Decentralized nonlinear model predictive control of a multimachine power system

Abstract

This paper proposes a novel decentralized nonlinear model predictive control approach for excitation control in multimachine power systems. A key feature of the proposed approach is the reduction of the multimachine control problem to multiple single-machine control problems. These reduced size control problems only require direct measurements from individual generators, thereby making implementation simple in practice. The effectiveness of the proposed approach is demonstrated through computer simulations on a one small-size Western System Coordinating Council (WSCC) and one large-size New England power system under a wide range of operating conditions. The performance of the proposed approach is evaluated in terms of damping power system oscillations, critical time enhancement, and control signal energy consumption. The results are compared with those obtained using power system stabilizer and feedback linearization based control schemes and found to be impressive.