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14 October 2021 Modeling and stability analysis of power system with SVC considering harmonic coupling characteristics
Runsheng Xie, Guorong Zhang, Chunpeng Wang
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Proceedings Volume 11930, International Conference on Mechanical Engineering, Measurement Control, and Instrumentation; 1193005 (2021) https://doi.org/10.1117/12.2611617
Event: International Conference on Mechanical Engineering, Measurement Control, and Instrumentation (MEMCI 2021), 2021, Guangzhou, China
Abstract
Aiming at the problems of power quality deterioration and low frequency oscillation in power system caused by the large-scale application of static var compensator (SVC), the existing methods ignore the dynamic coupling characteristics among harmonics in SVC and directly equate SVC to a fundamental frequency linearization model. This assumption fails to reflect the difference of equipment dynamic characteristics with frequency variation. Therefore, a harmonic interaction analysis method between SVC and power grid based on harmonic transfer function matrix is proposed in this paper. The dynamic harmonic domain (DHD) theory is used to construct the whole model of the system with SVC considering the influence of conduction angle and phase-locked loop module, and the corresponding harmonic transfer function matrix of the system is derived from the closed-loop model. Based on the harmonic dynamic transfer function matrix, the eigenvalue method is used to analyze the influence of controller parameters on system stability and to predict the oscillation frequency. MATLAB/Simulink simulation results demonstrate the accuracy of the system DHD model and the correctness of the system stability analysis.
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Runsheng Xie, Guorong Zhang, and Chunpeng Wang "Modeling and stability analysis of power system with SVC considering harmonic coupling characteristics", Proc. SPIE 11930, International Conference on Mechanical Engineering, Measurement Control, and Instrumentation, 1193005 (14 October 2021); https://doi.org/10.1117/12.2611617
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KEYWORDS
Control systems
Simulink
Systems modeling
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