基于非线性最小二乘法的光伏电池参数辨识
摘要：光伏阵列模型的准确性直接关系到其仿真的可靠性,由于模型的参数值随工况的变化而改变,因此根据实测数据辨识模型参数尤为重要。本文采用四参数模型对光伏组件建模,首先提出了一种基于逐步线性搜索的非线性最小二乘光伏电池参数辨识方法,利用该方法辨识得到了光伏电池的参数参考值,辨识曲线与实测数据的对比结果证明了该方法的可行性,且辨识精度较高,实现简单。然后对光伏组件四参数模型中的α、β、γ 3个系数进行了优化,并将光伏电池参数辨识与模型系数优化相结合,提出了参数辨识系数优化(PI-CO)迭代法。迭代过程中参数值和系数值快速收敛至最优点,且目标函数值随之减小,表明该辨识方法能够进一步提高仿真精度。
Abstract:The accuracy of the photovoltaic (PV) array model directly influences the validity of the simulation results, and the parameters of the PV array model may change with the operation conditions. Therefore, it is important to identify the parameters of the PV array model according to the measured data. In this paper, four-parameter model is used to model the PV module. Firstly, a nonlinear-least-squares based parameter identification method of PV cell is proposed to identify parameters of the PV cell based on stepwise linear searching method. The feasibility of the method is proved by comparing the identification curve and the measured data, its identification accuracy is high, and its realization is simple. Then, three parameters (α, β and γ) in the four-parameter model are optimized, and the parameter identification-coefficient optimization (PI-CO) iterative method is proposed through combing parameter identification and model coefficient optimization of the PV cell. In the iterative process, the parameter values and the system values can be converged to the optimal points, and the objective function value is decreased, which shows that PI-CO iterative method can further improve the simulation accuracy.
标题：基于非线性最小二乘法的光伏电池参数辨识
英文标题：Parameter Identification Method for Photovoltaic Cells Based on Nonlinear Least Square Method
作者：张海宁,
关键词：光伏电池, 参数辨识, 非线性最小二乘, PI-CO迭代法,
发表日期：2017-12-09
- 文件大小:
- 1.09 MB
- 下载次数:
- 60
-
高速下载
|
|
