Because of the need to account for back effects, national and regional resource assessments rely on models. In addition, it is often impractical (or impossible) to collect enough data to cover the domain of interest at the reconnaissance stage.
Tidal resource values based on the models are, of course, only as accurate as the model itself. This accuracy is particularly sensitive, because errors in the currents are exacerbated when taking the cube of the currents to calculate the tidal resource intensity. In this context, measurements are used to validate and tune the models.
For example, the model used for the US resource atlas grossly underestimated power density relative to in situ measurements at a potential tidal energy site in Admiralty Inlet in Washington State (USA), as shown in Fig.7. While the model qualitatively captures the amplification of currents by the nearby headland, quan-titative agreement is poor; measured power density exceeds model values by a factor of two to three and has a proportional implication for estimates of the cost of energy from tidal current power generation at this site. Models run at much higher resolution can more accurately quantify power density throughout the channel and the effects of the headland (Yang and Wang2013; Thyng et al.2013), but this level of detail is often beyond the scope of national reconnaissance activities. In Fig.8, both models and measurements show strong gradients in the currents at small spatial scales (∼100 m), demonstrating the importance of model validation prior to
Fig. 7 Comparison of average power density, K, measurement with ADCP data (blue) and modeled in the US tidal atlas (red) for the case study at Admiralty Inlet
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model application for resource assessment. It also supports the recommendation for site-specific resource characterization based on the field measurements (IEC2015), because the regional-scale nature of most reconnaissance resource assessments is not well-matched to the small-scale complexity of tidal currents.
The resource assessment conducted by Iyers et al. (2013) for the UK illustrates how theoretical, technical, and practical AEP can be estimated for a large region.
This resource assessment was greatly simplified at the outset by limiting tidal energy extraction to first-generation tidal turbine technologies, which requires spring peak currents to be greater than 2.5 m/s and depths between 25 and 50 m.
A similar approach was used by Boehme et al. (2006), but with a threshold current of 2.0 m/s and depths between 30 and 50 m. This limited the scope of the assessment to seven locations around the UK. Tidal current time series data from the UK Hydrographic Office Admiralty Chart were used in lieu of current speed data derived from ADCP measurements or a numerical model. These data are generated using a simple model based only on the two dominant tidal harmonic constituents, M2 and S2. Resource assessments that rely onfield data are most often applied over small domains (e.g., Fairley et al. 2013). More commonly, resource assessments cover larger domains and rely on realistic circulation models that have been validated to various degrees byfield measurements.
Fig. 8 Comparison of modeled and measured kinetic power density at a tidal energy site in Admiralty Inlet, Washington (USA) at a height of 10 m above the seabed. Model results derived from Thyng (2012). Color map denotes modeled kinetic power density. Circles denote measurements at specific locations
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One of the key contributions of reconnaissance studies at national scales is the identification of hot spots that have high local power densities and, therefore, high AEP values (e.g., O’Rourke et al. 2010). After hot spots are identified in the reconnaissance phase, feasibility-level assessments are conducted to refine project siting and increase the resolution and accuracy of resource characterization to plan a tidal energy farm. Data sources for feasibility studies often rely heavily on validated model hindcasts, but these should be supplemented withfield measurements, such as bottom- and vessel-mounted ADCP measurements. Finally, design-level assessments are conducted at spatial resolutions similar to the size of individual turbines and are best done withfixed field measurements, such as bottom-mounted ADCPs. Moored acoustic Doppler velocimeters (ADVs) can also be used during this stage. These methods are described by the IEC (2015), Neary et al. (2011), Blunden and Bahaj (2007), and Kilcher et al. (2016).
Conclusions
While tidal resource assessment can be limited in scope to an estimate of AEP, this simplification obscures the many complexities of the resource. While the resolution of deterministic components may be adequate for characterizing AEP, both com-ponents need to be quantified to determine design loads on tidal energy conversion devices. Large space and time variations are common at most tidal energy sites, and, given the limitations of modeling, site-specific measurements are required to fully characterize such variations. Quantifying a full suite of parameters (i.e., Table1), as well as AEP, provides a more comprehensive characterization and assessment of the tidal energy resource; one that includes quantification of the risks, as well as opportunities for a tidal energy project. Measurements are a key com-ponent of this process. Field measurements must be at high sampling frequencies (∼10 Hz), and over long durations (∼months) to resolve stochastic and determin-istic components occurring over a broad range of temporal scales. While this can be accomplished for a point measurement, it becomes challenging when measuring current speeds and turbulent fluctuations over a profile or cross section. Ongoing improvements in measurement techniques, e.g., Kilcher et al. (2016), and improved current profiler technology, e.g., Guerra and Thomson (in minor revision), will help researchers address these challenges.
The other role offield measurements is to evaluate and validate models. This role is equally important, because models have become a standard tool for high-level resource assessments (e.g., national and regional assessments). Small biases in the currents predicted by models can result in significant changes in the local power density (because of the cubic relation) and thus model accuracy must be confirmed at each level (or resolution) of its application. Furthermore, models often param-eterize details of the flow (e.g., turbulence closure schemes) that measurements can provide (Thyng et al.2013).
