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光伏发电系统的改进型快速GMPPT算法

周国华 薛宁 毕强

周国华, 薛宁, 毕强. 光伏发电系统的改进型快速GMPPT算法[J]. 西南交通大学学报. doi: 10.3969/j.issn.0258-2724.20220863
引用本文: 周国华, 薛宁, 毕强. 光伏发电系统的改进型快速GMPPT算法[J]. 西南交通大学学报. doi: 10.3969/j.issn.0258-2724.20220863
ZHOU Guohua, XUE Ning, BI Qiang. Improved and Fast Global Maximum Power Point Tracking Algorithm of Photovoltaic Power Generation System[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20220863
Citation: ZHOU Guohua, XUE Ning, BI Qiang. Improved and Fast Global Maximum Power Point Tracking Algorithm of Photovoltaic Power Generation System[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20220863

光伏发电系统的改进型快速GMPPT算法

doi: 10.3969/j.issn.0258-2724.20220863
基金项目: 国家自然科学基金项目(62271417,61771405)
详细信息
    作者简介:

    周国华(1983—),男,教授,博士生导师,研究方向为电力电子技术及其在新能源领域中的应用,E-mail:ghzhou-swjtu@163.com

  • 中图分类号: TM615

Improved and Fast Global Maximum Power Point Tracking Algorithm of Photovoltaic Power Generation System

  • 摘要:

    为提高局部阴影条件下光伏发电的能量利用率,提出一种改进型快速全局最大功率点跟踪(global maximum power point tracking, GMPPT)算法. 首先,研究局部阴影条件下光伏阵列的输出特性,并根据光伏阵列输出曲线中膝点与开路电压的关系,将其划分为恒流区和恒压区;其次,分析传统的最大功率梯形(maximum power trapezium,MPT)算法和以MPT算法为基础的改进型快速GMPPT算法的工作原理,改进型快速GMPPT算法利用电压的动态上、下限来限定搜索区间,并跳过调整时间较长的恒流区,以提高跟踪速度;最后,通过仿真与实验验证算法的有效性. 实验结果表明:改进型快速GMPPT算法的最短跟踪时间为4.0 s,扫描电压与能量损失分别为17.34 V和98.19 J;与传统全局扫描算法相比,跟踪时间缩短68.25%,扫描电压降低74.86%,能量损失减少58.19%;与MPT算法相比,跟踪时间缩短68.00%,扫描电压降低75.63%,能量损失减少62.31%.

     

  • 图 1  光伏组串的电路结构

    Figure 1.  Circuit structure of PV string

    图 2  光伏组件的输出特性

    Figure 2.  Output characteristics of PV module

    图 3  局部阴影条件下光伏组串的输出特性

    Figure 3.  Output characteristics of PV string under PSC

    图 4  MPT算法的跟踪示例

    Figure 4.  Tracking example of the MPT algorithm

    图 5  改进型快速GMPPT算法的流程

    Figure 5.  Flowcharts of the improved and fast GMPPT algorithm

    图 6  改进型快速GMPPT算法的跟踪示例

    Figure 6.  Tracking example of the improved and fast GMPPT algorithm

    图 7  光伏MPPT系统原理

    Figure 7.  Schematic of the PV system with MPPT

    图 8  不同局部阴影条件下光伏阵列的输出特性

    Figure 8.  Output characteristics of PV array under different PSCs

    图 9  阴影改变时采用不同算法的光伏阵列仿真波形

    Figure 9.  Simulation waveforms of the PV array with various algorithms when the shadow changes

    图 10  光伏GMPPT系统的实验平台

    Figure 10.  Experimental platform of PV system with GMPPT

    图 11  阴影改变时采用不同算法的光伏阵列实验波形

    Figure 11.  Experiment waveforms of the PV array with various algorithms when the shadow changes

    表  1  光伏阵列的输出参数

    Table  1.   Output parameters of the PV array

    条件 光照强度/(W·m−2 全局最大功率点
    PV1 PV2 PV3 功率/W 电压/V 电流/A
    PSC1 120 210 400 90.13 54.60 1.65
    PSC2 200 300 560 134.60 84.80 1.59
    PSC3 150 270 750 143.60 25.20 5.70
    下载: 导出CSV

    表  2  阴影条件变化下3种算法的仿真跟踪性能比较

    Table  2.   Simulation tracking performance comparison of the three algorithms under shading variation

    光照条件 扫描时间/s 总路径的扫描电压/V 能量损失/J
    算法 1 算法 2 算法 3 算法 1 算法 2 算法 3 算法 1 算法 2 算法 3
    PSC1→PSC2 0.110 0.330 0.340 17.34 69.09 71.14 2.94 7.81 8.25
    PSC2→PSC3 0.095 0.295 0.300 17.57 69.09 69.96 4.76 13.66 13.69
    PSC3→PSC1 0.125 0.320 0.355 17.34 69.09 76.99 2.63 6.13 7.41
    下载: 导出CSV

    表  3  阴影变化下3种算法的实验跟踪性能比较

    Table  3.   Experiment tracking performance comparison of the three algorithms under shading variation

    光照条件 扫描时间/s 总路径的扫描电压/V 能量损失/J
    算法 1 算法 2 算法 3 算法 1 算法 2 算法 3 算法 1 算法 2 算法 3
    PSC1→PSC2 4.0 12.6 12.5 17.34 69.09 71.14 98.19 234.86 260.49
    PSC2→PSC3 4.2 12.3 12.4 17.57 69.09 69.96 158.23 467.10 467.35
    PSC3→PSC1 4.5 12.6 13.8 17.34 69.09 76.99 72.00 266.25 311.85
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-12-14
  • 修回日期:  2023-03-10
  • 网络出版日期:  2024-10-14

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