Abstract: In order to improve the identification accuracy of single-diode model parameters for photovoltaic（PV） modules, a linear least squares algorithm for parameter identification is proposed by the linearization of current-voltage（I-V） characteristics of PV modules using the differential conductance information. The effectiveness of the algorithm is validated through indoor test data of the Photowatt-PWP 201 module, and the result shows that the algorithm has a higher accuracy than the existing typical algorithms such as special function method, Laplace transform method, and teaching and learning meta-heuristic method. Furthermore, the robustness of the algorithm is validated through continuous outdoor test data of the aSiMicro03036 module, and the result indicates that the PV parameters can be identified quickly and accurately under various irradiance and temperature conditions.