A Review on Neural Network Models for Wind Speed Prediction. Issue 2 (April 2013)

• Record Type: Journal Article
• Authors: Sheela, K. Gnana; Deepa, S.N.
• Is Part Of: Wind engineering. Volume 37:Issue 2(2013)
• Page Start: 111
• Page End: 123
• Publication Date: 2013-04
• Subjects: Wind speed prediction -- Neural Network Models -- Back propagation algorithm -- Radial Basis Function -- Recurrent network; Wind-pressure -- Periodicals; Winds -- Periodicals; Wind power -- Periodicals; Engineering meteorology -- Periodicals; Pression du vent; Vents; Énergie éolienne; Météorologie appliquée; Engineering meteorology; Wind power; Wind-pressure; Winds; Periodicals; 621.4505
• DOI: 10.1260/0309-524X.37.2.111
• Languages: English
• ISSNs: 0309-524X

Abstract

This paper presents review of neural network models for wind speed prediction during the past 15 years. Wind energy is one of renewable energy system with lowest cost of electricity production. The prediction of wind speed is recognized as a major contribution of wind farm. Wind speed prediction has many applications in Military, Air traffic control and Ship navigation etc. The prediction of wind speed depends on meteorological variables such as pressure, temperature, humidity and rainfall etc. The aim is to identify the importance, advantages and comparison of different neural network models of wind speed prediction. This review is to be useful for researchers working in this field and identify performance of neural network models. It is very helpful to the wind farm owners to understand the current wind prediction model capabilities and give an idea which model will be suitable for predicting the wind speed at their wind farms.