Author/Authors :
ATA, Raşit Celal Bayar Üniversitesi - Mühendislik Fakültesi - Elektrik-Elektronik Mühendisliği Bölümü, Turkey
Title Of Article :
NEURAL PREDICTION OF WIND BLOWING DURATIONS BASED ON AVERAGE WIND SPEEDS FOR AKHISAR LOCATION
Abstract :
Renewable energy resources are widely preferred over conventional resources as they are environmentally favorable. Wind energy is one of the important renewable energy resources and has been widely developed recently. The energy produced from wind is dependent upon several factors. One of them is average wind speed and the other is wind blowing period. In this study, the wind blowing period is estimated based on annual average wind speed, Hellman coefficient and tower height using artificial neural networks (ANN). The results of ANN are compared with a conventional method in which Rayleigh distribution is employed.
NaturalLanguageKeyword :
Wind energy , Wind blowing time , Hellmann coefficient , Artificial neural networks
JournalTitle :
Pamukkale University Journal Of Engineering Sciences
