Traditional methods for estimating output property of the photovoltaic (PV) modules are strongly influenced by the selection of reference condition and transforming equations, which determine the calculated physical parameters under real operating conditions. The differences in the carrier transport properties of PV cells under varying operating conditions, such as the number and velocity of minority carriers at the junction edge and their recombination speed, lead to large deviations in the estimation of the output characteristics, especially under low irradiance conditions. To enhance the accuracy of performance estimation, we propose an improved method that is independent of reference condition. This method eliminates the impact of reference conditions and improves the transformation equations under all irradiance levels. Transformation equations of single diode model are established in different irradiance intervals based on the dependence of physical parameter on irradiance and temperature. Especially in the low irradiance range, all effects of irradiance and temperature are considered for each physical parameter in improved transformation equations. To optimize the unknown parameters in the transformation equations, the artificial hummingbird algorithm is used to fit experimental I–V data. The experimental results of six different types PV modules under a wide range of operating conditions are used to verify the effectiveness of the proposed method. The proposed method offers immediate benefits, including independence from reference condition and a more precise relationship between physical parameters and environmental factors in the estimation of PV output properties. Comparing the results to the traditional method by Laudani, the proposed method demonstrates superior capability in estimating I–V characteristics and accurately identifies the maximum power point under various operating conditions, which is of significant value for engineering applications.

中文翻译：

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改进的独立于参考条件的方法，用于估计不同工作条件下光伏组件的输出性能

估计光伏（PV）组件输出特性的传统方法受到参考条件和转换方程的选择的强烈影响，这决定了实际运行条件下计算的物理参数。光伏电池在不同工作条件下载流子输运特性的差异，例如结边缘少数载流子的数量和速度及其复合速度，导致输出特性的估计存在较大偏差，特别是在低辐照度条件下。为了提高性能估计的准确性，我们提出了一种独立于参考条件的改进方法。该方法消除了参考条件的影响，改进了所有辐照度水平下的变换方程。根据物理参数对辐照度和温度的依赖关系，建立了不同辐照度区间下单二极管模型的变换方程。特别是在低辐照度范围内，改进的变换方程中的每个物理参数都考虑了辐照度和温度的所有影响。为了优化变换方程中的未知参数，使用人工蜂鸟算法来拟合实验 I-V 数据。六种不同类型光伏组件在多种运行条件下的实验结果验证了该方法的有效性。所提出的方法提供了直接的好处，包括独立于参考条件以及在光伏输出特性估计中物理参数和环境因素之间更精确的关系。与Laudani的传统方法相比，该方法在估计I-V特性方面表现出优异的能力，并能准确识别各种工作条件下的最大功率点，具有重要的工程应用价值。