Journals / Mathematical and Computational Applications / 2011 / Cilt: 16 - Sayı: 3

Analysis of height affect on average wind speed by ANN

Pages
556–564
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The model accuracy is evaluated by comparing the conventional model results with the actual measured and calculated values.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The power generated by wind turbines depends on several factors.
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Key Findings & Data:Two of them are the wind speed and the tower height of wind turbine.
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Conclusion & Impact:The model accuracy is evaluated by comparing the conventional model results with the actual measured and calculated values.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

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.

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Cite This Article

ATA, R., ÇETİN, N. S. (2011). Analysis of height affect on average wind speed by ANN. Mathematical and Computational Applications, Cilt: 16 - Sayı: 3, 556–564. https://ajindex.com/articles/279890

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