Wind speed analysis using the Extended Generalized Lindley Distribution
| dc.authorid | 0000-0002-4396-5182 | |
| dc.contributor.author | Kantar, Yeliz Mert | |
| dc.contributor.author | Usta, İlhan | |
| dc.contributor.author | Arık, İbrahim | |
| dc.contributor.author | Yenilmez, İsmail | |
| dc.date.accessioned | 2021-10-12T10:22:18Z | |
| dc.date.available | 2021-10-12T10:22:18Z | |
| dc.date.issued | 2018 | en_US |
| dc.department | Fakülteler, Fen Edebiyat Fakültesi, İstatistik ve Bilgisayar Bilimleri Bölümü | |
| dc.description.abstract | The wind energy potential of a specified region can be estimated using the distribution of wind speed.Thus,finding appropriate wind speed distribution is essential. Weibull distribution (WD) is the mostpopular distribution in wind energy literature. Besides WD, various statistical distributions have beenwidely-used as reference distributions to characterize wind speed. However, it is observed that thesedistributions may not model all wind speed data observed in nature. Thus, many studies on differentdistributions are still being conducted tofind better distributional models for use in wind energy esti-mates. In this study, we introduce for thefirst time the Extended Generalized Lindley distribution (EGLD)as an alternative wind speed distribution. EGLD isflexible enough to accommodate different shapes ofwind speed data and includes other forms of Lindley distribution as special cases. In addition, we test theperformance of EGLD on real wind speed data measured at various regions of Turkey. The results of theanalyses indicate that EGLD is suitable for most of the examined wind speed data cases compared to thewell-known WD, according to goodness-of-fit tests. Therefore, EGLD can be used as an alternative dis-tribution for the assessment of wind energy potential. | en_US |
| dc.identifier.citation | Kantar, Y. M., Usta, I., Arik, I., & Yenilmez, I. (2018). Wind speed analysis using the extended generalized Lindley distribution. Renewable Energy, 118, 1024-1030. | en_US |
| dc.identifier.doi | 10.1016/j.renene.2017.09.053 | |
| dc.identifier.endpage | 1030 | en_US |
| dc.identifier.issn | 0960-1481 | |
| dc.identifier.issn | 1879-0682 | |
| dc.identifier.scopus | 2-s2.0-85030220707 | |
| dc.identifier.scopusOldid | 1-s2.0-S0960148117309084 | |
| dc.identifier.scopusquality | Q1 | |
| dc.identifier.startpage | 1024 | en_US |
| dc.identifier.uri | https://doi.org/10.1016/j.renene.2017.09.053 | |
| dc.identifier.uri | https://hdl.handle.net/11552/2091 | |
| dc.identifier.volume | 118 | en_US |
| dc.identifier.wos | WOS:000423008500091 | |
| dc.identifier.wosquality | Q1 | |
| dc.indekslendigikaynak | Scopus | |
| dc.indekslendigikaynak | WoS | |
| dc.indekslendigikaynak | WoS - Science Citation Index Expanded | |
| dc.institutionauthor | Arık, İbrahim | |
| dc.language.iso | en | |
| dc.publisher | Pergamon-Elsevier Science | en_US |
| dc.relation.ispartof | Renewable Energy | |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.subject | Wind Speed Distribution | en_US |
| dc.subject | Wind Power Estimation | en_US |
| dc.subject | Weibull Distribution | en_US |
| dc.subject | Extended Generalized Lindley Distribution | en_US |
| dc.title | Wind speed analysis using the Extended Generalized Lindley Distribution | |
| dc.type | Article |
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