An adaptive neuro-fuzzy inference system approach for prediction of tip speed ratio in wind turbines

Ata R., KOÇYİĞİT Y.

Expert Systems with Applications, cilt.37, sa.7, ss.5454-5460, 2010 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 37 Sayı: 7
  • Basım Tarihi: 2010
  • Doi Numarası: 10.1016/j.eswa.2010.02.068
  • Dergi Adı: Expert Systems with Applications
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.5454-5460
  • Anahtar Kelimeler: Wind turbines, Tip speed ratio, Adaptive neuro-fuzzy inference system (ANFIS), Artificial neural-networks (ANN), Prediction
  • Manisa Celal Bayar Üniversitesi Adresli: Evet

Özet

This paper introduces an adaptive neuro-fuzzy inference system (ANFIS) model to predict the tip speed ratio (TSR) and the power factor of a wind turbine. This model is based on the parameters for LS-1 and NACA4415 profile types with 3 and 4 blades. In model development, profile type, blade number, Schmitz coefficient, end loss, profile type loss, and blade number loss were taken as input variables, while the TSR and power factor were taken as output variables. After a successful learning and training process, the proposed model produced reasonable mean errors. The results indicate that the errors of ANFIS models in predicting TSR and power factor are less than those of the ANN method. © 2010 Elsevier Ltd. All rights reserved.