基于矢量加权平均算法的太阳能电池参数估计

Davut Izci, Serdar Ekinci, Süleyman Dal, Necmettin Sezgin
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引用次数: 3

摘要

可再生能源由于其不可否认的可持续性潜力而受到研究界的强烈吸引。其中,太阳能因其全球可用性而占有独特的地位。然而,要将光伏电池与电网合理整合,必须解决一些挑战。在这方面,本文研究了一种新的智能优化技术,即加权向量均值(也称为INFO)算法,在成功估计单二极管和双二极管光伏模型参数方面的前景。所得结果与文献报道的现有方法的结果进行了比较。结果表明,该优化方法对光伏电池单、双二极管模型的参数估计具有良好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parameter Estimation of Solar Cells via Weighted Mean of Vectors Algorithm
The renewable energy sources has seen an intense attraction from the research community due to their undeniable potential in terms of sustainability. Amongst them, the solar energy holds a unique place because of the global availability. However, certain challenges must be addressed to appropriately integrate the photovoltaic cells with the power networks. In this regard, this paper investigates the promise of a new intelligent optimization technique named weighted mean of vectors (also known as INFO) algorithm in terms of successfully estimating the parameters of single and double diode photovoltaic models. The obtained results are compared with that of the available approaches reported in literature. The proposed optimization technique is demonstrated to have good performance for successfully estimating the parameters of single and double diode models of the photovoltaic cells.
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