Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/54369
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dc.contributor.authorJirakom Sirisrisakulchaien_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.date.accessioned2018-09-04T10:12:31Z-
dc.date.available2018-09-04T10:12:31Z-
dc.date.issued2015-01-01en_US
dc.identifier.issn03029743en_US
dc.identifier.other2-s2.0-84958550330en_US
dc.identifier.other10.1007/978-3-319-25135-6_43en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84958550330&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/54369-
dc.description.abstract© Springer International Publishing Switzerland 2015. Modeling of daily peak electricity demand is very crucial for reliability and security assessments of electricity suppliers as well as of electricity regulators. The aim of this paper is to model the peak electricity demand using the dynamic Peak-Over-Threshold approach. This approach uses the vector of covariates including time variable for modeling extremes. The effect of temperature and time dependence on shape and scale parameters of Generalized Pareto distribution for peak electricity demand is investigated and discussed in this article. Finally, the conditional return levels are computed for risk management.en_US
dc.subjectComputer Scienceen_US
dc.subjectMathematicsen_US
dc.titleModeling daily peak electricity demand in Thailanden_US
dc.typeConference Proceedingen_US
article.title.sourcetitleLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)en_US
article.volume9376en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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