Short-term wind power prediction with harmony search algorithm: Belen region

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Tarih

2022

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

Künye