posted on 2025-07-31, 16:16authored byC Frost, D Findlay, L Johanning, E Macpherson, P Sayer
A high level economic model has been developed to map wave energy performance and levelised cost of en-ergy (LCOE). It takes time-series, gridded hindcast wave data, for example generated by SWAN (Simulating WAves Nearshore) software. Interpolating this data against a device power matrix, the wave conditions are converted to power, and then to LCOE using a discounting method and considering capital and operational costs. The results are presented as maps, which serve as high level site assessment tools and allow the most cost-competitive sites to be established. Initial results have been generated for Albatern Ltd, a Scottish wave energy developer and industrial part-ner of the research project. Their technology is the WaveNET, a small-scale array based device which is con-structed from 7.5 kW rated modular units (known as “Squids”). LCOE Maps have been created for a domain covering the Scottish Western Isles, as well as for NOAA hindcast datasets for regions around the world. This paper includes a sample case study, comparing the LCOE for a device concept at two different scales. The re-sults found that, while the larger device performs better over the majority of the area, there are places where the smaller device has a better LCOE, sometimes by as much as 20-30 p/kWh. These are in the more sheltered regions, and imply both that there is not a one fit all solution to wave energy, and that device scale is a param-eter which could be tuned for location
Funding
The authors wish to thank the Energy Technology Institute and RCUK Energy programme for funding this research as part of the IDCORE programme (EP/J500847/1).
This is the author accepted manuscript. The final version is available from CRC Press
Publisher
Taylor & Francis (CRC Press)
Editors
Soares, CG
Language
en
Citation
Progress in Renewable Energies Offshore: Proceedings of the 2nd International Conference on Renewable Energies Offshore (RENEW2016), Lisbon, Portugal, 24-26 October 2016