Localization method of subsynchronous oscillation source based on high-resolution time-frequency distribution image and CNN

作     者：Hui Liu Yundan Cheng Yanhui Xu Guanqun Sun Rusi Chen Xiaodong Yu Hui Liu;Yundan Cheng;Yanhui Xu;Guanqun Sun;Rusi Chen;Xiaodong Yu

作者机构：Institute of Electric Power SystemsSchool of Electrical and Electronic EngineeringNorth China Electric Power UniversityBeijing 102206P.R.China Electric Power Research Institute of State Grid Hubei Electric Power Co.Ltd.Wuhan 430077P.R.China Central China Branch of State Grid Corporation of ChinaWuhan 430077P.R.China 

出 版 物：《Global Energy Interconnection》 (全球能源互联网（英文版）)

年 卷 期：2024年第7卷第1期

页      面：1-13页

核心收录：

学科分类：0820[工学-石油与天然气工程] 0808[工学-电气工程] 080802[工学-电力系统及其自动化] 08[工学] 081104[工学-模式识别与智能系统] 080203[工学-机械设计及理论] 0802[工学-机械工程] 0811[工学-控制科学与工程] 

基　　金：supported by the Science and Technology Project of State Grid Corporation of China(5100202199536A-0-5-ZN)。 

主　　题：Subsynchronous oscillation source localization Synchronous squeezing transform Enhanced short-time Fourier transform Convolutional neural networks 

摘      要：The penetration of new energy sources such as wind power is increasing,which consequently increases the occurrence rate of subsynchronous oscillation events.However,existing subsynchronous oscillation source-identification methods primarily analyze fixed-mode oscillations and rarely consider time-varying features,such as frequency drift,caused by the random volatility of wind farms when oscillations occur.This paper proposes a subsynchronous oscillation sourcelocalization method that involves an enhanced short-time Fourier transform and a convolutional neural network(CNN).First,an enhanced STFT is performed to secure high-resolution time-frequency distribution(TFD)images from the measured data of the generation unit ports.Next,these TFD images are amalgamated to form a subsynchronous oscillation feature map that serves as input to the CNN to train the localization model.Ultimately,the trained CNN model realizes the online localization of subsynchronous oscillation sources.The effectiveness and accuracy of the proposed method are validated via multimachine system models simulating forced and natural oscillation events using the Power Systems Computer Aided Design platform.Test results show that the proposed method can localize subsynchronous oscillation sources online while considering unpredictable fluctuations in wind farms,thus providing a foundation for oscillation suppression in practical engineering scenarios.