Journal
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
Volume 19, Issue 2, Pages 284-294Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TEVC.2014.2316199
Keywords
3-D printers; coevolution; surrogate-assisted evolution; wind turbines
Funding
- Leverhulme Trust of the U.K. [RPG-2013-344]
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available