期刊
SOLAR ENERGY MATERIALS AND SOLAR CELLS
卷 148, 期 -, 页码 87-98出版社
ELSEVIER
DOI: 10.1016/j.solmat.2015.09.003
关键词
Photovoltaics (PV); Evolutionary algorithms; PV cell electrical parameters extraction; Temperature effects; Particle swarm optimization (PSO); Cuckoo search (CS)
Photovoltaic (PV) cells induce current-voltage (I-V) characteristics dependent on the PV cell technology, the thin film structure and their eventual flaws during the elaboration process. The operation conditions also have a relevant impact on electrical curves characterizing these devices. The electrical parameters can be extracted from a PV panel standard datasheet using the commonly encountered single and double diode equivalent models representing the PV cell. This was done, in the present paper, at the most fundamental expression of these two models using evolutionary algorithms implemented in MATLAB (i.e. metaheuristic optimization methods). Four different I-V characteristics were available for the investigated commercial PV panel. They were fitted separately using the diode models and then taken as a whole to obtain parameters as physically meaningful as possible for the whole temperature range. The metaheuristic methods performed well for this problem, especially the cuckoo search algorithm. However, even with a good fitting of the fundamental behavior of the I-V characteristics, the presented approach may yield optimized solutions not as physically correct as it was expected. Thus, care must be taken for correctly interpreting the optimization results. (C) 2015 Elsevier B.V. All rights reserved.
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