Journal
ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS
Volume 45, Issue 1, Pages 2453-2470Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/15567036.2019.1663309
Keywords
Wind energy; maximum likelihood; wind speed distributions; model selection criteria; exponentiated Weibull
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The determination of wind speed characteristics is crucial for estimating wind power output. This study compares the fitting performances of different statistical distributions as alternatives to the commonly used Weibull distribution in different wind regimes encountered in nature.
The determination of wind speed characteristics is extremely important for estimating the wind power output. In this context, Weibull distribution is one of the most commonly used statistical distributions for modeling wind speed. However, despite its widespread usage, it may not be accurate for modeling all wind regimes. For this reason, alternative distributions are utilized for modeling wind speed data. In this study, we use Rayleigh, Inverse Weibull (IW), Burr Type III, Extreme Value (EV), Gamma, Inverse Gamma (IG), Marshall-Olkin extended Lindley (MOEL), generalized Extreme Value (GEV) and exponentiated Weibull (EW) distributions as alternatives to Weibull. Our aim is to determine the distribution which provides the best fit for different wind regimes encountered in nature. In the application part, data sets are taken from stations located on Turkey's Aegean coast and the fitting performances of the above-mentioned distributions are compared. In order to determine the appropriate wind speed distributions. Different model selection criteria are utilized.
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