Maximum Wind Energy Extraction by Using Neural Network Estimation and Predictive Control of Boost Converter

Mahdi Heidari


This paper proposes a new method to extract maximum energy from wind turbine systems. The artificial neural network (ANN) is used to estimate the wind speed based on the rotor speed and the output power. In addition to ANN, a predictive controller is used to maximize the efficiency of the boost converter. The method has been developed and analyzed by utilizing a turbine directly driven permanent-magnet synchronous generator (PMSG). The simulation results verify the performance of the proposed method. Results show that this method maximizes wind energy extraction with more accuracy and fastness.


Boost converter; Neural network; Pmsg; Predictive controller; Wind turbine

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IAES International Journal of Robotics and Automation (IJRA)
ISSN 2089-4856, e-ISSN 2722-2586
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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