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首页> 外文期刊>Energy Conversion & Management >Performance comparison of exponential, Lambert W function and Special Trans function based single diode solar cell models
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Performance comparison of exponential, Lambert W function and Special Trans function based single diode solar cell models

机译：基于指数，Lambert W函数和基于特殊Trans函数的单二极管太阳能电池模型的性能比较

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摘要

Accurate modeling plays an important role in solar cell simulation. In order to reveal the applicability and superiority of Special Trans function based single diode model (SBSDM), this paper presents a comprehensive comparison of SBSDM, Lambert W function based single diode model (LBSDM) and exponential-type single diode model (SDM). The performance difference of SBSDM, LBSDM and SDM is verified and compared in two aspects: (1) different fitness to the measured I-V data of solar cells and (2) different parameter extraction performance. To be objective and reproducible, the reported parameter values of standard datasets and measured datasets are employed to validate the fitness difference of the three models. The comparison results indicate that SBSDM always exhibits better fitness than LBSDM and SDM in representing the I-V characteristics of various solar cells and can provide a closer prediction to actual maximum power points. With the help of a ranking based branch selection strategy, a modified Nelder-Mead simplex (MNMS) algorithm is proposed to test the parameter extraction performance of SBSDM, LBSDM and SDM. The comparison results reveal that the time computational efficiency of SBSDM is inferior to SDM but superior to LBSDM. SBSDM always achieves superior accuracy and convergence speed than LBSDM and SDM, although lacking enough statistical robustness. Due to these superiorities, SBSDM is quite promising and envisaged to be the most valuable model for solar cell parameter extraction and PV system simulation.
机译：准确的建模在太​​阳能电池仿真中起着重要作用。为了揭示基于特殊Trans函数的单二极管模型（SBSDM）的适用性和优越性，本文对SBSDM，基于Lambert W函数的单二极管模型（LBSDM）和指数型单二极管模型（SDM）进行了全面比较。从两个方面验证和比较了SBSDM，LBSDM和SDM的性能差异：（1）对太阳能电池I-V数据的适应性不同，以及（2）参数提取性能不同。为了客观和可重复，采用标准数据集和测量数据集的报告参数值来验证这三个模型的适应性差异。比较结果表明，SBSDM在表示各种太阳能电池的I-V特性方面总是比LBSDM和SDM表现出更好的适应性，并且可以提供更接近实际最大功率点的预测。借助基于排名的分支选择策略，提出了一种改进的Nelder-Mead单纯形算法（MNMS），以测试SBSDM，LBSDM和SDM的参数提取性能。比较结果表明，SBSDM的时间计算效率低于SDM，但优于LBSDM。尽管缺乏足够的统计鲁棒性，但SBSDM始终比LBSDM和SDM具有更高的准确性和收敛速度。由于这些优势，SBSDM非常有前途，并有望成为太阳能电池参数提取和光伏系统仿真的最有价值的模型。

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