{"title":"多区域系统LOLP置信限的评价","authors":"Suhartono, Y. Zika, S. Sasaki","doi":"10.1109/DRPT.2000.855732","DOIUrl":null,"url":null,"abstract":"Since the forced outage rates (FOR) of generating plants is actually uncertain, LOLP must be a random variable. This paper presents an effective simulation method for calculating the value of LOLP of a multi area system by considering uncertainties both on FOR and load forecasting. There are no exact values of LOLP in a random system, and therefore one has to evaluate its confidence interval. The interval estimate of LOLP gives the upper and lower values of LOLP, so that the LOLP lies between these limits with a specified probability. These upper and lower values of LOLP may be interpreted to be confidence limits on the expected value of LOLP. The simulation results were tested by statistical goodness-of-fit tests and the gamma distribution was found to provide a good fit to the data produced by the Monte Carlo simulations for the sample system.","PeriodicalId":127287,"journal":{"name":"DRPT2000. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Proceedings (Cat. No.00EX382)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"The evaluation of confidence limit on LOLP for multi area system\",\"authors\":\"Suhartono, Y. Zika, S. Sasaki\",\"doi\":\"10.1109/DRPT.2000.855732\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Since the forced outage rates (FOR) of generating plants is actually uncertain, LOLP must be a random variable. This paper presents an effective simulation method for calculating the value of LOLP of a multi area system by considering uncertainties both on FOR and load forecasting. There are no exact values of LOLP in a random system, and therefore one has to evaluate its confidence interval. The interval estimate of LOLP gives the upper and lower values of LOLP, so that the LOLP lies between these limits with a specified probability. These upper and lower values of LOLP may be interpreted to be confidence limits on the expected value of LOLP. The simulation results were tested by statistical goodness-of-fit tests and the gamma distribution was found to provide a good fit to the data produced by the Monte Carlo simulations for the sample system.\",\"PeriodicalId\":127287,\"journal\":{\"name\":\"DRPT2000. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Proceedings (Cat. No.00EX382)\",\"volume\":\"77 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"DRPT2000. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Proceedings (Cat. No.00EX382)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DRPT.2000.855732\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"DRPT2000. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Proceedings (Cat. No.00EX382)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DRPT.2000.855732","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The evaluation of confidence limit on LOLP for multi area system
Since the forced outage rates (FOR) of generating plants is actually uncertain, LOLP must be a random variable. This paper presents an effective simulation method for calculating the value of LOLP of a multi area system by considering uncertainties both on FOR and load forecasting. There are no exact values of LOLP in a random system, and therefore one has to evaluate its confidence interval. The interval estimate of LOLP gives the upper and lower values of LOLP, so that the LOLP lies between these limits with a specified probability. These upper and lower values of LOLP may be interpreted to be confidence limits on the expected value of LOLP. The simulation results were tested by statistical goodness-of-fit tests and the gamma distribution was found to provide a good fit to the data produced by the Monte Carlo simulations for the sample system.
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