟踪速度、稳定性方面具有显著的优势。

     

    Abstract: To address the problem of slow tracking speed of existing differential evolutionary algorithm in the case of local shading, a new maximum power point tracking(abbr.MPPT) control strategy for photovoltaic(abbr.PV) power generation system with improved differential evolutionary algorithm was proposed. Firstly, the triangular mutation strategy was introduced and embedded in the crossover formula of the traditional differential evolutionary algorithm to avoid duplicate sampled power due to the same duty cycle of the output before and after the iteration. Secondly, an adaptive scaling factor strategy was introduced to enhance individual convergence. Finally, the global exploitation and local exploration capabilities of the proposed algorithm were balanced by a reward-penalty mechanism. The simulation results show that the improved algorithm has significant advantages in tracking speed and stability compared with the differential evolution algorithm of the comparative literature.

     

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