Model predictive control stabilization of a power system including a wind power plant

Abstract

The conventional generators are equipped with power system stabilizers (PSS) to damp oscillations that follow disturbances. The inclusion of renewable energy sources within the existing power systems requires further investigations to enhance the performance of PSS. Several control strategies have been being used to design the PSS. In this paper, model predictive control (MPC) is investigated to be used as a PSS. It uses numerical optimization algorithms to get an optimal control output considering the system’s constraints. Therefore, It is designed and applied to a multi-machine power system with a wind power plant (WPP). Three disturbances are used to test the controllers including three-phase fault, transmission line outage, and voltage reference sudden change. MATLAB/SIMULINK is used in the simulation. Then, the results are compared to conventional multi-band controller (MB) and linear quadratic regulator (LQR). MPC shows efficient performance in handling the constraints and damping types of oscillations with the existence of the WPP in the case of partial power-sharing.

Keywords

• Linear quadratic regulator
• Model predictive control
• Power system stabilizer
• State feedback control
• Wind power plant

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