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

International Journal of Energy and Environmental Engineering https://doi.org/10.1007/s40095-022-00519-z ORIGINAL RESEARCH Comparison of dense optical flow and PIV techniques for mapping surface current flow in tidal stream energy sites J. McIlvenny1 · B. J. Williamson1 · I. A. Fairley2 · M. Lewis3 · S. Neill3 · I. Masters2 · D. E. Reeve2 Received: 14 April 2022 / Accepted: 13 August 2022 © The Author(s) 2022 Abstract 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). Keywords Tidal stream · Remote sensing · Energy · Drones · UAV · Optical flow Introduction Marine renewable energy offers electricity generation from highly predictable sources [1–3]. Both offshore wind and tidal energy are being developed globally to move towards a net-zero carbon future. Flow data in such developments are routinely collected for a variety of reasons, such as initial site characterisation [4], device micro-siting [5] and flow around structures and turbines [6, 7]. Data collection for marine renewable energy site selection, resource characterisation and turbine placement often involves fixed seabed instrumentation or boat-based measurements such as Acoustic Doppler Current Profilers * J. McIlvenny 1 Environmental Research Institute, North Highland College, University of the Highlands and Islands, Ormlie Road, Thurso KW14 7EE, Scotland 2 Swansea University, Swansea, Wales 3 Bangor University, Bangor, Wales (ADCP). Bottom-mounted ADCPs provide a point-based measurement in a single location, whilst boat-based ADCP measurements are non-synchronous and typically of a low spatial resolution. ADCP measurements, whilst still essential, do carry high risk and cost. X-band radar is an effective method of deriving surface currents over a large area and has been used in tidal flows [8], however comes with high instrument and operating costs, particularly in remote environments. Small UAV technology is increasingly accessible with consumer off the shelf UAVs providing flexible platforms with high-quality video and effective battery life at a relatively low cost. These systems have been increasingly used in marine science [9]. UAV surveys incur less financial risk, and less physical risk, as the UAVs are typically lightweight and highly manoeuvrable [10]. For the marine renewable industry, video-derived flow will provide a valuable addition to existing data capture methods, measuring surface flow in a low cost and low-risk way. Capturing flow over a large spatial area is extremely useful throughout the lifecycle of a floating or seabed development enabling initial site sift and selection, 13 Vol.:(0123456789) International Journal of Energy and Environmental Engineering characterisation, device micro-siting and flow-structure analysis over different periods. Flow derived from optical videography began as a laboratory technique originally derived from laser-based particle measurements [11]. Flow derived from downward-looking video offers a way of measuring surface flow over a large spatial area capturing fine spatio-temporal detail of flow characteristics. UAV-derived video can also provide an additional tool to rapidly define surface flow characteristics such as high-velocity jets and other turbulent features in tidal streams; therefore, UAVs could offer an essential tool for the tidal energy industry. Various methods are available for deriving flow from video, each with advantages and disadvantages; however, their applicability to tidal energy site characterisation is unknown. Here, we compare two methods: large-scale particle image velocimetry (LSPIV) and Gunnar-Farneback dense optical flow. Particle tracking techniques have been increasingly used for flow measurement in rivers [12–16]. LSPIV relies on the flow being seeded with artificial or natural particles and is highly accurate in a wide variety of natural flow conditions [17]. However, LSPIV does have drawbacks, as the technique relies on natural particles such as foam or debris on the surface; insufficient particles require artificial seeding which is labour intensive and not appropriate for tidal environments on a large scale. The technique also has a reduced ability to derive flow from a low-intensity image gradient [18]. However, it has been shown to provide good results when ephemeral turbulent structures advected by the mean flow are tracked, sometimes termed surface structure image velocimetry [19], and it would be this approach that could be used at tidal sites. PIVlab is a GUI-based particle image velocimetry (PIV) software written in the MATLAB environment [20–22]. PIVlab uses a cross-correlation algorithm to derive the most probable particle displacement in small image subsections [20]. PIVlab has been applied to natural environments in the past for extracting river velocity and is accurate when compared with in situ measurement [23–27] and has also been used to estimate river discharge [25, 27–29]. Use of PIVlab for measurement of tidal flows, including at tidal stream sites, has been demonstrated [30, 31]; however, good results were dependent on site and environmental conditions. Therefore, investigation of alternative surface velocimetry approaches is warranted to seek wider ranging applicability of UAVs for tidal resource assessment. Various optical flow algorithms are available for surface water movement detection, some of which have been applied to the marine environment [32]. Here, the GunnarFarneback dense optical flow is used as a method of deriving flow from consecutive optical images by using pixel intensity and calculating the movements of each pixel between consecutive frames [33]. This has (...truncated)