Short-term wind power prediction with harmony search algorithm: Belen region
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Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Murat Yakar
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Wind power is the fastest-growing technology among alternative energy production sources. Reliable forecasting of short-term wind power plays a critical role in the acquisition of most of the generated energy. In this study, short-term wind power forecast is performed using radial-based artificial neural networks, forecast error and cost to be minimized with the harmony search algorithm. Experimented results show that, we can predict wind power with fewer features and less error by using harmony search algorithm. A %7 percent improvement in RMSE rate has been achieved with the proposed method for short-term wind power prediction. © Author(s) 2022.
Açıklama
Anahtar Kelimeler
Artificial neural networks, Feature Selection, Renewable Energy, Short-term forecast, Wind power
Kaynak
Turkish Journal of Engineering
WoS Q Değeri
Scopus Q Değeri
Q3
Cilt
6
Sayı
3