A probabilistic approach to model based adaptive control for damping of inter-area oscillations

Summary form only given. This paper demonstrates an adaptive control strategy for damping inter-area oscillations in a large power system model employing a probabilistic approach to model based control. The scheme accounts for the uncertain nature of the post-disturbance dynamics of the system for computing the control moves. A number of linearized plant models are considered to represent the system dynamics following the probable contingencies. Conventional observer based state feedback controllers are designed to achieve the desired performance for each of these models. This strategy has been used to design and test a damping controller for a thyristor controlled series compensator (TCSC) device installed in a 16-machine, 68-bus system model. The control scheme worked satisfactorily following possible disturbances without any prior knowledge about the specific post-disturbance dynamics.