Small signal stability problems are one of the major threats to grid stability and reliability. Prony analysis has been successfully applied on ringdown data to monitor electromechanical modes of a power system using phasor measurement unit (PMU) data. To facilitate an on-line application of mode estimation, this paper develops a recursive algorithm for implementing Prony analysis and propose an oscillation detection method to detect ringdown data in real time. By automatically detecting ringdown data, the proposed method helps to guarantee that Prony analysis is properly and timely applied on the ringdown data. Thus, the mode estimation results can be performed reliably and timely. The proposed method is tested using Monte Carlo simulations based on a 17-machine model and is shown to be able to properly identify the oscillation data for on-line application of Prony analysis.

10aAA07-00110aAARD10aAutomatic Switchable Network (ASN)10agrid reliability10aphasor measurement units (PMUs)10apower system monitoring1 aZhou, Ning1 aHuang, Zhenyu1 aTuffner, Francis, K.1 aPierre, John, W.1 aJin, Shuangshuang uhttps://certs.lbl.gov/publications/automatic-implementation-prony02086nas a2200253 4500008003900000022001400039245005800053210005800111260001200169300001400181490000700195520135600202653001301558653000901571653003901580653000901619100002101628700001501649700002501664700002001689700002001709700002901729856007401758 2010 d a0885-895000aProbing Signal Design for Power System Identification0 aProbing Signal Design for Power System Identification c05/2010 a835 - 8430 v253 aThis paper investigates the design of effective input signals for low-level probing of power systems. In 2005, 2006, and 2008 the Western Electricity Coordinating Council (WECC) conducted four large-scale system-wide tests of the western interconnected power system where probing signals were injected by modulating the control signal at the Celilo end of the Pacific DC intertie. A major objective of these tests is the accurate estimation of the inter-area electromechanical modes. A key aspect of any such test is the design of an effective probing signal that leads to measured outputs rich in information about the modes. This paper specifically studies low-level probing signal design for power-system identification. The paper describes the design methodology and the advantages of this new probing signal which was successfully applied during these tests. This probing input is a multi-sine signal with its frequency content focused in the range of the inter-area modes. The period of the signal is over 2 min providing high-frequency resolution. Up to 15 cycles of the signal are injected resulting in a processing gain of 15. The resulting system response is studied in the time and frequency domains. Because of the new probing signal characteristics, these results show significant improvement in the output SNR compared to previous tests.10aAA07-00110aAARD10aAutomatic Switchable Network (ASN)10aWECC1 aPierre, John, W.1 aZhou, Ning1 aTuffner, Francis, K.1 aHauer, John, F.1 aTrudnowski, Dan1 aMittelstadt, William, A. uhttps://certs.lbl.gov/publications/probing-signal-design-power-system01776nas a2200241 4500008003900000020002200039245010900061210006900170260003500239300001000274520096800284653001301252653000901265653003901274653003601313653002601349100001501375700001801390700001701408700002001425700002101445856006801466 2009 d a978-1-4244-4241-600aElectromechanical mode shape estimation based on transfer function identification using PMU measurements0 aElectromechanical mode shape estimation based on transfer functi aCalgary, CanadabIEEEc07/2009 a1 - 73 aPower system mode shapes are a key indication of how dynamic components participate in low-frequency oscillations. Traditionally, mode shapes are calculated from a linearized dynamic model. For large-scale power systems, obtaining accurate dynamic models is very difficult. Therefore, measurement-based mode shape estimation methods have certain advantages, especially for the application of real-time small signal stability monitoring. In this paper, a measurement-based mode shape identification method is proposed. The general relationship between transfer function (TF) and mode shape is derived. As an example, a least square (LS) method is implemented to estimate mode shape using an autoregressive exogenous (ARX) model. The performance of the proposed method is evaluated by Monte-Carlo studies using simulation data from a 17-machine model. The results indicate the validity of the proposed method in estimating mode shapes with reasonably good accuracy.10aAA07-00110aAARD10aAutomatic Switchable Network (ASN)10aphasor measurement units (PMUs)10aPower system modeling1 aZhou, Ning1 aHuang, Zhenyu1 aDosiek, Luke1 aTrudnowski, Dan1 aPierre, John, W. uhttps://certs.lbl.gov/publications/electromechanical-mode-shape