Wind speed analysis using the Extended Generalized Lindley Distribution


MERT KANTAR Y., USTA İ., Arik I., YENİLMEZ İ.

RENEWABLE ENERGY, cilt.118, ss.1024-1030, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 118
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1016/j.renene.2017.09.053
  • Dergi Adı: RENEWABLE ENERGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1024-1030
  • Anahtar Kelimeler: Wind speed distribution, Wind power estimation, Extended Generalized Lindley distribution, Weibull distribution, PROBABILITY-DISTRIBUTIONS, WEIBULL DISTRIBUTION, DISTRIBUTION MODELS, ENERGY, PARAMETERS
  • Anadolu Üniversitesi Adresli: Evet

Özet

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 most popular distribution in wind energy literature. Besides WD, various statistical distributions have been widely-used as reference distributions to characterize wind speed. However, it is observed that these distributions may not model all wind speed data observed in nature. Thus, many studies on different distributions are still being conducted to find better distributional models for use in wind energy estimates. In this study, we introduce for the first time the Extended Generalized Lindley distribution (EGLD) as an alternative wind speed distribution. EGLD is flexible enough to accommodate different shapes of wind speed data and includes other forms of Lindley distribution as special cases. In addition, we test the performance of EGLD on real wind speed data measured at various regions of Turkey. The results of the analyses indicate that EGLD is suitable for most of the examined wind speed data cases compared to the well-known WD, according to goodness-of-fit tests. Therefore, EGLD can be used as an alternative distribution for the assessment of wind energy potential. (C) 2017 Elsevier Ltd. All rights reserved.