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Artificial neural network-based maximum power point tracking control for variable speed wind energy conversion systems | IEEE Conference Publication | IEEE Xplore

Artificial neural network-based maximum power point tracking control for variable speed wind energy conversion systems


Abstract:

A new maximum power point tracking (MPPT) controller using artificial neural networks (ANN) for variable speed wind energy conversion system (WECS) is proposed. The algor...Show More

Abstract:

A new maximum power point tracking (MPPT) controller using artificial neural networks (ANN) for variable speed wind energy conversion system (WECS) is proposed. The algorithm uses Jordan recurrent ANN and is trained online using back propagation. The inputs to the networks are the instantaneous output power, maximum output power, rotor speed and wind speed, and the output is the rotor speed command signal for the WECS. The network output after a time step delay is used as the feed-back signal completing the Jordan recurrent ANN. Simulation is carried out in order to verify the performance of the proposed algorithm.
Date of Conference: 08-10 July 2009
Date Added to IEEE Xplore: 09 October 2009
ISBN Information:
Print ISSN: 1085-1992
Conference Location: St. Petersburg, Russia

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