A photovoltaic parameter identification method based on Pontogammarus maeoticus swarm optimization - Chen, Ling; Han, Wei; Shi, Yang; Zhang, Jingwei; Cao, Shang (Frontiers in Energy Research, 2023)
Currently, the improvement of model parameter extraction accuracy is essential to research of photovoltaic (PV) field. In this paper, a model parameter identification based on pontogammarus maeoticus swarm optimization (PMSO) is proposed. The PMSO is used for parameter identification of mathematical model of PV module. In the PMSO algorithm, by giving the ability of free exploration to the particles that are far away from the optimal solution, the search scope is expanded to avoid falling into the local optimal. Besides, local search for each Gammarus has a better convergence for PV parameter identification. Therefore, the accuracy of parameter identification for modeling PV module is improved. The feasibility and superiority of the proposed method are verified by the measured I-V characteristics of a PV array. Experimental results and error analysis verify that, compared with the conventional meta-heuristic algorithms, the proposed method achieves higher modeling accuracy. The proposed PMSO algorithm is suitable for engineering application of parameters identification and modeling of PV modules.