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

Year 2019, Volume: 2 Issue: 3, 47 - 53, 30.09.2019

Ali Hakan Işık , Fatma Kadriye Düden Örgen Ceylin Şirin , Azim Doğuş Tuncer , Afşin Güngör

Abstract

Applications which
integrate wind energy and both agriculture and stock raising are increasingly
becoming popular especially in Europe. Subject applications enable the land to
be utilized in various favorable ways. In this study, by using a 5-year average
wind data referring to Erzurum and Ardahan, two eastern cities of Turkey which
are characterized by prevailingly an extensive cattle-raising, wind-blowing
durations were calculated by Rayleigh distribution. Annual wind blowing
durations for Erzurum and Ardahan ranged between 479.6-5825.7 hours and
1643.6-6710.8 hours, respectively. The data obtained was predicted via
artificial neural networks and output results indicate an prediction accuracy
at 99% level thereupon. The integration of agricultural and stock raising
activities with wind energy shall contribute to environmental aspects as well
increasing the efficiency and effectiveness in the region.

Keywords

Wind energy prediction, wind blowing duration, artificial neural networks, machine learning, organic farming, stock raising

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