A neural network control strategy for improved energy capture on a variable-speed wind turbine
AF Silva, FA Castro, JN Fidalgo - Proceedings of the 6th WSEAS …, 2005 - dl.acm.org
AF Silva, FA Castro, JN Fidalgo
Proceedings of the 6th WSEAS international conference on Evolutionary computing, 2005•dl.acm.orgPitch control has so far been the dominating method for power control in modern variable
speed wind turbines. This paper proposes an improved control technique for pitching the
blades of a variable speed wind turbine, using Artificial Neural Networks (ANN). The control
objective is decided according the two states of operation: below rated operation and above
rated operation. In the below rated power state, the aim of control is to extract maximum
energy from the wind. In the above rated power, the control design problem is to limit and …
speed wind turbines. This paper proposes an improved control technique for pitching the
blades of a variable speed wind turbine, using Artificial Neural Networks (ANN). The control
objective is decided according the two states of operation: below rated operation and above
rated operation. In the below rated power state, the aim of control is to extract maximum
energy from the wind. In the above rated power, the control design problem is to limit and …
Pitch control has so far been the dominating method for power control in modern variable speed wind turbines. This paper proposes an improved control technique for pitching the blades of a variable speed wind turbine, using Artificial Neural Networks (ANN). The control objective is decided according the two states of operation: below rated operation and above rated operation. In the below rated power state, the aim of control is to extract maximum energy from the wind. In the above rated power, the control design problem is to limit and smooth the output electrical power. A model has been constructed and evaluated with experimental data obtained from Vestas V-47 660 kW wind turbine.
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