用萤火虫算法辨识太阳能电池参数

M. Louzazni, A. Craciunescu, E. Aroudam, A. Dumitrache
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引用次数: 12

摘要

由于太阳电池模型的非线性、多变量和多模态特性,传统方法无法对太阳电池参数进行高精度估计。最近,仿生算法引起了人们的关注。萤火虫算法是一种自然启发的随机优化算法,它基于萤火虫群的闪烁模式和行为,是解决现代非线性复杂系统全局优化问题最强大的算法之一。本文提出了一种从实验I-V特性中提取单二极管模型太阳能电池参数的萤火虫算法。萤火虫算法得到的结果很有希望,优于其他方法的结果。
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Identification of Solar Cell Parameters with Firefly Algorithm
Due to the non-linearity, multivariable and multimodal features of current-voltage of solar cell models, the conventional methods are incapable to estimating the parameters of solar cell with high accuracy. Recently, the bio-inspired algorithms have attracted the attention. The firefly algorithm is nature-inspired stochastic optimization algorithm is among the most powerful algorithms in solving modern global optimization for nonlinear and complex system, based on the flashing patterns and behavior of fireflies swarm. In this paper, a firefly algorithm is proposed to extract the parameters of single diode model solar cell from experimental I-V characteristics. The results obtained by firefly algorithm are quite promising and outperform those found by the other methods.
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