Publication: Downscaling wave energy converters for optimum performance in low-energy seas
dc.contributor.author | Iglesias, Gregorio | |
dc.contributor.buuauthor | Majidi, AjabGul | |
dc.contributor.buuauthor | Bingolbali, Bilal | |
dc.contributor.buuauthor | BİNGÖLBALİ, BİLAL | |
dc.contributor.buuauthor | Akpinar, Adem | |
dc.contributor.buuauthor | AKPINAR, ADEM | |
dc.contributor.buuauthor | Jafali, Halid | |
dc.contributor.department | Mühendislik Fakültesi | |
dc.contributor.orcid | 0000-0003-0006-5843 | |
dc.contributor.orcid | 0000-0003-4496-5974 | |
dc.contributor.orcid | 0000-0002-5422-0119 | |
dc.contributor.researcherid | AAB-4152-2020 | |
dc.contributor.researcherid | AAC-8011-2021 | |
dc.contributor.researcherid | AAC-6763-2019 | |
dc.date.accessioned | 2024-06-14T12:54:30Z | |
dc.date.available | 2024-06-14T12:54:30Z | |
dc.date.issued | 2021-05-01 | |
dc.description.abstract | As wave energy converters (WECs) are typically designed and optimized for ocean wave conditions, they struggle to perform in low-energy seas or bays, where wave conditions are very different. This work investigates the hypothesis that downscaled versions of WECs may well be more suited for such conditions. More specifically, fifteen downscaled WECs are considered for deployment in the Black Sea. The resizing (downscaling) of the WECs is based on Froude scaling law. Ten values are considered for the scaling factor (lambda(L) = 1/4 1.0, 0.9, 0.8 ... 0.1), and the value that yields the highest capacity factor is selected for downscaling the WEC. The downscaled WEC is then compared with the original (full-scale) WEC in terms of performance (capacity factor, full-load hours, and rated capacity). This analysis is carried out for fifteen WECs and 62 locations at different water depths (5, 25, 50, 75, and 100 m), distributed on 13 lines perpendicular to the shoreline along the south-western coast of the Black Sea. The highest capacity factor was obtained by Oyster, whereas the highest energy output was achieved by SSG and WaveDragon for the locations with 4-16 m depths. For deeper waters (25, 50, 75, and 100 m), the highest capacity factor was obtained by Oceantec. In terms of energy output, the best performers were WaveDragon (at 25 m water depth) and Pontoon (at 50, 75, and 100 m water depths). The interest of this approach, however, lies not only in that it enables a scaling factor to be determined for downscaling a WEC for a given site, but also and more generally in that it proves the initial hypothesis that downscaled WECs may provide a better alternative for low-energy seas than their full-scale counterparts. | |
dc.identifier.doi | 10.1016/j.renene.2020.12.092 | |
dc.identifier.endpage | 722 | |
dc.identifier.issn | 0960-1481 | |
dc.identifier.startpage | 705 | |
dc.identifier.uri | https://doi.org/10.1016/j.renene.2020.12.092 | |
dc.identifier.uri | https://hdl.handle.net/11452/42220 | |
dc.identifier.volume | 168 | |
dc.identifier.wos | 000617119200006 | |
dc.indexed.wos | WOS.SCI | |
dc.language.iso | en | |
dc.publisher | Elsevier | |
dc.relation.journal | Renewable Energy | |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi | |
dc.relation.tubitak | 214M436 | |
dc.relation.tubitak | 118R024 | |
dc.rights | info:eu-repo/semantics/closedAccess | |
dc.subject | Wave energy converter | |
dc.subject | Optimum scale | |
dc.subject | Production performance | |
dc.subject | Black sea | |
dc.subject | Science & technology | |
dc.subject | Technology | |
dc.subject | Green & sustainable science & technology | |
dc.subject | Energy & fuels | |
dc.subject | Science & technology - other topics | |
dc.subject | Energy & fuels | |
dc.title | Downscaling wave energy converters for optimum performance in low-energy seas | |
dc.type | Article | |
dspace.entity.type | Publication | |
local.contributor.department | Mühendislik Fakültesi | |
relation.isAuthorOfPublication | eae8fad3-a39c-4f74-b0a3-dc174fdc76ad | |
relation.isAuthorOfPublication | 7613a1fe-c70a-4b3c-9424-e4d5cabe5d81 | |
relation.isAuthorOfPublication.latestForDiscovery | eae8fad3-a39c-4f74-b0a3-dc174fdc76ad |