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Math. Comput. Appl. 2011, 16(3), 556-564; doi:10.3390/mca16030556

Analysis of Height Affect on Average Wind Speed by ANN

1
Celal Bayar University, Electrical Engineering Department, 45140, Muradiye, Manisa, Turkey
2
Ege University, Solar Energy Enstitute, Bornova, Izmir, Turkey
*
Author to whom correspondence should be addressed.
Published: 1 December 2011
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Abstract

The power generated by wind turbines depends on several factors. Two of them are the wind speed and the tower height of wind turbine. In this study, the annual average wind speed based on the tower height is predicted using Artificial Neural Networks (ANN) and comparisons made with conventional model approach. The backpropagation multi layer ANNs were used to estimate annual average wind speed for three locations in Turkey. The Model has been developed with the help of neural network methodology. It involves four input variables-wind speed of measured location, desired height on measured location, height above ground level of measured location and Hellmann coefficient and one output variables-annual average wind speed. The model accuracy is evaluated by comparing the conventional model results with the actual measured and calculated values.
Keywords: Artificial neural networks; Average wind speed forecasting; Hellmann coefficient Artificial neural networks; Average wind speed forecasting; Hellmann coefficient
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Ata, R.; Çetin, N.S. Analysis of Height Affect on Average Wind Speed by ANN. Math. Comput. Appl. 2011, 16, 556-564.

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Math. Comput. Appl. EISSN 2297-8747 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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