Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/83948
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Type: Conference paper
Title: Fast and effective multi-objective optimisation of wind turbine placement
Author: Tran, R.
Wu, J.
Denison, C.
Ackling, T.
Wagner, M.
Neumann, F.
Citation: Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation, GECCO'13, 2013: pp.1381-1388
Publisher: ACM
Publisher Place: online
Issue Date: 2013
ISBN: 9781450319638
Conference Name: Genetic and Evolutionary Computation Conference (15th : 2013 : Amsterdam, Netherlands)
Statement of
Responsibility: 
Raymond Tran, Junhua Wu, Christopher Denison, Thomas Ackling, Markus Wagner, Frank Neumann
Abstract: The single-objective yield optimisation of wind turbine placements on a given area of land is already a challenging optimization problem. In this article, we tackle the multi-objective variant of this problem: we are taking into account the wake effects that are produced by the different turbines on the wind farm, while optimising the energy yield, the necessary area, and the cable length needed to connect all turbines. One key step contribution in order to make the optimisation computationally feasible is that we employ problem-specific variation operators. Furthermore, we use a recently presented caching-technique to speed-up the computation time needed to assess a given wind farm layout. The resulting approach allows the multi-objective optimisation of large real-world scenarios within a single night on a standard computer.
Keywords: Wind Power; Wind Farm Layout; Multi-Objective Optimisation
Rights: Copyright 2013 ACM
RMID: 0020137859
DOI: 10.1145/2463372.2463541
Description (link): http://www.sigevo.org/gecco-2013/
Published version: http://dl.acm.org/citation.cfm?id=2463372
Appears in Collections:Computer Science publications

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