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An improved explicit double-diode model of solar cells: Fitness verification and parameter extraction

机译:改进的太阳能电池显式双二极管模型:适应性验证和参数提取

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摘要

Accurate simulation of photovoltaic characteristics is now a mandatory obligation before validating an experiment; hence, accurate model and parameters of solar cells are indispensable. This paper presents an improved explicit double-diode model based on the Lambert W function (EDDM-LW), and then compares the fitness and parameter extraction performance. By defining two new parameters (K and r) to separate the exponential function in double-diode model (DDM) and using the Lambert W function, the explicit expression for I-V characteristics is proposed. In contrast to exiting works, the new parameters can readily be computed by the electrical characteristics of the standard test condition without an implicit characteristic. To verify the accuracy of the proposed model, the fitness difference is first investigated with a solar cell and three different types of solar modules. The results indicate that under the same parameter values, EDDM-LW achieves the lowest root mean square error value and exhibits better fitness in representing the I-V characteristics. In addition, the optimal parameters are extracted by an improved teaching-learning-based optimization algorithm. The experimental results show that the optimal parameter values extracted from EDDM-LW are more accurate than those extracted from DDM. Based on these observations, EDDM-LW can be deemed a useful and practical model for the simulation, evaluation, and optimization of the photovoltaic system.
机译:现在,在验证实验之前,必须准确模拟光伏特性。因此,精确的太阳能电池模型和参数是必不可少的。本文提出了一种改进的基于Lambert W函数(EDDM-LW)的显式双二极管模型,然后比较了适应度和参数提取性能。通过定义两个新参数(K和r)以分离双二极管模型(DDM)中的指数函数并使用Lambert W函数,提出了I-V特性的显式表达式。与现有工作相反,可以通过标准测试条件的电气特性轻松计算出新参数,而无需隐含特性。为了验证所提出模型的准确性,首先使用太阳能电池和三种不同类型的太阳能模块研究适应性差异。结果表明,在相同的参数值下,EDDM-LW达到最低的均方根误差值,并且在表现I-V特性方面表现出更好的适应性。另外,通过改进的基于教学学习的优化算法提取最优参数。实验结果表明,从EDDM-LW提取的最优参数值比从DDM提取的最优参数值更准确。基于这些观察,可以将EDDM-LW视为用于光伏系统的仿真,评估和优化的有用且实用的模型。

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