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首页> 外文期刊>Energy Conversion & Management >Estimation of the photovoltaic cells/modules parameters using an improved Rao-based chaotic optimization technique
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Estimation of the photovoltaic cells/modules parameters using an improved Rao-based chaotic optimization technique

机译：使用改进的基于RAO的混沌优化技术估计光伏电池/模块参数

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摘要

One of the most important challenges issues while addressing the industrial applications of solar photovoltaic systems is to predict the performance of a photovoltaic system since the current-voltage and power-voltage characteristics are highly nonlinear. Note that the majority of manufacturer's data sheets do not provide full information about internal parameters of photovoltaic systems which are crucial to simulate an accurate photovoltaic module. As a major alternative for parameters' extraction of solar photovoltaic cells/modules, mathematical based optimization and global research techniques are more suitable compared with other methods. In this context, a new optimization method is proposed in this paper to extract the parameters of solar photovoltaic cells/modules of different technologies while providing an accurate representation of the current-voltage and power-voltage curves. For this purpose, the proposed optimization algorithm is based on a chaotic generator combined with the newly developed Rao-1 optimization algorithm to extract the photovoltaic parameters. A comparative performance analysis shows that the proposed optimization algorithm with a chaotic based search sequence has better performance in terms of robustness and accuracy while extracting the photovoltaic parameters than many recent well-known optimization algorithms. Further, comprehensive results show that the double diode model is more accurate to estimate the appropriate values of the model's parameters.
机译：在解决太阳能光伏系统的工业应用的同时最重要的挑战问题是预测光伏系统的性能，因为电流电压和电力电压特性是高度非线性的。请注意，大多数制造商的数据表不提供有关光伏系统内部参数的完整信息，这对于模拟精确的光伏模块至关重要。作为参数提取太阳能光伏电池/模块的主要替代方案，与其他方法相比，数学基础优化和全球研究技术更适合。在本文中，在本文中提出了一种新的优化方法，以提取不同技术的太阳能光伏电池/模块的参数，同时提供电流电压和电力电压曲线的精确表示。为此目的，所提出的优化算法基于混沌发生器与新开发的RAO-1优化算法结合以提取光伏参数。比较性能分析表明，具有混沌的搜索序列的所提出的优化算法在鲁棒性和准确性方面具有更好的性能，同时提取光伏参数而不是许多近期的众所周知的优化算法。此外，综合结果表明，双二极管模型更准确地估计模型参数的适当值。

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