Drone-based large-scale particle image velocimetry applied to tidal stream energy resource assessment

Iain Fairley, Benjamin J. Williamson, Jason McIlvenny, Nicholas King, Ian Masters, Matthew Lewis, Simon Neill, David Glasby, Daniel Coles, Ben Powell, Keith Naylor, Max Robinson and Dominic E. Reeve

Renewable Energy, 2022, vol. 196, issue C, 839-855

Abstract: Resource quantification is vital in developing a tidal stream energy site but challenging in high energy areas. Drone-based large-scale particle image velocimetry (LSPIV) may provide a novel, low cost, low risk approach that improves spatial coverage compared to ADCP methods. For the first time, this study quantifies performance of the technique for tidal stream resource assessment, using three sites. Videos of the sea surface were captured while concurrent validation data were obtained (ADCP and surface drifters). Currents were estimated from the videos using LSPIV software. Variation in accuracy was attributed to wind, site geometry and current velocity. Root mean square errors (RMSEs) against drifters were 0.44 m s−1 for high winds (31 km/h) compared to 0.22 m s−1 for low winds (10 km/h). Better correlation was found for the more constrained site (r2 increased by 4%); differences between flood and ebb indicate the importance of upstream bathymetry in generating trackable surface features. Accuracy is better for higher velocities. A power law current profile approximation enables translation of surface current to currents at depth with satisfactory performance (RMSE = 0.32 m s−1 under low winds). Overall, drone video derived surface velocities are suitably accurate for “first-order” tidal resource assessments under favourable environmental conditions.

Keywords: Ocean energy; Resource mapping; Unmanned aerial vehicles; Surface velocimetry; Oceanography; Remote sensing (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148122009983
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:196:y:2022:i:c:p:839-855

DOI: 10.1016/j.renene.2022.07.030

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().