{"title":"Flexibility Assessment Tool by Failure-based Uncertainty Management in Power Systems","authors":"Gokturk Poyrazoglu, Ugur Dolu","doi":"10.1109/ISGTEurope.2019.8905676","DOIUrl":null,"url":null,"abstract":"Flexibility in power systems operations is the capability to operate the system under secure conditions even after a sudden change in the system conditions. One of the sudden change may be considered as the failure of components in any power plants and the resultant loss of energy supply. This study provides a framework to manage the uncertainty associated with failures by evaluating the historical failure data. A novel empirical weighting methodology is presented consists of a supervised machine learning and probability techniques and a real dataset of Turkey's power systems is used to demonstrate the success of the developed flexibility assessment tool to manage the near future uncertainty on the supply side of the system.","PeriodicalId":305933,"journal":{"name":"2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISGTEurope.2019.8905676","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
Flexibility in power systems operations is the capability to operate the system under secure conditions even after a sudden change in the system conditions. One of the sudden change may be considered as the failure of components in any power plants and the resultant loss of energy supply. This study provides a framework to manage the uncertainty associated with failures by evaluating the historical failure data. A novel empirical weighting methodology is presented consists of a supervised machine learning and probability techniques and a real dataset of Turkey's power systems is used to demonstrate the success of the developed flexibility assessment tool to manage the near future uncertainty on the supply side of the system.