TY - JOUR
T1 - Detection and Analysis of Electromechanical Oscillation in Power Systems with Low-Sampled Data Using Modal Analysis Methods
AU - Baek, Jong Oh
AU - Kim, Soobae
N1 - Publisher Copyright:
© 2020, The Korean Institute of Electrical Engineers.
PY - 2020/9/1
Y1 - 2020/9/1
N2 - 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.
AB - 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.
KW - Detection and analysis of oscillations
KW - Electromechanical oscillations
KW - Korean power systems
KW - Low-sampled data
KW - Model-based modal analysis
KW - Variable projection method
UR - http://www.scopus.com/inward/record.url?scp=85086864783&partnerID=8YFLogxK
U2 - 10.1007/s42835-020-00471-0
DO - 10.1007/s42835-020-00471-0
M3 - Article
AN - SCOPUS:85086864783
SN - 1975-0102
VL - 15
SP - 1999
EP - 2006
JO - Journal of Electrical Engineering and Technology
JF - Journal of Electrical Engineering and Technology
IS - 5
ER -