A fast multi-step prediction and rolling optimization excitation control method for multi-machine power system

Abstract

Original scientific paper A fast excitation predictive control method for multi-machine power system is presented. The multi-step prediction technique is realized via system dynamic model. Some inequality constraints on states, inputs and outputs are considered in rolling optimization. The Gramian balanced reduction technique and the improved optimization algorithm are used in order to save the time of open-loop optimization in model predictive control. A 50machine power system is used to verify the effectiveness of this approach. Compared with simulated results under different controllers, this method can greatly reduce the calculating-time. The voltages of generator terminals are maintained within the set points. The stability of power system is improved.