Modal Energy Trending for Ringdown Analysis in Power Systems Using Synchrophasors

Accurate on-line estimation of power systems oscillatory modes is important for dealing with complex interactions of large interconnected power systems especially in light of growing number of wind farms with complex power electronics controls. This paper describes an automatic ringdown analysis algorithm for extracting dominant oscillatory modes in power system responses from multiple synchronized Phasor Measurement Unit (PMU) measurements. The proposed approach estimates the system modes by tracking and analyzing the trend of modal oscillation energy seen in the Power Spectrum Density (PSD) of the measured ringdown response. Singular Value Decomposition of Power Spectrum Density matrix as in Frequency Domain Decomposition (FDD) algorithm is used to get overall energy measures for each dominant mode from multiple PMU signals in the ringdown response. This method is useful for real-time oscillation detection and analysis. The combination of frequency domain analysis and SVD enable the method to be robust under noisy conditions. The method is tested with simulation data as well as real power system archived data, and is shown to accurately extract multiple oscillatory modes and their mode shapes from system measurements.