{"title":"Lyapunov exponents over variable window sizes for prediction of rotor angle stability","authors":"Haosen Guo, Chen-Ching Liu, Guanqun Wang","doi":"10.1109/NAPS.2014.6965398","DOIUrl":null,"url":null,"abstract":"A PMU-based method using Maximal Lyapunov Exponent (MLE) to determine the stability of a system following a disturbance has been established in previous research. This paper proposes a new method to determine the proper time window of MLE in an on-line environment. Spectral analysis is applied to the oscillation waveforms to calculate the variable window size of MLE. Two MLEs are calculated using the same window size but at different initial times. The consistency of the two MLEs indicates that sufficient information has been included in the first time window to characterize the system dynamics. Otherwise, the window size needs to be adapted for the operating condition. This method increases the accuracy of prediction given by MLE. A case study using a 200-bus system is presented to validate the feasibility of the proposed method.","PeriodicalId":421766,"journal":{"name":"2014 North American Power Symposium (NAPS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 North American Power Symposium (NAPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAPS.2014.6965398","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
A PMU-based method using Maximal Lyapunov Exponent (MLE) to determine the stability of a system following a disturbance has been established in previous research. This paper proposes a new method to determine the proper time window of MLE in an on-line environment. Spectral analysis is applied to the oscillation waveforms to calculate the variable window size of MLE. Two MLEs are calculated using the same window size but at different initial times. The consistency of the two MLEs indicates that sufficient information has been included in the first time window to characterize the system dynamics. Otherwise, the window size needs to be adapted for the operating condition. This method increases the accuracy of prediction given by MLE. A case study using a 200-bus system is presented to validate the feasibility of the proposed method.