Neural network based power system transient stability criterion using DSP-PC system

Transient stability assessment plays an important role in power systems. The transient stability deals with the electromechanical oscillation of synchronous generators, created by a disturbance in the power system. For example, in the case of a transmission line fault, assume that faulted line section is first isolated and then reclosed (reclosure); there then exists a threshold parameter known as the stable critical clearing time (CCT). This paper describes a neural network based adaptive pattern recognition approach for estimation of the critical clearing time. Numerical examples are presented to illustrate this approach. In the neural network considered in this research work, a multi DSP-PC system (digital signal processor-personal computer system) is used for realizing faster backpropagation by applying pipeline operation and parallel operation.