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采用近似修正技术对光伏电池和组件参数进行简单高效的估算。

Simple and efficient estimation of photovoltaic cells and modules parameters using approximation and correction technique.

机构信息

Department of Physics, Faculty of Science, Universiti Teknologi Malaysia (UTM), Skudai, Johor, Malaysia.

College of Basis Education, Charmo University, Chamchamal, Kurdistan Region, Iraq.

出版信息

PLoS One. 2019 May 2;14(5):e0216201. doi: 10.1371/journal.pone.0216201. eCollection 2019.

DOI:10.1371/journal.pone.0216201
PMID:31048867
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6497267/
Abstract

The behavior of solar cells and modules under various operational conditions can be determined effectively when their intrinsic parameters are accurately estimated and used to simulate the current-voltage (I-V) characteristics. This work proposed a new computational approach based on approximation and correction technique (ACT) for simple and efficient extraction of solar cells and modules parameters from the single-diode model. In this technique, an approximated value of series resistance (Rs) was first derived and used to determine the initial value of parallel resistance (Rp). Later, the final corrected values of Rs and Rp were obtained by resubstituting their approximated values in a five-loop iteration using the manipulated equations. For rapid evaluation and validation of the proposed technique, a software application was also created using MATLAB program. The correctness and robustness of the proposed technique was validated on five types of solar cells and modules operated at varied temperatures and irradiances. The lowest RMSE value was achieved for RTC France (7.78937E-4) and PVM 752 GaAs (2.10497E-4) solar cell. The legitimacy of ACT extracted parameters was established using a simple yet competitive implementation approach wherein the performance of the developed technique was compared with several state-of-the-art methods recently reported in the literature.

摘要

当准确估计太阳能电池和模块的固有参数并用于模拟电流-电压(I-V)特性时,可以有效地确定它们在各种工作条件下的行为。这项工作提出了一种新的基于近似和校正技术(ACT)的计算方法,用于从单二极管模型中简单高效地提取太阳能电池和模块的参数。在该技术中,首先推导出串联电阻(Rs)的近似值,并将其用于确定并联电阻(Rp)的初始值。然后,通过在五次循环迭代中重新代入其近似值,并使用处理后的方程,获得 Rs 和 Rp 的最终修正值。为了快速评估和验证所提出的技术,还使用 MATLAB 程序创建了一个软件应用程序。在不同温度和辐照度下运行的五种类型的太阳能电池和模块上验证了所提出技术的正确性和鲁棒性。RTC France(7.78937E-4)和 PVM 752 GaAs(2.10497E-4)太阳能电池的 RMSE 值最低。使用简单而具有竞争力的实现方法来确定 ACT 提取参数的合法性,其中比较了开发技术的性能与最近文献中报道的几种最先进的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab3c/6497267/0c44ee72da6b/pone.0216201.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab3c/6497267/81dded2be8eb/pone.0216201.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab3c/6497267/794880d307e9/pone.0216201.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab3c/6497267/d9cb03bfdbe5/pone.0216201.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab3c/6497267/0c44ee72da6b/pone.0216201.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab3c/6497267/81dded2be8eb/pone.0216201.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab3c/6497267/794880d307e9/pone.0216201.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab3c/6497267/d9cb03bfdbe5/pone.0216201.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab3c/6497267/0c44ee72da6b/pone.0216201.g004.jpg

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本文引用的文献

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2
A neural network based computational model to predict the output power of different types of photovoltaic cells.一种基于神经网络的计算模型,用于预测不同类型光伏电池的输出功率。
PLoS One. 2017 Sep 12;12(9):e0184561. doi: 10.1371/journal.pone.0184561. eCollection 2017.
3
Employment of single-diode model to elucidate the variations in photovoltaic parameters under different electrical and thermal conditions.
最先进的元启发式技术在太阳能电池/组件参数提取中的性能研究。
Sci Rep. 2023 Jul 10;13(1):11134. doi: 10.1038/s41598-023-37824-4.
采用单二极管模型来阐明不同电学和热学条件下光伏参数的变化。
PLoS One. 2017 Aug 9;12(8):e0182925. doi: 10.1371/journal.pone.0182925. eCollection 2017.