Multidimensional frequency domain ringdown analysis for power systems using synchrophasors

Zaid Tashman

Wide-area implementations of synchrophasors enable real-time monitoring of power system dynamic responses during disturbances. These disturbances generally excite oscillatory modes of the system which can become problematic if the modes are either poorly damped or negatively damped. In light of the growing number of integrated wind farms with complex power electronics controls, dealing with the complex interactions of large interconnected power systems is becoming more challenging than ever. Therefore, an accurate on-line estimation of power systems oscillatory modes is important for power system operation. In this thesis, we introduce two new real-time monitoring algorithms for extracting power system oscillatory modes from a system response seen by multiple system-wide distributed phasor measurements units. The Multidimensional Fourier Ringdown Analyzer, or MFRA, uses Fourier analysis to extract dominant oscillatory modes from multiple synchrophasor measurements in real-time. The use of least square fitting in the proposed MFRA does not only give an accurate estimation of the damping ratio of the system oscillatory modes, but also provides a measure for detecting bad data and outlier signals. The proposed method is shown to be robust under noisy conditions iv by testing with simulation data as well as real system data, and is able to extract multiple problematic oscillatory modes computationally fast. The Modal Energy Trending for Ringdown Analyzer, or METRA, 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. The combination of frequency domain analysis and SVD enables the method to be robust under noisy conditions and makes it suitable for real-time oscillation detection and analysis. Both methods were tested with simulation data as well as real power system archived data, and are shown to accurately extract multiple oscillatory modes and their mode shapes from system measurements.

Multidimensional frequency domain ringdown analysis for power systems using synchrophasors

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