Governor Parameter Estimation Considering Upper/Lower Production Limits

Turbine-governor is one of the key elements in the dynamic performance of electric power systems. The accurate modeling of turbine-governor has great importance in analyzing the transient behavior of power systems. This paper proposes a hybrid method combining Particle Swarm Optimization (PSO) and Sensitivity Analysis (SA) for dynamic parameter identification of turbine-governor model in multi-machine power systems. The proposed method utilizes the frequency and turbine powers responses following some events. In each event, to recognize the validity of the estimated parameters, sensitivity analysis technique is applied. Also, considering the results of the sensitivity analysis, the impact of type and magnitude of events and also upper/lower production limits on estimation of the parameters are investigated. Finally, the accuracy of the estimated parameters are verified through a different event. The proposed methodology is applied to the IEEE 9-bus system and the results demonstrate the feasibility and practicality of this approach.