Metaheuristic-Based Photovoltaic Parameter Identification Using a Dynamic Elite Cooperative Artificial Circulatory System Algorithm
Year: 2026
Type: conference-paper
Abstract: Accurate parameter estimation of photovoltaic (PV) models is essential for performance evaluation, efficiency enhancement, and reliable energy forecasting in solar energy systems. However, the nonlinear, multimodal, and implicit nature of the current–voltage (I–V) relationship makes this task challenging for conventional optimization methods, which often suffer from premature convergence and sensitivity to initial conditions. In this study, a modified variant of the Artificial Circulatory System Algorithm, termed Dynamic Elite Cooperative ACSA (DEC-ACSA), is proposed for estimating the unknown parameters of the Single-Diode Model (SDM). The proposed approach extends the original ACSA by incorporating dynamic population grouping, elite-guided cooperative interaction, and directional elite refinement, thereby aiming to improve convergence stability and the utilization of high-quality population information. The objective is to minimize the residual root mean square error (RMSE) of the implicit SDM equation using measured I–V data from four established benchmarks: the RTC France solar cell and the PWP201, STM6-40/36, and STP6-120/36 PV modules. The performance of DEC-ACSA is evaluated against the original ACSA, Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Genetic Algorithm (GA), and Henry Gas Solubility Optimization (HGSO) over 30 independent runs under an equal budget of 50,100 function evaluations. The DEC-ACSA configuration selected on RTC France was retained unchanged for the three additional module benchmarks. DEC-ACSA achieved mean residual RMSE values of 1.2514 × 10−3, 2.656 × 10−3, 2.647 × 10−3, and 1.8108 × 10−2 for RTC France, PWP201, STM6-40/36, and STP6-120/36, respectively, while consistently reducing run-to-run variability relative to ACSA. Holm-corrected tests showed no significant difference from PSO on RTC France and PWP201, whereas significant differences from all comparison algorithms were observed on STM6-40/36 and STP6-120/36. I–V reconstruction further confirmed close agreement with the measured data across all four PV systems.
Authors: Nermin Özcan, Imam Barket Ghiloubi
Institutions: İskenderun Technical University, University of Biskra
Language: English
Field: Energy
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7207522720