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Type: Conference paper
Title: Fast and effective multi-objective optimisation of submerged wave energy converters
Author: Arbonès, D.
Ding, B.
Sergiienko, N.
Wagner, M.
Citation: Lecture Notes in Artificial Intelligence, 2016 / Handl, J., Hart, E., Lewis, P.R., LopezIbanez, M., Ochoa, G., Paechter, B. (ed./s), vol.9921, pp.675-685
Publisher: Springer
Issue Date: 2016
Series/Report no.: Lecture Notes in Computer Science
ISBN: 9783319458229
ISSN: 0302-9743
Conference Name: 14th International Conference on Parallel Problem Solving from Nature (PPSN XIV) (17 Sep 2016 - 21 Sep 2016 : Edinburgh, United Kingdom)
Editor: Handl, J.
Hart, E.
Lewis, P.R.
LopezIbanez, M.
Ochoa, G.
Paechter, B.
Statement of
Dídac Rodríguez Arbonès, Boyin Ding, Nataliia Y. Sergiienko, and Markus Wagner
Abstract: Despite its considerable potential, wave energy has not yet reached full commercial development. Currently, dozens of wave energy projects are exploring a variety of techniques to produce wave energy efficiently. A common design for a wave energy converter is called a buoy. A buoy typically floats on the surface or just below the surface of the water, and captures energy from the movement of the waves. In this article, we tackle the multi-objective variant of this problem: we are taking into account the highly complex interactions of the buoys, while optimising the energy yield, the necessary area, and the cable length needed to connect all buoys. We employ caching-techniques and problem-specific variation operators to make this problem computationally feasible. This is the first time the interactions between wave energy resource and array configuration are studied in a multi-objective way.
Keywords: Wave energy, multi-objective optimisation, simulation speed-up
Rights: © Springer International Publishing AG 2016
DOI: 10.1007/978-3-319-45823-6_63
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Appears in Collections:Aurora harvest 3
Mechanical Engineering conference papers

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