Adaptive decision fusion based framework for short-term wind speed and turbulence intensity forecasting: case study for North West of Turkey

Authors

ÇİĞDEM DİNÇKAL
BEHÇET UĞUR TÖREYİN
SERHAT KÜÇÜKALİ

DOI

10.3906/elk-1404-367

Abstract

In this paper, an online learning framework called adaptive decision fusion (ADF) is employed for short-term wind speed and turbulence intensity forecasting by use of wind speed data for each season for the city of İzmit, located in the northwest of Turkey. Fixed-weight (FW) linear combination is derived and used for comparison with ADF. Wind speeds and turbulence intensities are predicted from the existing wind speed data and computed turbulence intensities, respectively, using the ADF and FW methods. Simulations are carried out for each season and the results are tested on mean absolute percentage error criterion. It is shown that the proposed model captured the system dynamic behavior and made accurate predictions based on the seasonal wind speed characteristics of the site. The procedure described here can be used to estimate the local velocity and turbulence intensity in a wind power plant during a storm.

Keywords

Wind speed, turbulence intensity, adaptive decision fusion, fixed weight linear combination, mean absolute percentage error

First Page

2770

Last Page

2783

Recommended Citation

DİNÇKAL, ÇİĞDEM; TÖREYİN, BEHÇET UĞUR; and KÜÇÜKALİ, SERHAT (2017) "Adaptive decision fusion based framework for short-term wind speed and turbulence intensity forecasting: case study for North West of Turkey," Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 25: No. 4, Article 19. https://doi.org/10.3906/elk-1404-367
Available at: https://journals.tubitak.gov.tr/elektrik/vol25/iss4/19