| 解析法-Nelder Mead单纯形算法确定太阳电池参数 |
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| 引用本文： | 高献坤,姚传安,高向川,余泳昌.解析法-Nelder Mead单纯形算法确定太阳电池参数[J].农业工程学报,2014,30(6):97-106. |
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| 作者姓名： | 高献坤 姚传安 高向川 余泳昌 |
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| 作者单位： | 1. 河南农业大学农业部农村可再生能源新材料与装备重点实验室，郑州 450002;;1. 河南农业大学农业部农村可再生能源新材料与装备重点实验室，郑州 450002;;2. 郑州大学信息工程学院，郑州 450001;;1. 河南农业大学农业部农村可再生能源新材料与装备重点实验室，郑州 450002; |
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| 基金项目： | 河南省重点科技攻关项目（102102210154）；教育部博士点专项科研基金项目（20104105110004）；国家自然科学基金资助项目（U1204607） |
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| 摘 要： | 光伏发电系统的设计计算、性能评估及优化控制要求快速、准确的确定太阳电池模型参数。针对太阳电池单、双二极管模型参数辨识问题,该文提出一种基于解析法和Nelder Mead单纯形法重启策略的A-bcNM混合算法。先用实测I-V曲线上的部分关键点计算合成参数,再以单二极管模型近似解析式快速定位搜索始点,最后在边界范围内利用Nelder Mead单纯形算法的重启策略最小化实测数据与模拟结果之间的均方根误差,以提高拟合精度及参数解的质量。MATLAB环境下,利用2种典型太阳电池的实测数据对A-bcNM算法的有效性进行了测试和验证。与已有的其他算法相比,A-bcNM算法收敛速度快,计算量小,辨识精度高,可快速、准确的确定单、双二极管模型参数,为识别太阳电池的工作特性提供了一种有效方法。
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| 关 键 词： | 太阳电池 模型 参数 单二极管 双二极管 Nelder Mead单纯形算法 |
| 收稿时间： | 2013/12/8 0:00:00 |
| 修稿时间： | 2014/2/19 0:00:00 |
Identification of solar cell model parameters by combining analytical method with Nelder-Mead simplex method |
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| Gao Xiankun,Yao Chuan''an,Gao Xiangchuan and Yu Yongchang.Identification of solar cell model parameters by combining analytical method with Nelder-Mead simplex method[J].Transactions of the Chinese Society of Agricultural Engineering,2014,30(6):97-106. |
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| Authors: | Gao Xiankun Yao Chuan'an Gao Xiangchuan and Yu Yongchang |
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| Institution: | 1. Key Laboratory of New Materials and Facilities for Rural Renewable Energy, Ministry of Agriculture, Henan Agricultural University, Zhengzhou 450002, China;;1. Key Laboratory of New Materials and Facilities for Rural Renewable Energy, Ministry of Agriculture, Henan Agricultural University, Zhengzhou 450002, China;;2. School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China;;1. Key Laboratory of New Materials and Facilities for Rural Renewable Energy, Ministry of Agriculture, Henan Agricultural University, Zhengzhou 450002, China; |
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| Abstract: | In the simulation and design calculations of photovoltaic (PV) systems, it is very crucial to select an accurate mathematical model to closely represent the nonlinear current-voltage (I-V) characteristics of solar cells. In practice, two main equivalent circuit models are used widely: the single and double diode models. The single diode model contains five unknown parameters, while the double diode model has seven unknown parameters, which are not always available in commercial PV datasheets. Hence, parameter extraction of solar cell models is an essential prerequisite for the precise modeling, performance analysis, and optimal control of PV systems. Unfortunately, since the single and double diode models are inherently implicit and transcendental in nature, it is difficult to quickly and accurately identify their unknown parameters just by analytic methods or traditional numerical optimization methods. By combining an approximate analytic method and the Nelder-Mead simplex method (NM), an comprehensively hybrid algorithm named A-bcNM is proposed in this paper to simultaneously determine the precise values of photo-generated current, diode saturation currents, parasitic series and shunt resistances, and diode ideality factors of solar cell models. In the A-bcNM method, the parameter identification problem of solar cell models is formulated as a bounded, multidimensional, nonlinear optimization problem of minimizing a given objective function. The basic idea of the A-bcNM method can be broken up into three phases. First, we make use of several key points on the nonlinear I-V characteristic curve to roughly estimate the synthetic parameters, i.e., the output current and voltage at the maximum power point, short-circuit current, open-circuit voltage, and slopes of the I-V characteristic at the axis intersections. Secondly, we substitute the synthetic parameters into our proposed approximate analytical formulas of the single diode model so as to quickly pinpoint the initial search point for the NM method. The third phase of A-bcNM is utilizing the NM method as optimizer to minimize the root mean square error between the experimental data and the simulated data, and restart the NM method at the currently observed points several times. The main intention of restarting the NM method is to escape from the local extreme points and further improve the precision of fitting and the quality of parameter solutions. To evaluate the speed of convergence and accuracy of the A-bcNM method presented here, single and double diode models of two typical solar cells were tested. The identification results indicate that the simulation data with the parameters obtained by A-bcNM method are in very good agreement with the experimental data in all cases. Comparing with the best known methods reported in the literature, such as a genetic algorithm (GA), simulated annealing (SA), pattern search (PS), particle swarm optimization (PSO), harmony search (HS), artificial bee swarm optimization (ABSO), improved adaptive differential evolution (IADE), bird mating optimizer (BMO), and repaired adaptive differential evolution (Rcr-IJADE), all cases demonstrate that the A-bcNM method is rather simple, straightforward, computationally efficient and sufficiently accurate for parameter identification of solar cell models. In short, simple concept, easy implementation and high performance are the main advantages of the A-bcNM method, and it is useful for PV systems designers to build an efficient and accurate solar cell system simulator. |
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| Keywords: | solar cells models parameterization single diode double diode Nelder-Mead simplex method |
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