An Oscillation Monitoring System for Real-time Detection of Small-Signal Instability in Large Electric Power Systems

Quintero, José Melchor Medina; Liu, Shuai; Venkatasubramanian, V.

doi:10.1109/pes.2007.385822

Cited by 18 publications

(8 citation statements)

References 22 publications

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“…Thambirajah et al [5] summarised different techniques used to assess the said stability under the two operating modes. The major area of interest in this study is the ring‐down condition, which has been analysed using linear techniques, such as Prony [6], Kalman filter [7], Hankel total least squares [8], matrix pencil [9], Steiglitz‐Mcbride and eigensystem realisation [10] algorithms. Furthermore, the algorithms based on the Hilbert–Huang transformation [11], and the Teager–Kaiser energy operator [12] do not use linear approximations to determine the mode parameters in the ring‐down oscillations.…”

Section: Introductionmentioning

confidence: 99%

Identification of dominant low‐frequency modes in ring‐down oscillations using multiple Prony models

Wadduwage

Annakkage

Narendra³

2015

IET Generation, Transmission & Distribution

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This study presents a simple approach to modify the Prony algorithm to extract dominant low-frequency modes present in ring-down oscillations in power systems. The proposed approach is based on the observation that true modes present in the ring-down oscillations appear consistently, irrespective of the order of the Prony model. It is shown that the consistently appearing modes can be extracted using a sorting method. The improved Prony algorithm which has the feature of extracting only the true modes present in the input signal is utilised to propose an oscillation monitoring algorithm in this study. The suitability of the proposed oscillation monitoring algorithm for real-time monitoring of lowfrequency inter-area oscillations is demonstrated using synthetic signals and simulated signals of different test systems.

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Section: Introductionmentioning

confidence: 99%

Identification of dominant low‐frequency modes in ring‐down oscillations using multiple Prony models

Wadduwage

Annakkage

Narendra³

2015

IET Generation, Transmission & Distribution

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“…We consider a 4-area partitioning of the network. The attack occurs at t 0 = 0, and by t f = 20 sec enough data has been recorded to capture the 2 The lines typically connecting buses 4 and 5 and buses 16 and 17 has been removed to improve the coherency of the areas. slow oscillatory modes of the network.…”

Section: B Ieee 39-bus Systemmentioning

confidence: 99%

“…This overhaul includes the deployment of wide-area measurement systems consisting of hundreds of new phasor measurement units (PMUs), which are capable of streaming geo-synchronized dynamic measurements via Ethernet connections in near real-time, effectively creating the backbone of a cyber layer on top of the physical model of the power grid [1]. In the current state-of-the-art, PMU data are primarily used for offline postmortem analysis of disturbance events including oscillation monitoring [2], voltage stability monitoring, and phasor-based state estimation [3], [4], in addition to recent developments in closed-loop control [5]. However, a very limited amount of research has evaluated how synchrophasors, beyond analyzing offline disturbance events, can also be used for online detection, and, more importantly, localization of faults and malicious attacks.…”

Section: Introductionmentioning

confidence: 99%

A Real-Time Attack Localization Algorithm for Large Power System Networks Using Graph-Theoretic Techniques

Nudell

Nabavi

Chakrabortty

2015

IEEE Trans. Smart Grid

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We develop a graph-theoretic algorithm for localizing the physical manifestation of attacks or disturbances in large power system networks using real-time synchrophasor measurements. We assume the attack enters through the electromechanical swing dynamics of the synchronous generators in the grid as an unknown additive disturbance. Considering the grid to be divided into coherent areas, we pose the problem as to localize which area the attack may have entered using relevant information extracted from the phasor measurement data. Our approach to solve this problem consists of three main steps. We first run a phasor-based model reduction algorithm by which a dynamic equivalent of the clustered network can be identified in real-time. Second, in parallel, we run a system identification in each area to identify a transfer matrix model for the full-order power system. Thereafter, we exploit the underlying graph-theoretic properties of the identified reduced-order topology, create a set of localization keys, and compare these keys with a selected set of transfer function residues. We validate our results using a detailed case study of the two-area Kundur model and the IEEE 39-bus power system.

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“…With a large number of synchrophasors being deployed, it is possible to construct power system model based purely on real-time synchrophasor measurements, which also can make online power system instability awareness feasible. Studies have been done with the measurement data for the system instability assessment [5][6][7][8][9][10][11]. Some focus on using real-time phasor measurements with pre-existing knowledge obtained from computer simulation results or historical events to enable real-time assessment under disturbance conditions [8,9].…”

Section: Introductionmentioning

confidence: 99%

“…Some focus on using real-time phasor measurements with pre-existing knowledge obtained from computer simulation results or historical events to enable real-time assessment under disturbance conditions [8,9]. Some use selected realtime measurement locations to directly compute energy functions for the potential of instability [10,11]. An adaptive power system equivalent method for real-time estimation of stability margin using phase-plane trajectories was proposed in [7].…”

Section: Introductionmentioning

confidence: 99%

A measurement-based approach for power system instability early warning

Bai

Liu

et al. 2016

Prot Control Mod Power Syst

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Early warning of impending instability in a power system under disturbance conditions is important for preventing of system collapse. A measurement-based approach is proposed to assess the potential power system transient instability problem under cascading outages. Where a measurement-based index is obtained as the estimation accuracy of a linear autoregressive exogenous (ARX) model to estimate the dynamic response of the power system and indicate the system stability to some extent after a disturbance. The proposed approach was verified using a set of marginally stable cases in a 179-bus WECC equivalent power system. Then the instability early warning threshold for this system is obtained as 0.44.

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An Oscillation Monitoring System for Real-time Detection of Small-Signal Instability in Large Electric Power Systems

Cited by 18 publications

References 22 publications

Identification of dominant low‐frequency modes in ring‐down oscillations using multiple Prony models

Identification of dominant low‐frequency modes in ring‐down oscillations using multiple Prony models

A Real-Time Attack Localization Algorithm for Large Power System Networks Using Graph-Theoretic Techniques

A measurement-based approach for power system instability early warning

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