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Hydraulic turbine generating unit plays an important role in power system. An accurate hydraulic turbine governor system model is essential to analyze its stability and dynamic performance. In order to identify the parameters of the hydraulic turbine governor system model, a new approach of Bacterial Foraging Optimization Algorithm (BFOA) is introduced in this study. To improve the precision of the identification process, a modified objective function is proposed based on the measurement of gate opening, mechanical torque and generator speed from a simulated model. The improved objective function (IOF) and the conventional objective function (COF) are used in the identification and two sets of parameters are derived and compared. The results show that BFOA is effective in identification of hydraulic turbine governor system and parameters derived from the modified objective function have a higher accuracy.