Sub‐Synchronous Oscillation Suppression Strategy for DFIG Based on Morris‐EFAST Global Sensitivity Analysis and Multi‐Parameter Co‐Optimisation

ABSTRACT With the growing share of wind power generation in the global energy structure, sub‐synchronous oscillations (SSOs) triggered by the integration of wind power into the grid, as a potential dynamic instability phenomenon, have a non‐negligible impact on the performance and safety of the power system and even lead to serious operational risks. Starting from the operation mechanism of the doubly‐fed induction generator (DFIG) and in combination with the control of the rotor‐side converter (RSC), an equivalent impedance model of the DFIG is constructed. Employing the Morris method and the extended Fourier amplitude sensitivity test (EFAST) method, a comprehensive global sensitivity analysis of the system impedance is conducted, progressing from qualitative to quantitative analysis. High‐sensitivity parameters are identified, and the system dynamic interval is partitioned through the joint adjustment among these parameters. Subsequently, a cooperative optimisation method for high‐sensitivity parameters is proposed to optimise the parameter set within the instability region to effectively suppress SSO. Finally, the simulation model of the DFIG grid‐connected system with series compensation is established, and the feasibility of the optimisation method is verified using the Middlebrook criterion. The results demonstrate that the optimisation method exhibits strong adaptability under different operating conditions, effectively mitigating the risk of SSOs and ensuring stable operation of the wind power system.

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Publication Details

Journal
IET Electric Power Applications
Published
2025-01-01
DOI
https://doi.org/10.1049/elp2.70051
Citations
1
Primary Topic
Power System Optimization and Stability
Type
article
Field-Weighted Citation Impact
0.73

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article

Sub‐Synchronous Oscillation Suppression Strategy for DFIG Based on Morris‐EFAST Global Sensitivity Analysis and Multi‐Parameter Co‐Optimisation

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IET Electric Power Applications
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article

Sub‐Synchronous Oscillation Suppression Strategy for DFIG Based on Morris‐EFAST Global Sensitivity Analysis and Multi‐Parameter Co‐Optimisation

Linlin Yu, Yihua Zhang, Lei Huang, Junyi Wang, G. Meng, Haitao Liu
article en
1 citations

Abstract

ABSTRACT With the growing share of wind power generation in the global energy structure, sub‐synchronous oscillations (SSOs) triggered by the integration of wind power into the grid, as a potential dynamic instability phenomenon, have a non‐negligible impact on the performance and safety of the power system and even lead to serious operational risks. Starting from the operation mechanism of the doubly‐fed induction generator (DFIG) and in combination with the control of the rotor‐side converter (RSC), an equivalent impedance model of the DFIG is constructed. Employing the Morris method and the extended Fourier amplitude sensitivity test (EFAST) method, a comprehensive global sensitivity analysis of the system impedance is conducted, progressing from qualitative to quantitative analysis. High‐sensitivity parameters are identified, and the system dynamic interval is partitioned through the joint adjustment among these parameters. Subsequently, a cooperative optimisation method for high‐sensitivity parameters is proposed to optimise the parameter set within the instability region to effectively suppress SSO. Finally, the simulation model of the DFIG grid‐connected system with series compensation is established, and the feasibility of the optimisation method is verified using the Middlebrook criterion. The results demonstrate that the optimisation method exhibits strong adaptability under different operating conditions, effectively mitigating the risk of SSOs and ensuring stable operation of the wind power system.

IET Electric Power ApplicationsVol. 19(1)
State Grid Corporation of China (China) (CN), Nanjing Institute of Technology (CN), Southeast University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 28%
Power System Optimization and Stability
0.73
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