研究目的
To develop a new computational approach based on Brent’s algorithm for accurate determination of single-diode model parameters to simulate solar cells and modules.
研究成果
The proposed Brent’s algorithm-based method efficiently extracts single-diode model parameters for solar cells and modules, demonstrating superior accuracy and computational efficiency compared to existing methods. It effectively simulates I-V characteristics under varied environmental conditions, offering a robust tool for PV performance assessment and optimization.
研究不足
The method's accuracy is dependent on the initial curve fitting for parameter extraction and may be sensitive to noise in experimental data. The approach is primarily validated on inorganic solar cells, and its applicability to organic-based, Perovskite, and dye-sensitized solar cells may be limited due to non-uniform series resistance distribution.
1：Experimental Design and Method Selection:
A new mathematical manipulation was performed on the single-diode equation to derive a non-linear formula for Rs. Brent’s algorithm was then used to estimate Rs at every fine-tuned point of n, with other parameters determined subsequently. The set of parameters providing the lowest RMSE between experimental and simulated I-V data was selected as optimal.
2：Sample Selection and Data Sources:
Experimental I-V data from various PV cells and modules under different temperatures and irradiations were used.
3：List of Experimental Equipment and Materials:
PV cells and modules, MATLAB for algorithm implementation.
4：Experimental Procedures and Operational Workflow:
The method involved curve fitting to extract initial parameters, iterative tuning of n to find Rs via Brent’s algorithm, and calculation of other parameters to minimize RMSE.
5：Data Analysis Methods:
RMSE, SAE, and MAE were calculated to compare simulated and experimental I-V data.
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