Xu Chen1,*, Shuai Wang1, Kaixun He2
CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1779-1806, 2025, DOI:10.32604/cmc.2025.066543
- 29 August 2025
Abstract Accurate and reliable photovoltaic (PV) modeling is crucial for the performance evaluation, control, and optimization of PV systems. However, existing methods for PV parameter identification often suffer from limitations in accuracy and efficiency. To address these challenges, we propose an adaptive multi-learning cooperation search algorithm (AMLCSA) for efficient identification of unknown parameters in PV models. AMLCSA is a novel algorithm inspired by teamwork behaviors in modern enterprises. It enhances the original cooperation search algorithm in two key aspects: (i) an adaptive multi-learning strategy that dynamically adjusts search ranges using adaptive weights, allowing better individuals to More >
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