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
- Transfer-learning-based BiLSTM-WGAN Approach for Synthetic Data Generation of Sub-synchronous Oscillations in Wind Farms
- “本文介绍了其在电力系统稳定性领域的研究进展。专家们提出了一种新的基于TL的WGAN方法，用于风电场SSO的合成数据生成。该方法有效地解决了训练人工智能模型时数据稀缺的问题，为实际电力系统中数据可用性有限的问题提供了一种解决方案。”
- MPCE 2025年13卷第4期页码：1199-1210
- 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：
  
  the National Natural Science Foundation of China(52377084);the Zhishan Young Scholar Program of Southeast University, China(2242024RCB0019)
- DOI：10.35833/MPCE.2024.000550
  中图分类号：
- 收稿：2024-05-26，
  
  修回：2024-10-08，
  
  录用：2024-12-24，
  
  网络首发：2025-01-20，
  
  纸质出版：2025-07-15
- 稿件说明：
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Shuang Feng, Zhirui Zhang, Yuhang Zheng, 等. Transfer-learning-based BiLSTM-WGAN Approach for Synthetic Data Generation of Sub-synchronous Oscillations in Wind Farms[J]. MPCE, 2025,13(4):1199-1210.

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.
Shuang Feng, Zhirui Zhang, Yuhang Zheng, 等. Transfer-learning-based BiLSTM-WGAN Approach for Synthetic Data Generation of Sub-synchronous Oscillations in Wind Farms[J]. MPCE, 2025,13(4):1199-1210. DOI： 10.35833/MPCE.2024.000550.

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

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

DOI：10.35833/MPCE.2024.000550