Performance analysis of animal migration optimization algorithm in extracting solar cell double diode model parameters

Abstract

Modeling solar cell involved the formulation of the current versus voltage (I-V) non-linear curve. Obtaining the accurate model parameters value is important for better performance evaluation, simulation and control of solar cell and module. Extracting these values using traditional methods required more resources, therefore, the used of meta heuristic optimization method become an attractive choice. Some optimization algorithms have been used to estimate the model parameters. However, more investigation is needed to improve model estimation. In this paper, the performance of Animal Migration Optimization (AMO) technique in identifying the unknown parameters of solar cell double diode model is studied. A measurement data of a 57 mm diameter commercial (R.T.C. France) silicon solar cell is used to observe the performance of this algorithm and the consistency of accurately estimating various parameters. The results show that the estimated and experimental data are accurately fitted and certify a good agreement. Furthermore, comparative study among different parameter estimation techniques is presented to demonstrate the effectiveness of the proposed approach.