Abstract
Renewable forms of energy are becoming increasingly important to consider, as the global energy demand continues to grow. Wave energy is one of these widely available forms, but it is largely unexploited. A common design for a wave energy converter is called a point absorber or buoy. The buoy typically floats on the surface or just below the surface of the water, and captures energy from the movement of the waves. It can use the motion of the waves to drive a pump to generate electricity and to create potable water. Since a single buoy can only capture a limited amount of energy, large-scale wave energy production necessitates the deployment of buoys in large numbers called arrays. However, the efficiency of arrays of buoys is affected by highly complex intra-buoy interactions. The contributions of this article are two-fold. First, we present an approximation of the buoy interactions model that results in a 350-fold computational speed-up to enable the use inside of iterative optimisation algorithms, Second, we study arrays of fully submerged three-tether buoys, with and without shared mooring points.
Original language | English |
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Title of host publication | Proceedings of the 2016 Genetic and Evolutionary Computation Conference |
Editors | Frank Neumann |
Place of Publication | New York NY USA |
Publisher | Association for Computing Machinery (ACM) |
Pages | 1045-1052 |
Number of pages | 8 |
ISBN (Electronic) | 9781450342063 |
DOIs | |
Publication status | Published - 2016 |
Externally published | Yes |
Event | The Genetic and Evolutionary Computation Conference 2016 - Hyatt Regency Denver Tech Center, Denver, United States of America Duration: 20 Jul 2016 → 24 Jul 2016 Conference number: 18th http://gecco-2016.sigevo.org/index.html/ https://dl.acm.org/doi/proceedings/10.1145/2908812 (Proceedings) |
Conference
Conference | The Genetic and Evolutionary Computation Conference 2016 |
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Abbreviated title | GECCO 2016 |
Country/Territory | United States of America |
City | Denver |
Period | 20/07/16 → 24/07/16 |
Internet address |
Keywords
- Evolutionary algorithm
- Renewable energy
- Wave energy