Regional Inertia Estimation of Power Systems Using Empirical Mode Decomposition and Frequency Response Analysis

This paper presents a PMU-data-based methodology for estimating regional inertia constants in power systems during the initial transient period following a disturbance. The power system is partitioned into dynamically coherent regions based on frequency signals from all monitored buses. Empirical Mode Decomposition (EMD) is applied to each nodal frequency signal to extract Intrinsic Mode Functions (IMFs), and the dominant IMF is identified through an energy ratio criterion. Pairwise correlation analysis of these dominant IMFs is then used to group buses with similar dynamic behavior, forming coherent regions. Within each region, the active power imbalance is computed from Phasor Measurement Units (PMU)-measured tie-line power deviations, while the rate of change of frequency (RoCoF) is estimated from residual trends of EMD-processed frequency signals. These residuals are shown to accurately follow the center of inertia (CoI) frequency trajectory, allowing precise CoI RoCoF estimation. To improve robustness against noise and oscillatory distortions, an adaptive Least Mean Squares (LMS) filter is applied. The regional inertia constants are subsequently estimated using an adapted swing equation during the initial transient period. The method is validated on the IEEE 39-bus test system, yielding estimation errors below 3% relative to reference values, demonstrating its effectiveness for inertia monitoring in low-inertia systems.