电机与控制应用2024，Vol.51Issue(7)：119-130,后插1,13.DOI:10.12177/emca.2024.059
基于STFT图像和迁移学习的次同步振荡源定位方法
Localization Method for Sub-Synchronous Oscillation Sources Based on STFT Images and Transfer Learning
摘要
Abstract
Sub-synchronous oscillations induced by the interaction between direct-drive wind turbines and the grid pose a serious threat to the safe and stable operation of the power grid.To rapidly identify the triggering unit,a localization method for sub-synchronous oscillation source based on short-time Fourier transform(STFT)images and transfer learning is proposed.Firstly,compressive sensing technology is employed to transform output data into observation signals,and then the STFT is performed on the observation signals to obtain the mapping image with oscillation characteristics,and the link between the mapping image and the oscillation source unit is constructed.Secondly,an adversarial transfer learning architecture is utilized in conjunction with the power system to achieve rapid generalization of unlabeled oscillation data in the target domain.Finally,the traditional transfer learning method is introduced for comparison,the results show that the proposed method performs better in terms of localization accuracy and efficiency,and has strong noise resistance.关键词
次同步振荡源/短时傅里叶变换/压缩感知/映射图/迁移学习Key words
sub-synchronous oscillation source/short-time Fourier transform/compressive sensing/mapping image/transfer learning分类
信息技术与安全科学引用本文复制引用
刘志坚,黄建,骆军..基于STFT图像和迁移学习的次同步振荡源定位方法[J].电机与控制应用,2024,51(7):119-130,后插1,13.基金项目
国家重点研发计划项目(2022YFB2703500)National Key Research and Development Program of China(2022YFB2703500) （2022YFB2703500）
