Neural prediction of power factor in wind turbines
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Date
2007
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Abstract
The power generated by wind turbines depends on several factors. One of them is the power factor also known as blade efficiency. In this study, the power factor is predicted using Artificial Neural Networks (ANN) and comparisons made with conventional model approach for the selected turbine profiles mostly used in practice. The study has shown that the prediction of power factors from seven input parameters by ANN yields better results than those of the conventional model.
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Keywords
Artificial intelligence , Backpropagation , Electric generators , Electric power factor , Engines , Forecasting , Hydraulic machinery , Hydraulic motors , Parameter estimation , Turbines , Wind power , Wind turbines , Artificial neural networks (ANN) , Conventional modeling , Input parameters , Neural prediction , Power factor (PF) , Neural networks