Parameter extraction of solar cell models using mutative-scale parallel chaos optimization algorithm

Abstract

To simulate solar cell systems or to optimize photovoltaic (PV) system performance, accurate parameter values of solar cell systems are extremely crucial. In this article, the parameter extraction of solar cell models is posed as an optimization process with an objective function minimizing the difference between the measured values and estimated data. A mutative-scale parallel chaos optimization algorithm (MPCOA) using crossover operation and merging operation is proposed for this optimization problem. To verify the performance of MPCOA, it is applied to extract the parameters of different solar cell models, i.e., double diode, single diode, and PV module. Comparison results with other parameter extraction techniques are in favor of the MPCOA, which signifies its potential as another optional method.