Statistics and Probability Theory in Renewable Energy: Teaching and Research

dc.authorid DEVRIM, YILSER/0000-0001-8430-0702
dc.authorscopusid 8203625300
dc.authorscopusid 6602407267
dc.authorscopusid 11139445500
dc.authorwosid DEVRIM, YILSER/AAF-8790-2019
dc.contributor.author Eryilmaz, Serkan
dc.contributor.author Kateri, Maria
dc.contributor.author Devrim, Yilser
dc.contributor.other Industrial Engineering
dc.contributor.other Energy Systems Engineering
dc.date.accessioned 2024-07-05T15:22:19Z
dc.date.available 2024-07-05T15:22:19Z
dc.date.issued 2023
dc.department Atılım University en_US
dc.department-temp [Eryilmaz, Serkan] Atilim Univ, Dept Ind Engn, Ankara, Turkiye; [Kateri, Maria] Rhein Westfal TH Aachen, Inst Stat, Aachen, Germany; [Devrim, Yilser] Atilim Univ, Dept Energy Syst Engn, Ankara, Turkiye en_US
dc.description DEVRIM, YILSER/0000-0001-8430-0702 en_US
dc.description.abstract In this paper, the key-role and utility of statistics and probability theory in the field of renewable energy are emphasized and illustrated via specific examples. It is demonstrated that renewable energy is a very suitable field to effectively teach and implement many statistical and probabilistic concepts and techniques. From a research point of view, statistical and probabilistic methods have been successfully employed in evaluating renewable energy systems. These methods will continue to be of core interest for the renewable energy sector in the future, as new and more complex renewable energy systems are developed and installed. In this context, some future research directions in relation to the evaluation of renewable energy systems are also presented. en_US
dc.identifier.citationcount 0
dc.identifier.doi 10.1002/asmb.2782
dc.identifier.endpage 729 en_US
dc.identifier.issn 1524-1904
dc.identifier.issn 1526-4025
dc.identifier.issue 5 en_US
dc.identifier.scopus 2-s2.0-85161602712
dc.identifier.scopusquality Q3
dc.identifier.startpage 720 en_US
dc.identifier.uri https://doi.org/10.1002/asmb.2782
dc.identifier.uri https://hdl.handle.net/20.500.14411/2182
dc.identifier.volume 39 en_US
dc.identifier.wos WOS:001001332000001
dc.identifier.wosquality Q3
dc.institutionauthor Eryılmaz, Serkan
dc.institutionauthor Devrim, Yılser
dc.language.iso en en_US
dc.publisher Wiley en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 3
dc.subject Markov chains en_US
dc.subject reliability en_US
dc.subject renewable energy en_US
dc.subject stochastic modeling en_US
dc.subject stochastic processes en_US
dc.subject Weibull distribution en_US
dc.title Statistics and Probability Theory in Renewable Energy: Teaching and Research en_US
dc.type Article en_US
dc.wos.citedbyCount 2
dspace.entity.type Publication
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