Evolutionary computation for wind farm layout optimization

Wilson, Dennis and Rodrigues, Silvio and Segura, Carlos and Loshchilov, Ilya and Huttor, Frank and Buenfil, Guillermo López and Kheiri, Ahmed and Keedwell, Ed and Ocampo-Pineda, Mario and Özcan, Ender and Peña, Sergio Ivvan Valdez and Goldman, Brian and Rionda, Salvador Botello and Hernández-Aguirre, Arturo and Veeramachaneni, Kalyan and Sylvain, Cussat-Blanc (2018) Evolutionary computation for wind farm layout optimization. Renewable Energy . ISSN 1879-0682 (In Press)

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Abstract

This paper presents the results of the second edition of the Wind Farm Layout Optimization Competition, which was held at the 22nd Genetic and Evolutionary Computation COnference (GECCO) in 2015. During this competition, competitors were tasked with optimizing the layouts of five generated wind farms based on a simplified cost of energy evaluation function of the wind farm layouts. Online and offline APIs were implemented in C++, Java, Matlab and Python for this competition to offer a common framework for the competitors. The top four approaches out of eight participating teams are presented in this paper and their results are compared. All of the competitors' algorithms use evolutionary computation, the research field of the conference at which the competition was held. Competitors were able to downscale the optimization problem size (number of parameters) by casting the wind farm layout problem as a geometric optimization problem. This strongly reduces the number of evaluations (limited in the scope of this competition) with extremely promising results.

Item Type: Article
Keywords: wind farm layout optimization, evolutionary algorithm, competition
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number: 10.1016/j.renene.2018.03.052
Depositing User: Ozcan, Dr Ender
Date Deposited: 04 Apr 2018 08:29
Last Modified: 05 Apr 2018 13:38
URI: http://eprints.nottingham.ac.uk/id/eprint/50864

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