This paper presents a hybrid method to extract the five unknown parameters of a single-diode photo-voltaic (PV) model. The proposed method is a combination of analytical and optimization algorithms such that only two parameters, namely, series (R-s) and shunt resistance (R-sh), are estimated by using metaheuristic algorithms. The information of three major key points in datasheets provided by manufacturers is used for optimization and the sum of the squared error formulated. The rest of the unknown parameters, diode ideality factor (D), photo-generated current (I-ph), and dark saturation current (I-0) are obtained analytically. In order to predict the behavior of real performance characteristics of solar PV modules under different environmental conditions, a set of translational formulas have been used. Finally, performance indices, such as PV characteristics, absolute error in current, normalized root mean square error (nRMSE), maximum power, and relative maximum power error are estimated for six different types of PV modules from different technology to reveal the effectiveness of the proposed method. Through comparison with experimental data available in modules datasheet and existing method, it was found that the proposed method is sufficiently accurate. (C) 2020 Elsevier Ltd. All rights reserved.