Transfer-learning-based BiLSTM-WGAN Approach for Synthetic Data Generation of Sub-synchronous Oscillations in Wind Farms

Shuang Feng; Zhirui Zhang; Yuhang Zheng; Jiaxing Lei; Yi Tang

doi:10.35833/MPCE.2024.000550

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Transfer-learning-based BiLSTM-WGAN Approach for Synthetic Data Generation of Sub-synchronous Oscillations in Wind Farms

Original Paper | 更新时间：2025-07-30

- Transfer-learning-based BiLSTM-WGAN Approach for Synthetic Data Generation of Sub-synchronous Oscillations in Wind Farms
- “The paper introduces its research progress in the field of power system stability. Experts proposed a novel TL-based WGAN approach for synthetic data generation of SSO in wind farms. This method effectively addresses the issue of data scarcity in training AI models, providing a solution to the limited data availability problem in practical power systems.”
- Journal of Modern Power Systems and Clean Energy Vol. 13, Issue 4, Pages: 1199-1210(2025)
- 作者机构：
  
  Department of Electrical Engineering, Southeast University, Nanjing 210096, China
  School of Software, Southeast University, Suzhou 215123, China
- 作者简介：
  
  Shuang Feng received the B.Sc. degree in electrical engineering from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2012, and the Ph.D. degree in electrical engineering from Southeast University, Nanjing, China, in 2017. She is currently an Associate Professor at the Department of Electrical Engineering, Southeast University. Her research interests include power system stability and control, and application of artificial intelligence in power systems.e-mail: sfeng@seu.edu.cn
  Zhirui Zhang received the B.Sc. degree in electrical engineering from Nanjing University of Science and Technology, Nanjing, China, in 2023. He is currently pursuing the M.S. degree at the Department of Electrical Engineering, Southeast University, Nanjing, China. His research interest includes application of artificial intelligence in power systems.e-mail: zyh19990219@163.com
  Yuhang Zheng received the M.Sc. degree in software engineering from Southeast University, Suzhou, China, in 2023. His research interest includes application of artificial intelligence in power systems.e-mail: 220232952@seu.edu.cn
  Jiaxing Lei received the B.Sc. and Ph.D. degrees in electrical engineering from College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2012 and 2017, respectively. He is currently an Associate Professor at the Department of Electrical Engineering, Southeast University, Nanjing, China. His research interests include precision switching-mode power amplifier, high-performance topology, and control of power converters.e-mail: jxlei@seu.edu.cn
  Yi Tang received the B.S., M.Eng., and Ph.D. degrees in electrical engineering from the Harbin Institute of Technology, Harbin, China, in 2000, 2002, and 2006, respectively. He is currently a Professor with the School of Electrical Engineering, Southeast University, Nanjing, China. His research interests include power system analysis, renewable energy, and application of artificial intelligence in power systems.e-mail: tangyi@seu.edu.cn
- 基金信息：
- DOI：10.35833/MPCE.2024.000550
  CLC：
- Received：26 May 2024，
  
  Revised：2024-10-08，
  
  Accepted：24 December 2024，
  
  Online First：20 January 2025，
  
  Published：15 July 2025
- 稿件说明：
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Feng Shuang,Zhang Zhirui,Zheng Yuhang,et al.Transfer-learning-based BiLSTM-WGAN Approach for Synthetic Data Generation of Sub-synchronous Oscillations in Wind Farms[J].Journal of Modern Power Systems and Clean Energy,2025,13(04):1199-1210.
DOI：

Feng Shuang,Zhang Zhirui,Zheng Yuhang,et al.Transfer-learning-based BiLSTM-WGAN Approach for Synthetic Data Generation of Sub-synchronous Oscillations in Wind Farms[J].Journal of Modern Power Systems and Clean Energy,2025,13(04):1199-1210. DOI： 10.35833/MPCE.2024.000550.

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Transfer-learning-based BiLSTM-WGAN Approach for Synthetic Data Generation of Sub-synchronous Oscillations in Wind Farms

DOI：10.35833/MPCE.2024.000550