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Parameter estimation of solar cells using datasheet information with the application of an adaptive differential evolution algorithm

机译:利用数据表信息和自适应差分进化算法的应用来估算太阳能电池的参数

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A solar cell or photovoltaic (PV) module is electrically represented by an appropriate circuit model with certain defined parameters. The parameters are required to be correctly computed from solar cell characteristic and/or a set of experimental data for simulation and control of the PV system. However, experimental data or accurate characteristic data (i.e. current-voltage or I-V curve) of a PV module may not be readily available. The manufacturer of a PV system usually provides relevant information on open circuit, short circuit and maximum power points. Therefore, an alternate approach is to estimate the PV system parameters by utilizing the I-V characteristic data at these three major points. The process involves formulation and solution of complex non-linear equations from an adopted solar cell model. This paper proposes an application of an advanced adaptive differential evolution algorithm on the problem of PV module parameter estimation using minimum available information from the manufacturer datasheet by implementing single-diode and double-diode models. Linear population size reduction technique of success history based adaptive differential evolution (L-SHADE) algorithm is implemented to minimize the error of current-voltage relationships at the above-mentioned three important points defining the I-V characteristic. The algorithm facilitates evolution of solutions that result in almost zero error ( 10(-12)) at these three major points. All relevant parameters of the PV cell are optimized by the algorithm without any assumption or predetermination of parameters. It is observed that a set of feasible solutions (parameters) is obtained for the PV module from multiple runs of the algorithm. The fact of attaining several probable solutions from datasheet information using few other metaheuristics is also discussed in this work. (C) 2018 Elsevier Ltd. All rights reserved.
机译:太阳能电池或光伏(PV)模块由具有特定定义参数的适当电路模型电气表示。需要从太阳能电池特性和/或一组实验数据中正确计算出参数,以进行光伏系统的仿真和控制。但是,PV模块的实验数据或准确的特性数据(即电流-电压或I-V曲线)可能不容易获得。光伏系统的制造商通常会提供有关开路,短路和最大功率点的相关信息。因此,另一种方法是通过利用这三个主要点的I-V特性数据来估计PV系统参数。该过程涉及根据采用的太阳能电池模型来制定和求解复杂的非线性方程。本文提出了一种先进的自适应差分进化算法,该方法通过实现单二极管和双二极管模型,利用制造商数据表中的最少可用信息,来解决光伏模块参数估计问题。实施基于成功历史的线性种群大小缩减技术的自适应差分进化(L-SHADE)算法,以在定义I-V特性的上述三个重要点上使电流-电压关系的误差最小。该算法有助于解决方案的演变,在这三个主要点上几乎导致零误差(<10(-12))。该算法可优化光伏电池的所有相关参数,而无需任何假设或预先确定参数。可以看到,从算法的多次运行中获得了PV模块的一组可行解(参数)。本文还讨论了使用其他几种元启发式方法从数据表信息中获得几种可能的解决方案的事实。 (C)2018 Elsevier Ltd.保留所有权利。

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