{"title":"Time-Delay Correlation Analysis of Wide-Area PMU Control Signals in Complex Communication Scenarios","authors":"Jianbo Yi, Zhendong Liu, Zhenyuan Zhang, Jian Li, Qi Huang","doi":"10.1109/ICPS51807.2021.9416638","DOIUrl":null,"url":null,"abstract":"Power system wide-area measurement and control signals based on phasor measurement unit (PMU) may exist in complex communication scenarios. This makes the problems of time delay, packet loss, noise and control signal distortion caused by chaotic time series. This paper presents a novel prediction compensation structure, which combines the signal hierarchical filtering method with gray prediction algorithm. First, utilize complete ensemble empirical decomposition with adaptive noise (CEEMDAN) method to decompose the PMU measurement signal into components with different frequency scales and use WOLF method to determine the chaotic characteristics of each frequency band component. Second, based on the analysis results of singular spectrum analysis (SSA), after removing the weak correlation information and noise corresponding to small singular values, reconstruct the known chaotic components. Third, add the components of each frequency scale predicted by gray Verhulst prediction method to get the final control input signal without time delay interference. Finally, the paper takes 5 communication scenarios to analyze that the proposed compensation scheme has a good compensation effect under different delays and packet loss.","PeriodicalId":350508,"journal":{"name":"2021 IEEE/IAS 57th Industrial and Commercial Power Systems Technical Conference (I&CPS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE/IAS 57th Industrial and Commercial Power Systems Technical Conference (I&CPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPS51807.2021.9416638","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Power system wide-area measurement and control signals based on phasor measurement unit (PMU) may exist in complex communication scenarios. This makes the problems of time delay, packet loss, noise and control signal distortion caused by chaotic time series. This paper presents a novel prediction compensation structure, which combines the signal hierarchical filtering method with gray prediction algorithm. First, utilize complete ensemble empirical decomposition with adaptive noise (CEEMDAN) method to decompose the PMU measurement signal into components with different frequency scales and use WOLF method to determine the chaotic characteristics of each frequency band component. Second, based on the analysis results of singular spectrum analysis (SSA), after removing the weak correlation information and noise corresponding to small singular values, reconstruct the known chaotic components. Third, add the components of each frequency scale predicted by gray Verhulst prediction method to get the final control input signal without time delay interference. Finally, the paper takes 5 communication scenarios to analyze that the proposed compensation scheme has a good compensation effect under different delays and packet loss.