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A linear method to extract diode model parameters of solar panels from a single I–V curve

机译:一种从单个I-V曲线中提取太阳能电池板二极管模型参数的线性方法

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摘要

The I-V characteristic curve is very important for solar cells/modules being a direct indicator of performance.\udBut the reverse derivation of the diode model parameters from the I-V curve is a big challenge due to the strong nonlinear relationship between the model parameters. It seems impossible to solve such a nonlinear problem accurately using linear identification methods, which is proved wrong in this paper. By changing the viewpoint from conventional static curve fitting to dynamic system identification, the integral-based linear least square identification method is proposed to extract all diode model parameters simultaneously from a single I-V curve. No iterative searching or approximation is required in\udthe proposed method. Examples illustrating the accuracy and effectiveness of the proposed method, as compared to the existing approaches, are presented in this paper. The possibility of real-time monitoring of model parameters versus environmental factors (irradiance and/or temperatures) is also discussed.
机译:I-V特性曲线对于太阳能电池/组件的性能直接指标非常重要。\ ud但是,由于模型参数之间存在很强的非线性关系,因此从I-V曲线反向推导二极管模型参数是一个巨大的挑战。使用线性识别方法似乎无法准确解决此类非线性问题,这在本文中被证明是错误的。通过将观点从传统的静态曲线拟合转变为动态系统辨识,提出了一种基于积分的线性最小二乘辨识方法,可从一条I-V曲线中同时提取所有二极管模型参数。所提出的方法不需要迭代搜索或近似。本文介绍了一些示例,说明了与现有方法相比所提方法的准确性和有效性。还讨论了对模型参数与环境因素(辐照度和/或温度)进行实时监视的可能性。

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