Benjamin L. Francis, Jacob R. Nuttall, M. Transtrum, A. Sarić, A. Stanković
{"title":"Network Reduction in Transient Stability Models using Partial Response Matching","authors":"Benjamin L. Francis, Jacob R. Nuttall, M. Transtrum, A. Sarić, A. Stanković","doi":"10.1109/NAPS46351.2019.9000378","DOIUrl":null,"url":null,"abstract":"We describe a method for simultaneously identifying and reducing dynamic power systems models in the form of differential-algebraic equations. Often, these models are large and complex, containing more parameters than can be identified from the available system measurements. We demonstrate our method on transient stability models, using the IEEE 14-bus test system. Our approach uses techniques of information geometry to remove unidentifiable parameters from the model. We examine the case of a networked system with 58 parameters using full observations throughout the network. We show that greater reduction can be achieved when only partial observations are available, Including reduction of the network itself.","PeriodicalId":175719,"journal":{"name":"2019 North American Power Symposium (NAPS)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 North American Power Symposium (NAPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAPS46351.2019.9000378","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We describe a method for simultaneously identifying and reducing dynamic power systems models in the form of differential-algebraic equations. Often, these models are large and complex, containing more parameters than can be identified from the available system measurements. We demonstrate our method on transient stability models, using the IEEE 14-bus test system. Our approach uses techniques of information geometry to remove unidentifiable parameters from the model. We examine the case of a networked system with 58 parameters using full observations throughout the network. We show that greater reduction can be achieved when only partial observations are available, Including reduction of the network itself.