An improved dynamic mode decomposition for real-time electromechanical oscillation monitoring in power systems: The impact of ultra-low frequency modes and its removal strategy

Abstract

The growing complexity of power systems, driven by the increasing use of renewable energy sources, necessitates efficient real-time monitoring of electromechanical oscillations, which is crucial for enhancing grid security. Dynamic Mode Decomposition (DMD) is a promising data-driven method for addressing this challenge of monitoring the electromechanical oscillations, made possible by power system digitalization. However, DMD implementation faces unresolved issues, including the impact of ultra-low-frequency modes (ULFM) on accuracy due to trends caused by their excitation. While larger data windows can mitigate this, they slow down oscillation estimation. ULFM characteristics remain poorly studied. This study conducts a comprehensive ULFM analysis and proposes a solution by combining DMD with a high-pass filter to counter ULFM's adverse effects on accuracy. This allows for a reduction in DMD's window size, significantly improving computational efficiency. Simulations on three test systems demonstrate that the enhanced DMD offers faster computation and superior accuracy compared to the traditional DMD method.