Parameter Extraction of Single, Double, and Triple-Diode Photovoltaic Models Using the Weighted Leader Search...

Area of Science:

• Renewable Energy Engineering
• Computational Intelligence
• Materials Science

Background:

• Accurate photovoltaic (PV) device modeling is crucial for maximizing technical and economic benefits.
• Parameter extraction for single, double, and triple-diode PV models presents significant challenges.

Purpose of the Study:

• To develop accurate PV models by extracting parameters using the weighted leader search (WLS) algorithm.
• To evaluate and select the most suitable optimization algorithm for PV parameter extraction.

Main Methods:

• Developed 24 PV models (6 for PV cells, 18 for PV modules) using publicly available experimental data.
• Tested seven novel metaheuristic algorithms, including WLS, for PV parameter extraction.
• Employed advanced statistical tests (Friedman, Wilcoxon signed-rank) for algorithm comparison.

Main Results:

• The weighted leader search (WLS) algorithm achieved the lowest minimum, average, RMSE, and standard deviation values.
• WLS demonstrated superior performance in PV parameter extraction compared to six other algorithms.
• Statistical tests confirmed the significant superiority of WLS based on 144 pairwise comparisons.

Conclusions:

• The weighted leader search (WLS) algorithm is highly effective for PV parameter extraction.
• WLS enables the development of accurate PV models, leading to improved performance and economic outcomes.
• WLS is identified as a superior optimization technique for complex PV modeling tasks.