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Lookup NU author(s): Professor Vladimir TerzijaORCiD
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
© 2025. The operating point of wind farms changes in a wide range, leading to diverse performances of small-signal stability. The mapping between the stability index and the operating point is complex. It is challenging to quantify the stability region, especially in multiple parameter space. Furthermore, online identification of the stability is necessary since the gird impedance is changing in practical systems. Following the piecewise affine impedance in part I, part II proposes an online method for constructing the high-dimensional stability region of the operating point, thereby filling the gap in this field. Firstly, using the concept of the piecewise affine, the grid impedance is identified with the dynamic mode decomposition method in frequency range partitions. Based on the first-order affine impedance of wind turbine generators and the grid, the nodal admittance matrix is established with high accuracy and efficiency. By solving the zeros of the nodal admittance matrix, the stability margins of the system at different operating points are obtained. Secondly, based on stability margin data at diverse operating points, a k-nearest neighbor support vector machine is proposed to quantify the multi-parameter stability region. The stability region is formed with boundaries of different stability margins. Thirdly, the proposed stability region could help to enlarge the stability margin by regulating the operating point. The grid impedance identification and stability region estimation are instantiated and validated for grid-tied wind farms by numerical simulations and experiments.
Author(s): Luo J, Wang P, Zhao H, Liu Y, Terzija V
Publication type: Article
Publication status: Published
Journal: International Journal of Electrical Power and Energy Systems
Year: 2025
Volume: 169
Print publication date: 01/08/2025
Online publication date: 13/06/2025
Acceptance date: 25/05/2025
Date deposited: 25/06/2025
ISSN (print): 0142-0615
ISSN (electronic): 1879-3517
Publisher: Elsevier Ltd
URL: https://doi.org/10.1016/j.ijepes.2025.110791
DOI: 10.1016/j.ijepes.2025.110791
Data Access Statement: Data will be made available on request.
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