Identification of PV solar cells and modules parameters using the genetic algorithms: Application to maximum power extraction
- Laboratoire de Photovoltaique, des Semi-conducteurs et des Nanostructures, Centre de Recherches et des Technologies de l'Energie, Technopole de Borj-Cedria, Tunis, B.P. 95, 2050 Hammam-Lif (Tunisia)
- Unite de Recherche RME-Groupe AIA, Institut National des Sciences Appliquees et de Technologie (Tunisia)
In this paper, we propose to perform a numerical technique based on genetic algorithms (GAs) to identify the electrical parameters (I{sub s}, I{sub ph}, R{sub s}, R{sub sh}, and n) of photovoltaic (PV) solar cells and modules. These parameters were used to determine the corresponding maximum power point (MPP) from the illuminated current-voltage (I-V) characteristic. The one diode type approach is used to model the AM1.5 I-V characteristic of the solar cell. To extract electrical parameters, the approach is formulated as a non convex optimization problem. The GAs approach was used as a numerical technique in order to overcome problems involved in the local minima in the case of non convex optimization criteria. Compared to other methods, we find that the GAs is a very efficient technique to estimate the electrical parameters of PV solar cells and modules. Indeed, the race of the algorithm stopped after five generations in the case of PV solar cells and seven generations in the case of PV modules. The identified parameters are then used to extract the maximum power working points for both cell and module. (author)
- OSTI ID:
- 21318387
- Journal Information:
- Solar Energy, Vol. 84, Issue 5; Other Information: Elsevier Ltd. All rights reserved; ISSN 0038-092X
- Country of Publication:
- United States
- Language:
- English
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