An Oscillation Monitoring System for Real-time Detection of Small-Signal Instability in Large Electr

An Oscillation Monitoring System for Real-time Detection of Small-Signal Instability in Large Electr

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Unformatted text preview: Abstract This paper proposes a real-time oscillation monitoring system for detecting the emergence of small-signal instability related events in large electric power systems. The oscillation monitoring system has been developed as a fully autonomous expert system for real-time extraction of modal information from the wide-area PMU measurements during the progress of power system disturbance events. The oscillation analysis uses three different algorithms, namely, the classical multiple-input Prony algorithm, the matrix Pencil algorithm as well as the recent Hankel total least square method. These algorithms were primarily used for off-line manual analysis of power system oscillations in the past. In our research, a specific set of rules has been designed to automate the modal analysis of oscillations by using the three algorithms above without any human intervention during the analysis. The monitor will thus issue operator alerts or control triggers whenever the damping levels of the electromechanical modes of oscillation go below preset thresholds. I. INTRODUCTION N modern day power systems, the power-flows across distant portions of the transmission network have been growing steadily to accommodate growing consumer demands. Moreover, owing to deregulation, the power transfers have also become somewhat unpredictable as dictated by market price fluctuations. As a result, the system operation can find itself close to or outside the secure operating limits under severe contingencies. Recent occurrences of large-scale blackouts all over the world reinforce the significance of developing safety net type control mechanisms, which are specifically designed to Support of this work from a) Power Systems Engineering Research Center (PSERC), b) Consortium for Electric Reliability Technology Solutions (CERTS), and c) Bonneville Power Adminsitration (BPA) is gratefully acknowledged. Jaime Quinteros doctoral research was partially funded by the Colciencias-Fulbright-Laspau program. Jaime Quintero is an Associate Professor at Universidad Autonoma de Occidente, Cali, Colombia (jquintero@uao.edu.co). Guoping Liu is a Ph.D. student in the School of Electrical Engineering and Computer Science (EECS) at Washington State University, Pullman, WA (gliu@eecs.wsu.edu). Vaithianathan Mani Venkatasubramanian is a Professor in the School of EECS at Washington State University, Pullman, WA (mani@eecs.wsu.edu). handle such unforeseen operating conditions, [1], [2], [3]. The controller is motivated towards preventing oscillatory instability events such as the August 10, 1996 western blackout that was caused by the negative damping of the 0.25 Hz western interarea mode [4], [5]. Such oscillatory instability events typically take a minimum of four to five swings of growing oscillations before the oscillations become large enough to lead to system separation. Therefore, for such small-signal instability related events, there does exist sufficient time for an automatic controller to detect the event and to take...
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This note was uploaded on 01/29/2011 for the course ENGR 52 taught by Professor Mcmillan during the Spring '10 term at Baylor Med.

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An Oscillation Monitoring System for Real-time Detection of Small-Signal Instability in Large Electr

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