Prediction of wind blowing durations of Eastern Turkey with machine learning for integration of renewable energy and organic farmingstock raising

IŞIK, Ali Hakan; DÜDEN ÖRGEN, Fatma Kadriye; ŞİRİN, Ceylin; TUNCER, Azim Doğuş; GÜNGÖR, Afşin

Prediction of wind blowing durations of Eastern Turkey with machine learning for integration of renewable energy and organic farmingstock raising

Authors

IŞIK, Ali Hakan

DÜDEN ÖRGEN, Fatma Kadriye

ŞİRİN, Ceylin

TUNCER, Azim Doğuş

GÜNGÖR, Afşin

Publisher

Mehmet Akif Ersoy University
Mehmet Akif Ersoy Üniversitesi

Description

Applications whichintegrate wind energy and both agriculture and stock raising are increasinglybecoming popular especially in Europe. Subject applications enable the land tobe utilized in various favorable ways. In this study, by using a 5-year averagewind data referring to Erzurum and Ardahan, two eastern cities of Turkey whichare characterized by prevailingly an extensive cattle-raising, wind-blowingdurations were calculated by Rayleigh distribution. Annual wind blowingdurations for Erzurum and Ardahan ranged between 479.6-5825.7 hours and1643.6-6710.8 hours, respectively. The data obtained was predicted viaartificial neural networks and output results indicate an prediction accuracyat 99% level thereupon. The integration of agricultural and stock raisingactivities with wind energy shall contribute to environmental aspects as wellincreasing the efficiency and effectiveness in the region.