Evaluation of Photovoltaic Module Performance Using Novel Data-driven I-V Feature Extraction and Suns-VOC Determined from Outdoor Time-Series I-V Curves
Evaluation of Photovoltaic Module Performance Using Novel Data-driven I-V Feature Extraction and Suns-VOC Determined from Outdoor Time-Series I-V Curves
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使用新颖的数据驱动 I-V 特征提取和根据室外时间序列 I-V 曲线确定的 Suns-VOC 评估光伏模块性能
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发表时间：
2018
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通讯作者：
R. French
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作者：
Menghong Wang;Xuan Ma;Wei;Jiqi Liu;A. Curran;Erdmut Schnabel;M. Köhl;K. Davis;Jenný Brynjarsdóttir;J. Braid;R. French
提出了一种从真实曝光条件下光伏组件的时间序列曲线中提取最大功率点、短路电流、开路电压、并联电阻、串联电阻、填充因子等性能参数的方法。此外，还提取了$I-V$曲线中的“阶跃”，认为这是模块失配和物理损坏的标志。为了更好地量化性能损失和区分损失机制，还根据上述真实数据构建了太阳$-V_(OC)$伪IV曲线，基于每周测量的$I_{SC}，V_{OC}$对，并根据经过各种算法修正的初始和退化的$I-V$和伪$I-V$曲线的PMP的差异计算性能损失。
This paper presents an alternative method to extract performance parameters including the maximum power point $( P_{MPlt/pgt})$, short-circuit current $( I_{SC})$, open-circuit voltage $(V_{OC})$, shunt resistance $( R_{sh})$, series resistance $( R_{S})$, and fill factor (FF) from time-series $I-V$ curves of PV Modules under real-world exposure conditions. Moreover, ”steps” in $I-V$ curves are also extracted, which is considered as a sign for module mismatch and physical damage. To better quantify performance losses and distinguish loss mechanisms, Suns$-V_{OC}$ psuedo IV curves are also constructed from aforesaid real-world data, based on the measured $I_{SC}, V_{OC}$ pairs during each week, and performance losses are calculated from the difference in PMP of initial and degraded $I-V$ and pseudo $I-V$ curves corrected with various algorithms.