Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
|Title:||Optimisation of large wave farms using a multi-strategy evolutionary framework|
|Citation:||Proceedings of the 2020 Genetic and Evolutionary Computation Conference (GECCO'20), 2020 / vol.abs/2003.09594, pp.1150-1158|
|Publisher:||Association for Computing Machinery|
|Publisher Place:||New York|
|Conference Name:||Genetic and Evolutionary Computation Conference (GECCO) (08 Jul 2020 - 12 Jul 2020 : Cancún, Mexico)|
|Mehdi Neshat, Bradley Alexander, Nataliia Y. Sergiienko, and Markus Wagner|
|Abstract:||Wave energy is a fast-developing and promising renewable energy resource. The primary goal of this research is to maximise the total harnessed power of a large wave farm consisting of fullysubmerged three-tether wave energy converters (WECs). Energy maximisation for large farms is a challenging search problem due to the costly calculations of the hydrodynamic interactions between WECs in a large wave farm and the high dimensionality of the search space. To address this problem, we propose a new hybrid multi-strategy evolutionary framework combining smart initialisation, binary population-based evolutionary algorithm, discrete local search and continuous global optimisation. For assessing the performance of the proposed hybrid method, we compare it with a wide variety of state-of-the-art optimisation approaches, including six continuous evolutionary algorithms, four discrete search techniques and three hybrid optimisation methods. The results show that the proposed method performs considerably better in terms of convergence speed and farm output.|
|Keywords:||Wave Energy Converters; Large wave farm; Optimisation; Evolutionary Algorithms; Hybrid multi-strategy evolutionary method; Discrete local search|
|Rights:||© 2020 Association for Computing Machinery.|
|Appears in Collections:||Computer Science publications|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.