Detection and Analysis of Electromechanical Oscillation in Power Systems with Low-Sampled Data Using Modal Analysis Methods
Purpose Electromechanical oscillations between interconnected generators are considered a major threat to the secure operation of power systems. Therefore, oscillation monitoring systems in real-time are of critical importance to detect the danger of poorly damped oscillations. For the detection and...
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Published in | Journal of electrical engineering & technology Vol. 15; no. 5; pp. 1999 - 2006 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Singapore
Springer Singapore
01.09.2020
대한전기학회 |
Subjects | |
Online Access | Get full text |
ISSN | 1975-0102 2093-7423 |
DOI | 10.1007/s42835-020-00471-0 |
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Abstract | Purpose
Electromechanical oscillations between interconnected generators are considered a major threat to the secure operation of power systems. Therefore, oscillation monitoring systems in real-time are of critical importance to detect the danger of poorly damped oscillations. For the detection and analysis of the oscillations, high-temporal-resolution measurements are required according to the Nyquist theorem. This paper proposes a novel algorithm for the identification of electromechanical oscillations using low-sampled data such as supervisory control and data acquisition (SCADA) measurements.
Methods
The lack of temporal resolution of the data is compensated by using low-sampled data sets at multiple different locations. At a target location, a high-sampled data-signal can be reconstructed using mode shape information obtained from model-based modal analysis. The variable projection method is then used to detect oscillations and estimate oscillation components including frequency and damping ratio.
Results
Case studies based on practical Korean power systems are presented to evaluate the performance of the proposed method. Simulation results show that the proposed method can detect and identify electromechanical oscillations with low-sampled data. |
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AbstractList | Purpose
Electromechanical oscillations between interconnected generators are considered a major threat to the secure operation of power systems. Therefore, oscillation monitoring systems in real-time are of critical importance to detect the danger of poorly damped oscillations. For the detection and analysis of the oscillations, high-temporal-resolution measurements are required according to the Nyquist theorem. This paper proposes a novel algorithm for the identification of electromechanical oscillations using low-sampled data such as supervisory control and data acquisition (SCADA) measurements.
Methods
The lack of temporal resolution of the data is compensated by using low-sampled data sets at multiple different locations. At a target location, a high-sampled data-signal can be reconstructed using mode shape information obtained from model-based modal analysis. The variable projection method is then used to detect oscillations and estimate oscillation components including frequency and damping ratio.
Results
Case studies based on practical Korean power systems are presented to evaluate the performance of the proposed method. Simulation results show that the proposed method can detect and identify electromechanical oscillations with low-sampled data. Purpose Electromechanical oscillations between interconnected generators are considered a major threat to the secure operation of power systems. Therefore, oscillation monitoring systems in real-time are of critical importance to detect the danger of poorly damped oscillations. For the detection and analysis of the oscillations, high-temporal-resolution measurements are required according to the Nyquist theorem. This paper proposes a novel algorithm for the identifi cation of electromechanical oscillations using low-sampled data such as supervisory control and data acquisition (SCADA) measurements. Methods The lack of temporal resolution of the data is compensated by using low-sampled data sets at multiple diff erent locations. At a target location, a high-sampled data-signal can be reconstructed using mode shape information obtained from model-based modal analysis. The variable projection method is then used to detect oscillations and estimate oscillation components including frequency and damping ratio. Results Case studies based on practical Korean power systems are presented to evaluate the performance of the proposed method. Simulation results show that the proposed method can detect and identify electromechanical oscillations with lowsampled data. KCI Citation Count: 0 |
Author | Kim, Soobae Baek, Jong-Oh |
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Keywords | Electromechanical oscillations Detection and analysis of oscillations Korean power systems Variable projection method Low-sampled data Model-based modal analysis |
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Electromechanical oscillations between interconnected generators are considered a major threat to the secure operation of power systems. Therefore,... Purpose Electromechanical oscillations between interconnected generators are considered a major threat to the secure operation of power systems. Therefore,... |
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Title | Detection and Analysis of Electromechanical Oscillation in Power Systems with Low-Sampled Data Using Modal Analysis Methods |
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