TY - JOUR

T1 - Comparison of dense optical flow and PIV techniques for mapping surface current flow in tidal stream energy sites

AU - McIlvenny, Jason

AU - Williamson, Benjamin

AU - Fairley, Ian

AU - Lewis, Matthew

AU - Neill, Simon

AU - Masters, Ian

AU - Reeve, Dominic E.

PY - 2023/9

Y1 - 2023/9

N2 - Marine renewable energy site and resource characterisation, in particular tidal stream energy, require detailed flow measurements which often rely on high-cost in situ instrumentation which is limited in spatial extent. We hypothesise uncrewed aerial vehicles (UAV) offer a low-cost and low-risk data collection method for tidal stream environments, as recently techniques have been developed to derive flow from optical videography. This may benefit tidal and floating renewable energy developments, providing additional insight into flow conditions and complement traditional instrumentation. Benefits to existing data collection methods include capturing flow over a large spatial extent synchronously, which could be used to analyse flow around structures or for site characterisation; however, uncertainty and method application to tidal energy sites is unclear. Here, two algorithms are tested: large-scale particle image velocimetry using PIVlab and dense optical flow. The methods are applied on video data collected at two tidal stream energy sites (Pentland Firth, Scotland, and Ramsey Sound, Wales) for a range of flow and environmental conditions. Although average validation measures were similar (~ 20–30% error), we recommend PIVlab processed velocity data at tidal energy sites because we find bias (underprediction) in optical flow for higher velocities (> 1 m/s).

AB - Marine renewable energy site and resource characterisation, in particular tidal stream energy, require detailed flow measurements which often rely on high-cost in situ instrumentation which is limited in spatial extent. We hypothesise uncrewed aerial vehicles (UAV) offer a low-cost and low-risk data collection method for tidal stream environments, as recently techniques have been developed to derive flow from optical videography. This may benefit tidal and floating renewable energy developments, providing additional insight into flow conditions and complement traditional instrumentation. Benefits to existing data collection methods include capturing flow over a large spatial extent synchronously, which could be used to analyse flow around structures or for site characterisation; however, uncertainty and method application to tidal energy sites is unclear. Here, two algorithms are tested: large-scale particle image velocimetry using PIVlab and dense optical flow. The methods are applied on video data collected at two tidal stream energy sites (Pentland Firth, Scotland, and Ramsey Sound, Wales) for a range of flow and environmental conditions. Although average validation measures were similar (~ 20–30% error), we recommend PIVlab processed velocity data at tidal energy sites because we find bias (underprediction) in optical flow for higher velocities (> 1 m/s).

KW - Drones

KW - Energy

KW - Optical flow

KW - Remote sensing

KW - Tidal stream

KW - UAV

U2 - 10.1007/s40095-022-00519-z

DO - 10.1007/s40095-022-00519-z

M3 - Article

VL - 14

SP - 273

EP - 285

JO - International Journal of Energy and Environmental Engineering

JF - International Journal of Energy and Environmental Engineering

IS - 3

ER -