Excitation prediction control of multi-machine power systems using balanced reduced model

This paper presents a multi-machine power system excitation predictive control method using balanced reduced model. First, The theory of empirical Gramians balanced reduction was used to reduce the orders of power system nonlinear dynamic model to save the computing time of open-loop optimization of model predictive control. Then, it used the minimum deviation of system output(state) and control input as the control objective, using sampling point linearization model of nonlinear reduced model as equality constraint and the change limits of system output and control input as inequality constraint to establish the excitation predictive control model based on reduced model. Next, the interior-point method was used to solve the optimal control problem. Finally, we took advantage of a four-machine power system to verify the effectiveness of the predictive control method, and the simulating results show that excitation predictive control method using balanced reduced model for the multi-machine power systems can greatly shorten the optimization calculating time, meanwhile maintain the voltage of generator terminals within the set points and improve the stability of power system.