GA-based solar cell parameters extraction Application to single, double and triple diode models

In this paper, we propose a new technique based on genetic algorithm for the extraction of electrical parameters (the saturation current, the serial resistance, the parallel resistance and the ideality factor). The models with five, seven and nine parameters respectively are considered. The genetic algorithm is used as a tool for optimization to increase the probability of reaching the global minimum solutions in a short time with a very good accuracy based on the minimization of the quadratic error between experimental and theoretical characteristics. The simulation results show that the accuracy of the heuristic approach is effective for modeling in the case of solar modules. The values of squared errors are around zero (5.8297 × 10-8, 3.0751 × 10-7 and 1.7243 ×10-5 for the five, seven and nine parameters models, respectively). On the other hand, the results were obtained after only seven generations which can be considered very fast for a nonlinear optimization problem with many physical constraints. The results prove that the GA is very suitable for estimating electrical parameters needed for modeling the PV array