Artificial NARX Neural Network Model of Wind Speed: Case of Istanbul-Avcilar

Calik H., Ak N., Guney I.

JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, cilt.16, sa.5, ss.2553-2560, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 16 Sayı: 5
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1007/s42835-021-00763-z
  • Dergi Adı: JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC
  • Sayfa Sayıları: ss.2553-2560
  • Anahtar Kelimeler: Effect size, NARX, Neural network, Time series prediction, Wind speed estimation
  • İstanbul Üniversitesi Adresli: Hayır

Özet

Wind farms have a focus role in environmentally friendly energy production. There are short-term estimates of wind speed in planning energy production in wind power plants. In this article, we analyzed the wind speed in the Istanbul Avcilar region by an artificial neural network method (ANN) and regression method. One of the methods commonly used in estimation processes is Nonlinear Autoregressive Exogenous (NARX). We divide the data into three parts 70%, 15%, and 15%, respectively, for learning, validation, and testing. We used the Levenberg-Marquardt (LM) algorithm for data network training. We compared the predicted wind speed with the measured and tested values. We used MATLAB software in the analysis of the model. We obtained system outputs and regression models of wind speed with artificial neural network simulations. Besides, we calculated the effect sizes.