F. E. Reyes, M. G. Juarez, A. Zamora, J. Ortiz, J. C. Silva, M. Paternina, C. Toledo-Santos
{"title":"实时执行线性铃响分析方法,以识别优势模式","authors":"F. E. Reyes, M. G. Juarez, A. Zamora, J. Ortiz, J. C. Silva, M. Paternina, C. Toledo-Santos","doi":"10.1109/SGSMA51733.2022.9806011","DOIUrl":null,"url":null,"abstract":"This paper specializes in the real-time execution of three mature linear ringdown analysis methods for modal identification in power systems. Data-based identification methods such as Prony’s method, eigensystem realization algorithm, and matrix pencil are embedded into a Matlab & Simulink-powered real-time simulation environment. Their implementations are achieved by using a sliding window approach, are profited by the inherent features of a parallel computing software architecture, reduce the computational complexity of the methods through shorttime windows length, and provide instantaneous modal information (damping and frequency). These enhancements make part of a user-friendly tool to effectively deal with the modal identification issue. This tool is successfully tested using two test power systems: the two-area Kundur system and a reduced-order representation of the New England power grid. Its effectiveness and performance are demonstrated with the attained results and its validation.","PeriodicalId":256954,"journal":{"name":"2022 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Real-time execution of linear ringdown analysis methods for identifying dominant modes\",\"authors\":\"F. E. Reyes, M. G. Juarez, A. Zamora, J. Ortiz, J. C. Silva, M. Paternina, C. Toledo-Santos\",\"doi\":\"10.1109/SGSMA51733.2022.9806011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper specializes in the real-time execution of three mature linear ringdown analysis methods for modal identification in power systems. Data-based identification methods such as Prony’s method, eigensystem realization algorithm, and matrix pencil are embedded into a Matlab & Simulink-powered real-time simulation environment. Their implementations are achieved by using a sliding window approach, are profited by the inherent features of a parallel computing software architecture, reduce the computational complexity of the methods through shorttime windows length, and provide instantaneous modal information (damping and frequency). These enhancements make part of a user-friendly tool to effectively deal with the modal identification issue. This tool is successfully tested using two test power systems: the two-area Kundur system and a reduced-order representation of the New England power grid. Its effectiveness and performance are demonstrated with the attained results and its validation.\",\"PeriodicalId\":256954,\"journal\":{\"name\":\"2022 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA)\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SGSMA51733.2022.9806011\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SGSMA51733.2022.9806011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real-time execution of linear ringdown analysis methods for identifying dominant modes
This paper specializes in the real-time execution of three mature linear ringdown analysis methods for modal identification in power systems. Data-based identification methods such as Prony’s method, eigensystem realization algorithm, and matrix pencil are embedded into a Matlab & Simulink-powered real-time simulation environment. Their implementations are achieved by using a sliding window approach, are profited by the inherent features of a parallel computing software architecture, reduce the computational complexity of the methods through shorttime windows length, and provide instantaneous modal information (damping and frequency). These enhancements make part of a user-friendly tool to effectively deal with the modal identification issue. This tool is successfully tested using two test power systems: the two-area Kundur system and a reduced-order representation of the New England power grid. Its effectiveness and performance are demonstrated with the attained results and its validation.