ESTONIAN ACADEMY
PUBLISHERS
eesti teaduste
akadeemia kirjastus
PUBLISHED
SINCE 1952
 
Proceeding cover
proceedings
of the estonian academy of sciences
ISSN 1736-7530 (Electronic)
ISSN 1736-6046 (Print)
Impact Factor (2022): 0.9
A novel information geometry method for estimating parameters of the Weibull wind speed distribution; pp. 39–49
PDF | https://doi.org/10.3176/proc.2018.1.01

Authors
Mehmet Kurban, Emrah Dokur, Salim Ceyhan
Abstract

Accurate modelling of wind speed is very important for the assessment of the wind energy potential of a region. The two-parameter Weibull distribution is widely used to model wind speed. Many different numerical methods can be used to estimate the shape and scale parameters of the Weibull distribution function. This paper proposes the estimation of parameters based on a novel approach, the Information Geometry Method (IGM). Non-Euclidean geometry and the Riemannian metric called the Fisher metric or the information metric are used in this approach. Differential equations derived from the Fisher information matrix are solved for the Weibull statistical manifold by the shooting method. The IGM is compared with the graphical method, maximum likelihood method, method of Lysen, method of Justus, and power density method. In particular, it is shown that this approach has a better performance than the other estimation methods according to the power density results for the periods of three years from 2012 to 2014 for Bilecik, a city of Turkey. Therefore, the IGM as a new approach used for the estimation of parameters of the Weibull distribution function can be a good alternative for the assessment of the wind energy potential.

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