Towards the evolution of novel vertical-axis wind turbines

Preen, R. and Bull, L. (2013) Towards the evolution of novel vertical-axis wind turbines. In: 13th UK Workshop on Computational Intelligence, UKCI 2013, Guildford, UK, 9-11 September 2013., pp. 74-81 Available from: http://eprints.uwe.ac.uk/25812

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Publisher's URL: http://dx.doi.org/10.1109/UKCI.2013.6651290

Abstract/Description

Renewable and sustainable energy is one of the most important challenges currently facing mankind. Wind has made an increasing contribution to the world's energy supply mix, but still remains a long way from reaching its full potential. In this paper, we investigate the use of artificial evolution to design vertical-axis wind turbine prototypes that are physically instantiated and evaluated under approximated wind tunnel conditions. An artificial neural network is used as a surrogate model to assist learning and found to reduce the number of fabrications required to reach a higher aerodynamic efficiency. Unlike in other approaches, such as computational fluid dynamics simulations, no mathematical formulations are used and no model assumptions are made.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:aerodynamic efficiency, approximated wind tunnel conditions, artificial evolution, artificial neural network, surrogate model, vertical-axis wind turbines
Faculty/Department:Faculty of Environment and Technology > Department of Computer Science and Creative Technologies
ID Code:25812
Deposited By: Dr R. Preen
Deposited On:23 Jun 2015 07:08
Last Modified:15 Nov 2016 18:14

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