Journal
INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS
Volume 32, Issue 4, Pages -Publisher
WILEY
DOI: 10.1002/jnm.2267
Keywords
NeuCube; spiking neural network; wind; wind power forecasting; wind power plant
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In this paper, a spiking neural network-based architecture for the prediction of wind farm energy production is proposed. The model is also able to evaluate the wake effects due to interactions between the elements of a wind farm on the energy production of the whole farm. This method has been applied to a large wind power plant, composed of 28 turbines and 3 anemometric towers, located in the rural area of Vizzini's municipality in province of Catania, Italy, that is characterised by a complex orography and an extension of 30 km(2). For the implementation of this architecture it was used the NeuCube simulator. The results show that the presented method can be successfully applied for predictions of wind energy generation in real wind farm also in presence of faults.
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