Hybrid Solar PV Cell Parameter Estimation Techniques

In this study, a hybrid method for estimation of solar photovoltaic (PV) parameters is developed by integrating existing analytical and numerical methods. The hybrid method estimate the unknown parameters i.e., Photovoltaic current (Ipv), Diode saturation current (Io) and ideality factor (A), consistently, while using different existing analytical or numerical methods to estimate Series resistance (Rs) and Shunt resistance (Rsh), across the three variants of the hybrid method. The study evaluate the impact of different estimation approaches for Rs and Rsh on the accuracy of the overall method. In the proposed hybrid method, the value of Ipv is assumed to be the same as Isc. The value of ideality factor ‘A’ is arbitrarily selected as 1.5 and the value of Io is analytically estimated. The hybrid method is firstly tested by estimating Rs and Rsh using an explicit approach via Lambert W-function. The Lambert W function transforms the non-linear implicit I-V characteristic equation into an explicit form, subsequently solving for Rs and Rsh using the Newton-Raphson method (NRM). Secondly, the hybrid method is tested by estimating Rs and Rsh analytically. Lastly, the parameters Rs and Rsh are iteratively solved by minimizing a function via NRM. The function is obtained using the fact that the difference in maximum measured power and maximum estimated power should be minimum. The three variants of the hybrid method are tested on ‘Grey solar PV cell’, and the results are compared to experimental data to evaluate their effectiveness. The results shows that the hybrid method when uses direct analytical method to estimate Rs and Rsh outperforms the other variant of the hybrid method, providing the lowest values of relative maximum power error (RMPE%), overall model error (OME%), root mean square error (RMSE), and individual absolute error (IAE), i.e., 1.866%, 2.26577%, 0.019721, and 0.13217, respectively.