{"title":"A comparison of placement methods for collecting PMU data used in angular stability detection","authors":"J. López, Chan-nan Lu","doi":"10.1109/ISAP.2017.8071401","DOIUrl":null,"url":null,"abstract":"Phaser Measurement Units (PMUs) enable several online critical applications, such as State Estimation (SE) and stability monitoring enhancement where the dynamic behavior of the electric network is supervised in order to maintain a reliable power supply. However, due to the cost of PMUs, identifying key locations for installation is essential. Several PMU allocation algorithms have been suggested. Two PMU placement formulations for enhancing the instability detection are studied and their performance is assessed. These are the Lyapunov Exponent and the Correlation Matrix based methods. Simulated PMU data obtained from the optimal locations are tested in an intelligent system stability detection framework. Test results on a practical 1646 bus network are presented.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"77 5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISAP.2017.8071401","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
Phaser Measurement Units (PMUs) enable several online critical applications, such as State Estimation (SE) and stability monitoring enhancement where the dynamic behavior of the electric network is supervised in order to maintain a reliable power supply. However, due to the cost of PMUs, identifying key locations for installation is essential. Several PMU allocation algorithms have been suggested. Two PMU placement formulations for enhancing the instability detection are studied and their performance is assessed. These are the Lyapunov Exponent and the Correlation Matrix based methods. Simulated PMU data obtained from the optimal locations are tested in an intelligent system stability detection framework. Test results on a practical 1646 bus network are presented.