Toward the coevolution of novel vertical-axis wind turbines

Preen, R. and Bull, L. (2015) Toward the coevolution of novel vertical-axis wind turbines. IEEE Transactions on Evolutionary Computation, 19 (2). pp. 284-294. ISSN 1089-778X Available from: http://eprints.uwe.ac.uk/25797

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Publisher's URL: http://dx.doi.org/10.1109/TEVC.2014.2316199

Abstract/Description

The production of 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 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. Initially, a conventional evolutionary algorithm is used to explore the design space of a single wind turbine and later a cooperative coevolutionary algorithm is used to explore the design space of an array of wind turbines. Artificial neural networks are used throughout as surrogate models to assist learning and found to reduce the number of fabrications required to reach a higher aerodynamic efficiency. Unlike other approaches, such as computational fluid dynamics simulations, no mathematical formulations are used and no model assumptions are made.

Item Type:Article
Uncontrolled Keywords:3-D printers, coevolution, surrogate-assisted evolution, wind turbines
Faculty/Department:Faculty of Environment and Technology > Department of Computer Science and Creative Technologies
ID Code:25797
Deposited By: Dr R. Preen
Deposited On:22 Jun 2015 08:00
Last Modified:07 Jul 2016 14:26

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