TY - JOUR
T1 - Ambient data-based online identification and location of frequency oscillations
AU - Cai, Guowei
AU - Xuan, Lei
AU - Sun, Zhenglong
AU - Chao, Jiang
AU - Belikov, Juri
AU - Levron, Yoash
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2024/6
Y1 - 2024/6
N2 - Frequency oscillation results in all units within the system oscillating in the same phase and persistently, leading to significant damage to the system. It is important to remove the threat of frequency oscillation. However, existing methods rely on extracting and localizing oscillation parameters from transient oscillation data, failing to effectively identify potential oscillation risks within the system for proper corrective control. To fill this gap, this paper proposes a method for identifying and localizing frequency oscillations within random environmental data. Firstly, signal processing employs Morlet wavelet filtering to extract electrical quantity data in a single mode. Subsequently, a subspace dynamic mode decomposition algorithm is applied for parameter identification, enabling the detection and warning of weakly damped modes. In order to accurately locate the source of oscillations, a locating index is improved based on the energy flow theory, known as the dissipation area difference ratio, which enables the online evaluation of dissipation energy variation in generators within power systems operating under different modes. Through an arithmetic analysis conducted on both a 16-machine 5-zone system and an actual grid system, the effectiveness and accuracy of the proposed identification and localization method are demonstrated.
AB - Frequency oscillation results in all units within the system oscillating in the same phase and persistently, leading to significant damage to the system. It is important to remove the threat of frequency oscillation. However, existing methods rely on extracting and localizing oscillation parameters from transient oscillation data, failing to effectively identify potential oscillation risks within the system for proper corrective control. To fill this gap, this paper proposes a method for identifying and localizing frequency oscillations within random environmental data. Firstly, signal processing employs Morlet wavelet filtering to extract electrical quantity data in a single mode. Subsequently, a subspace dynamic mode decomposition algorithm is applied for parameter identification, enabling the detection and warning of weakly damped modes. In order to accurately locate the source of oscillations, a locating index is improved based on the energy flow theory, known as the dissipation area difference ratio, which enables the online evaluation of dissipation energy variation in generators within power systems operating under different modes. Through an arithmetic analysis conducted on both a 16-machine 5-zone system and an actual grid system, the effectiveness and accuracy of the proposed identification and localization method are demonstrated.
KW - Energy flow
KW - Frequency oscillation
KW - Morlet wavelet filtering
KW - Random data
KW - SDMD
UR - http://www.scopus.com/inward/record.url?scp=85183940278&partnerID=8YFLogxK
U2 - 10.1016/j.ijepes.2024.109843
DO - 10.1016/j.ijepes.2024.109843
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AN - SCOPUS:85183940278
SN - 0142-0615
VL - 157
JO - International Journal of Electrical Power and Energy Systems
JF - International Journal of Electrical Power and Energy Systems
M1 - 109843
ER -