Extraction of electrical parameters for one diode photovoltaic model using quasi-oppositional Rao-1 optimization algorithm

Abstract

Usually the model parameters of photovoltaic (PV) cells are unavailable in their datasheet provided by the manufacturers. Hence, the problem of extracting appropriate PV parameters is of high importance, and has been highly attracted by researchers. This paper presents a new method to estimate the parameters of the one diode model (ODM), namely quasi-oppositional Rao-1 optimization algorithm (QORao-1). The present method uses only addition and multiplication operations with a quasi-oppositional-based learning process, in order to improve the exploration capability of the original Rao-1 algorithm. Hence, an attractive amelioration in the Root-Mean-Square-Error (RMSE) values is acquired. Comparative performance analysis demonstrates that the QORao-1 algorithm has better performance in terms of robustness and accuracy while estimating the PV parameters than many well-known algorithms.

Keywords

• modelling
• optimization
• parameters identification
• photovoltaic
• rao-1 algorithm