Abstract:
Inter-area oscillations provide a considerable risk to the stability of interconnected
power networks, as they involve generators from many regions, potentially resulting
in intensified oscillations in tie-lines. The prompt and efficient suppression of these
oscillations—preferably within 15 seconds—is essential for the secure functioning of
contemporary power networks. Traditional control methods may fail to provide uniform
performance under diverse operating conditions, underscoring the necessity for
sophisticated estimation and control strategies. In this research, a novel approach
combining subspace identification methods, specifically the N4SID and MOESP algorithms,
with a Linear Quadratic Regulator (LQR) controller is proposed to address
the challenge of inter-area oscillations. Subspace identification methods, known for
their ability to extract accurate state-space models directly from input-output data,
enable efficient and robust estimation of the power system’s dynamic behavior under
diverse post-disturbance scenarios. By leveraging the LQR controller, optimal control
efforts are achieved, ensuring rapid damping of oscillations and enhanced system stability.
The proposed framework eliminates the need for manual re-tuning of controller
parameters and demonstrates superior performance in both computational efficiency
and control effectiveness compared to traditional methods. Simulation results validate
the efficacy of this combined approach, offering a reliable and computationally efficient
solution for inter-area oscillation damping in interconnected power systems.
