Improved and Fast Global Maximum Power Point Tracking Algorithm of Photovoltaic Power Generation System
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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，研究了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 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%.
Abstract:In order to improve the energy utilization of photovoltaic (PV) power generation under partial shading conditions (PSCs), an improved and fast global maximum power point tracking (GMPPT) algorithm was proposed. Firstly, the output characteristics of PV array under PSCs were researched, and the output curve of PV array was divided into constant current region (CCR) and constant voltage region (CVR) according to the relationship between knee point and open circuit voltage. Then, the operation principles of the traditional maximum power trapezium (MPT) algorithm and the improved and fast GMPPT algorithm were analyzed. The improved and fast GMPPT algorithm is based on the MPT algorithm, where the search interval is limited by dynamic upper and lower limits of voltage, and CCR with a long adjustment time was skipped to further improve the tracking speed. Finally, the effectiveness of the proposed algorithm was verified by simulation and experiment. The experimental results reveal that the minimum tracking time of the improved and fast GMPPT algorithm is 4 s, and the scanning voltage and the energy loss of the proposed algorithm are 17.34 V and 98.19 J, respectively. Compared with the traditional global scanning algorithm and the MPT algorithm, the proposed algorithm decreases tracking time by 68.25% and 68.00%, lowers scanning voltage by 74.86% and 75.63%, and reduces energy loss by 58.19% and 62.31%, respectively.
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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 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 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 
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表 2 阴影条件变化下三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
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表 3 阴影变化下三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
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