基于有效辐照度修正的光伏电池模型参数辨识和输出特性建模研究

doi:10.19595/j.cnki.1000-6753.tces.231694

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摘要为了提高光伏电池的参数辨识和输出特性计算的精度,该文提出基于单二极管模型的有效辐照度修正方法。通过研究影响光伏输出特性的环境因素,建立测量辐照度到有效辐照度的修正方程,包含常数修正、角度修正、季节修正和温度修正。首先使用解析方法求解参考条件下的光伏电池单二极管模型物理参数值,根据物理参数与辐照度、温度的转化方程,以I-V曲线的方均根误差（RMSE）为目标函数,拟合得到有效辐照度修正方程中各个参数;然后根据光伏组件实际运行条件,计算有效辐照度数值,将修正后的有效辐照度代入物理参数转化方程,进而得到光伏组件运行物理参数和输出特性;最后通过实测数据对所提出方法进行验证。结果表明,在不同天气条件（晴天、阴天）、不同辐照度区间和温度区间,与未修正结果相比,文中所提方法在I-V、P-V输出特性计算和最大功率估计方面的精度均得到提高。

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关键词 ：单二极管模型, 参数辨识, 辐照度修正, 有效辐照度

Abstract：Parameter identification and output characteristic modelling of photovoltaic (PV) module is a complex task with several significant challenges, including recording and contribution of large amounts of data, data privacy protection anduncertainty of physical parameters of PV modules under varying operating conditions. These poses significant challenges for the efficient implementation of traditional mathematical optimization methods. Recently, many researchers have turned their attention to intelligent optimization algorithm methods, which rely on data-driven principles and exhibit strong adaptability to solve the optimal solution. However, as the prediction accuracy of PV power generation improves, more stringent demands are placed on the accuracy of PV module modeling. The traditional analytical calculation approach alone struggles to meet the heightened requirements for power prediction accuracy, as it involves solving for five parameters under changing operating conditions. To tackle these challenges, this paper introduces a new method for parameter identification and modeling of PV module output characteristics that incorporates effective irradiance correction.
First, the study analyzes environmental factors influencing the output characteristics of photovoltaic modules to establish a correction formula that converts measured irradiance to effective irradiance. This formula accounts for constant, angular, seasonal, and temperature adjustments. Second, the paper employs an analytical method to determine the single-diode model’s physical parameters under standard test conditions, fitting each parameter in the effective irradiance correction formula based on how the physical parameters vary with irradiance and temperature. The fitting process is guided by minimizing the root-mean-square error (RMSE) of the current-voltage (I-V) curve. Then, using the proposed correction method, the actual operating conditions of the PV modules are considered to adjust effective irradiance, which is then used to calculate the modules’ physical parameters and output characteristics. Finally, the method’s efficacy is confirmed using measured data: the corrected results enhance the accuracy of the I-V and power-voltage (P-V) output characteristic computations and maximum power estimation, out performing uncorrected outcomes under varied weather (sunny and cloudy), irradiance levels, and temperature ranges.
The following conclusions can be drawn from the case studies: the results show that the correction value of effective irradiance is negative in low irradiance area, and the correction value changes from negative to positive and increases monotonically with the increase of irradiance. Compared with the irradiance obtained by fitting from the measured I-V data, the effective irradiance is more consistent with fitting irradiance than measured irradiance.In different weather conditions (sunny day, cloudy day), different irradiance, temperature and season intervals, the error RMSE of the proposed effective irradiance method is less than that of the measured irradiance calculation results. And the RMSE of high irradiance (greater than 800 W/m²) and temperature intervals (greater than 50℃) is significantly reduced by 21.6% and 18.6%. The mean RMSE is reduced by 9.78% for all outcomes. Compared with the measured irradiance calculation results, the effective irradiance calculation results is in better agreement with the measured maximum power. The proposed method in this study improves the modelling accuracy of PV modules and the accuracy of PV power prediction. Based on the work in this study, establishing more accurate correction equations for irradiance and temperature is the future work.

Key words： Single diode model parameter identification irradiance correction effective irradiance

收稿日期: 2023-10-12

PACS:

TM615

基金资助:国家重点研发计划“极高渗透率分布式光伏发电自适应并网与主动同步关键技术（2022YFB2402900）”和国家电网公司总部科技项目（52060023001T）资助

通讯作者: 张云鹏男,1981年生,副教授,硕士生导师,研究方向为电工理论与新技术、新能源发电预测。E-mail：zhangyp@sdu.edu.cn

作者简介: 李国荣男,2000年生,硕士研究生,研究方向为新能源发电预测。E-mail：202214611@mail.sdu.edu.cn

引用本文:

李国荣, 张云鹏, 周海, 吴骥, 关逸飞. 基于有效辐照度修正的光伏电池模型参数辨识和输出特性建模研究[J]. 电工技术学报, 2024, 39(23): 7331-7340. Li Guorong, Zhang Yunpeng, Zhou Hai, Wu Ji, Guan Yifei. Parameter Identification and Output Characteristics Modelling of Photovoltaic Module Based on Effective Irradiance Correction. Transactions of China Electrotechnical Society, 2024, 39(23): 7331-7340.

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