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Journals / Istanbul University Journal of Electrical and Electronics Engineering / 2007 / Cilt: 7 - Sayı: 2

Neural prediction of power factor in wind turbines

Numan Sabit CETIN
Rasit ATA
Pages
431–438
Publication Date
2022-10-18
DOI
—
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AI Summary & Key Takeaways

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

The study has shown that the prediction of power factors from seveninput parameters by ANN yields better results than those of the conventional model.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The power generated by wind turbines depends on several factors.
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Key Findings & Data:One of them is the power factoralso known as blade efficiency.
💡
Conclusion & Impact:The study has shown that the prediction of power factors from seveninput parameters by ANN yields better results than those of the conventional model.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

The power generated by wind turbines depends on several factors. One of them is the power factoralso known as blade efficiency. In this study, the power factor is predicted using Artificial NeuralNetworks (ANN) and comparisons made with conventional model approach for the selected turbineprofiles mostly used in practice. The study has shown that the prediction of power factors from seveninput parameters by ANN yields better results than those of the conventional model.

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Cite This Article

CETIN, N. S., ATA, R. (2022). Neural prediction of power factor in wind turbines. Istanbul University Journal of Electrical and Electronics Engineering, Cilt: 7 - Sayı: 2, 431–438. https://ajindex.com/articles/543774

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References (12)

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