Decomposition of Electromagnetic Torque in the Detailed Transient Model of Synchronous Machines

Analysis of the classical model of power systems has revealed the importance of damping torque in determining the transient stability region. However, when a detailed model is employed, damping torque is seen to be hardly decomposed from electromagnetic torque. In this case, the reduced model tends to take on an empirical damping coefficient, such as 1 to 3, without sufficient reasons. Moreover, the expression of the electromagnetic torque is usually replaced by electric power. Thereby a large deviation of a rotor’s velocity during the transient process of a generator will inevitably induce a biased expression of the torque. In this paper, the electromagnetic torque is separated into synchronising torque and damping torque by a torque decomposer in the frame of a radial basis function neural network. Its effectiveness is verified by analysis on a singlemachine infinite-bus system. Then, it is used to analyse the influences of a generator’s parameters upon the damping torque. It is shown that the stator resistance will non-linearly worsen the system’s damping. Also, the influence of damping winding’s reactance upon system damping is so small that it can be ignored, and the contribution of its resistance to the system’s damping is obvious while its relationship is non-linear.