In this paper, we present a novel evolutionary algorithm-based approach to identification of hydraulic turbine governor system (HTGS). A new variant of particle swarm optimization (PSO) technique named unified PSO (UPSO) is employed and improved to search for optimal parameters of HTGS by minimizing errors between the model's evaluated outputs and the actual ones. The performance of the improved unified PSO (IUPSO) is compared with standard PSO and UPSO algorithms tested via numerical simulation. Identification results aptly show that the IUPSO algorithm has the advantage of convergence capability and solution quality and it provides a new way for parameter identification of hydraulic turbine governor system.