AI Summary & Key Takeaways
AI InsightThe obtained results show that the novel method based on Finsler geometry is a better alternative to the two-parameter Weibull and the Rayleigh probability density functions to describe wind speed characteristics.
📌 3 Key Takeaways
Abstract
Determining and modeling the wind speed characteristics of a region are important in terms of constructing the wind energy conversion systems. Several distribution functions such as Finsler geometry, two-parameter Weibull, and Rayleigh are proposed for wind speed modeling in the literature. The modeling performance of Finsler geometry method at high and low speeds was not investigated in the literature, although a model proposal was presented in the studies on Finsler geometry. In addition, there is no comparison in terms of power density. This paper presents the comparative performance analysis of Finsler geometry for modeling the wind speed data. The Finsler geometry method allows accurate modeling and describes the ability for chaotic structures like wind speed data. The two-parameter Weibull, Rayleigh, and Finsler Geometry are used to analyze the wind speed data between October 2015 and September 2016 in Bilecik, Gökçeada, and Bozcaada, which are located in the northwest of Turkey. The obtained results show that the novel method based on Finsler geometry is a better alternative to the two-parameter Weibull and the Rayleigh probability density functions to describe wind speed characteristics.