{"title":"基于蒙特卡罗模拟和逻辑回归分类器的复合系统充分性评估","authors":"Sangit Poudel, Nava Raj Karki","doi":"10.1109/ODICON50556.2021.9429000","DOIUrl":null,"url":null,"abstract":"This paper presents a new method that combines Logistic Regression Classifier (LRC) and Monte Carlo Simulation (MCS) to evaluate the adequacy of a composite power system. LRC is used to pre-classify the system states as failure or success based on training data set provided by conventional MCS itself, but with a relaxed error tolerance level. The proposed method is applied to the IEEE Reliability test system (IEEE-RTS-79) to calculate the annualized and annual indices.The results thus obtained are compared with that of conventional MCS. In different cases, the simulation results provide a significant improvement in computational burden and indices calculation time while maintaining resonable accuracy.","PeriodicalId":197132,"journal":{"name":"2021 1st Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology(ODICON)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Composite System Adequacy Assessment Using Monte Carlo Simulation and Logistic Regression Classifier\",\"authors\":\"Sangit Poudel, Nava Raj Karki\",\"doi\":\"10.1109/ODICON50556.2021.9429000\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a new method that combines Logistic Regression Classifier (LRC) and Monte Carlo Simulation (MCS) to evaluate the adequacy of a composite power system. LRC is used to pre-classify the system states as failure or success based on training data set provided by conventional MCS itself, but with a relaxed error tolerance level. The proposed method is applied to the IEEE Reliability test system (IEEE-RTS-79) to calculate the annualized and annual indices.The results thus obtained are compared with that of conventional MCS. In different cases, the simulation results provide a significant improvement in computational burden and indices calculation time while maintaining resonable accuracy.\",\"PeriodicalId\":197132,\"journal\":{\"name\":\"2021 1st Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology(ODICON)\",\"volume\":\"54 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 1st Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology(ODICON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ODICON50556.2021.9429000\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 1st Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology(ODICON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ODICON50556.2021.9429000","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Composite System Adequacy Assessment Using Monte Carlo Simulation and Logistic Regression Classifier
This paper presents a new method that combines Logistic Regression Classifier (LRC) and Monte Carlo Simulation (MCS) to evaluate the adequacy of a composite power system. LRC is used to pre-classify the system states as failure or success based on training data set provided by conventional MCS itself, but with a relaxed error tolerance level. The proposed method is applied to the IEEE Reliability test system (IEEE-RTS-79) to calculate the annualized and annual indices.The results thus obtained are compared with that of conventional MCS. In different cases, the simulation results provide a significant improvement in computational burden and indices calculation time while maintaining resonable accuracy.