Application of the Genetic Algorithms for Identifying the Electrical Parameters of PV Solar Generators

摘要: The determination of model parameters plays an important role in solar cell design and fabrication, especially if these are well correlated to known physical phenomena. A detailed knowledge the can be way for control manufacturing process, may a mean pinpointing causes degradation performances panels photovoltaic systems being produced. For this reason, identification provides powerful tool optimization performance. algorithms determining cells, two types: those that make use selected parts characteristic (Chan et al., 1987; Charles 1981; 1985; Dufo-Lopez Bernal-Agustin, 2005; Enrique 2007) employ whole (Haupt Haupt, 1998; Bahgat 2004; Easwarakhanthan 1986). first group involves solution five equations derived from considering select points current-voltage (I-V) characteristic, e.g. open-circuit short-circuit coordinates, maximum power slopes at strategic portions different level illumination temperature. This method is often much faster simpler comparison curve fitting. However, disadvantage approach only used determine parameters. fitting methods offer advantage taking all experimental data consideration. Conversely it has artificial solutions. nonlinear procedure based on minimisation not convex criterion, using traditional deterministic leads local minima To overcome problem, least square minimization technique computed with global search approaches such Genetic Algorithms (GAs) Sellami 2007; Zagrouba 2010) strategy, increasing probability obtaining best minimum value cost function very reasonable time. In chapter, we propose numerical GAs identify electrical (PV) modules arrays. These are, respectively, photocurrent (Iph), saturation current (Is), series resistance (Rs),