A new metaphor-less algorithms for the photovoltaic cell parameter estimation

The performance of the solar photovoltaic (PV) system can be improved by an accurate modelling of the solar cells, but cell modelling is inaccurate due to the lack of precise solar cell parameters. To model a reliable solar PV cell, the required parameters will not be provided in the manufacturer's datasheet. Therefore, it's necessary to estimate the required parameters adequately. Thereby, with this observation, in this paper, proposed a simple multi-objective optimization algorithm to estimate the cell parameters. Various optimization algorithms address this issue; however, most of the algorithms produce suboptimal results due to local minima and premature convergence. So, this paper proposes two simple metaphor-less algorithms named as Rao-2 (R-II), and Rao-3 (R-III) algorithm to estimate the PV cell parameters. The performance of the proposed algorithms is compared with other well-known optimization algorithms to show the proficiency of the proposed algorithms. To validate the performance of the proposed algorithms, the estimated parameters are compared with experimental results, including statistical analysis. Moreover, from the results, it can be judged that the proposed algorithms are more suitable for the estimation of three types of solar PV models effectively.