电力系统保护与控制2025，Vol.53Issue(3)：81-94,14.DOI:10.19783/j.cnki.pspc.240251
基于短时傅里叶变换和两阶段深度迁移学习的多频段振荡源定位
Multi-frequency band oscillation source location based on STFT and two-stage deep transfer learning
摘要
Abstract
With the large-scale integration of new energy,represented by wind and solar power,into the system and the use of new governors of high-power turbine units,the oscillations in the new power system have expanded from the traditional low frequency oscillation to multi-frequency band oscillation.Accurately locating the oscillation source is a key means to suppress the expansion of adverse effects.Thus a novel location method based on short-time Fourier transform(STFT)and two-stage deep transfer learning is proposed.In this method,the active power measurement signals of all generators are converted into time-frequency representation matrices by STFT processing,and the matrices are transformed into feature images by linear mapping,so that the location problem is transformed into an image classification problem.The feature images are then fed into a ResNet50-based two-stage classifier.The first stage is used to determine the type of oscillation,while the second stage is used to locate the source.Transfer learning integrated with image knowledge learning is adopted to further improve the training efficiency and localization accuracy.Simulation results for the New England system with wind power and the Hubei power grid show that,compared to the support vector machine,decision tree and single-step transfer learning method,the proposed method has higher accuracy and robustness in the presence of noise.关键词
多频段振荡/短时傅里叶变换/特征图像/深度迁移学习/振荡源定位Key words
multi-frequency band oscillation/short-time Fourier transform(STFT)/feature image/deep transfer learning/oscillation source location引用本文复制引用
余明,姚伟,赵一帆,石重托,刘海光,陈汝斯,李大虎,文劲宇..基于短时傅里叶变换和两阶段深度迁移学习的多频段振荡源定位[J].电力系统保护与控制,2025,53(3):81-94,14.基金项目
This work is supported by the Science and Technology Project of the Headquarters of State Grid Corporation of China(No.5100-202099522A-0-0-00). 国家电网公司总部科技项目资助"新一代人工智能技术在未来电网安全分析与决策中的应用"(5100-202099522A-0-0-00) （No.5100-202099522A-0-0-00）