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Best practices for quantifying the tidal resource are still being actively developed by a large community of researchers. The choice of parameters and approaches depends on study objective and site characteristics, but it is clear that the mea-surements, combined with models, are essential for capturing the complexity of the tidal resource in sufficient detail to effectively harness the energy.
References
Adcock, T. A., Draper, S., Houlsby, G. T., Borthwick, A. G., & Serhadlıoğlu, S. (2013). The available power from tidal stream turbines in the Pentland Firth. In Proceedings of the Royal Society A, 469(2157), 20130072. The Royal Society.
Blachfield, J., Garrett, C., Rowe, A., & Wild, P. (2008). The extractable power from a channel linking a bay to the open ocean. Proceedings of IMechE Part A: Journal of Power Energy, 222 (A3), 289–297.
Blunden, L. S., & Bahaj, A. S. (2007). Tidal energy resource assessment for tidal-stream generators. Journal of Power Energy, 221, 137–146.
Boehme, T., Taylor, J., Wallace, A. R., & Bialek, J. (2006). Matching renewable electricity generation with demand. Edinburgh: The Scottish Executive.
Carballo, R., Iglesias, G., & Castro, A. (2009). Numerical model evaluation of tidal-stream energy resources in the Ría de Muros (NW Spain). Renewable Energy, 34(6), 1517–1524.
Defne, Z., Haas, K. A., Fritz, H. M., Jiang, L., French, S. P., Shi, X., et al. (2012). National geodatabase of tidal stream power resource in USA. Renewable and Sustainable Energy Reviews, 16(5), 3326–3338. ISSN 1364-0321. doi:10.1016/j.rser.2012.02.061.
Easton, M. C., Woolf, D. K., & Bowyer, P. A. (2012). The dynamics of an energetic tidal channel, the Pentland Firth, Scotland. Continental Shelf Research, 48, 50–60.
Fairley, I., Evans, P., Wooldridge, C., Willis, M., & Masters, I. (2013). Evaluation of tidal stream resource in a potential array area via direct measurements. Renewable Energy, 57, 70–78.
Frost, C., Morris, C. E., Mason-Jones, A., O’Doherty, D. M., & O’Doherty, T. (2015). The effect of tidal flow directionality on tidal turbine performance characteristics. Renewable Energy, 78, 609–620.
Garrett, C., & Cummins, P. (2005). The power potential of tidal currents in channels. Proceedings of the Royal Society A, 461, 2563–2572.
Garrett, C., & Cummins, P. (2007). The efficiency of a turbine in a tidal channel. Journal of Fluid Mechanics, 588, 243–251.
Garrett, C., & Cummins, P. (2008). Limits to tidal current power. Renewable Energy, 33, 2485–2490.
Godin, G. (1983). On the predictability of currents. International Hydrographic Review, 60, 119–126.
Goundar, J. N., & Ahmed, M. R. (2014). Marine current energy resource assessment and design of a marine current turbine for Fiji. Renewable Energy, 65, 14–22.
Guerra, M., & Thomson, J. (in minor revision). Turbulence measurements from 5-beam ADCPs.
Journal of Atmospheric and Ocean Technology.
Gunawan, B., Neary, V. S., & Colby, J. (2014). Tidal energy site resource assessment in the East River tidal strait, near Roosevelt Island, New York, New York. Renewable Energy, 71, 509–517.
IEC (2015) TS 62600-201:2015 Marine energy—Wave, tidal and other water current converters—
Part 201: Tidal energy resource assessment and characterization.
Iyer, A., Couch, S., Harrison, G., & Wallace, A. (2013). Variability and phasing of tidal current energy around the United Kingdom. Renewable Energy, 51, 343–357.
134 J. Thomson et al.
Jonkman, J. B., & Kilcher, L. (2012). TurbSim user’s guide: Version 1.06. 00, National Renewable Energy Laboratory. Technical report.https://wind.nrel.gov/designcodes/preprocessors/turbsim/
TurbSim.pdf.
Karsten, R. H., McMillan, J. M., Lickley, M. J., & Haynes, R. D. (2008). Assessment of tidal current energy in the Minas Passage, Bay of Fundy. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 222(5), 493–507.
Kilcher, L., Thomson, J., Talbert, J., & deKlerk, A. (2016). Measuring turbulence from moored acoustic Doppler velocimeters: A manual to quantifying inflow at tidal energy sites. NREL technical report TP-5000-62979.
Kutney, T., Karsten, R., & Polagye, B. (2013). Priorities for reducing tidal energy resource uncertainty. In European Wave and Tidal Energy Conference, Aalborg, Denmark, September 2–5.
Lewis, M., Neill, S. P., Robins, P. E., & Hashemi, M. R. (2015). Resource assessment for future generations of tidal-stream energy arrays. Energy, 83(1), 403–415.
McCaffrey, K., Fox-Kemper, B., Hamlington, P. E., & Thomson, J. (2015). Characterization of turbulence anisotropy, coherence, and intermittency at a prospective tidal energy site:
Observational data analysis. Renewable Energy, 76, 441–453.
Mycek, P., Gaurier, B., Germain, G., Pinon, G., & Rivoalen, E. (2014). Experimental study of the turbulence intensity effects on marine current turbines behaviour. Part I: One single turbine.
Renewable Energy, 66, 729–746.
National Research Council. (2013). An evaluation of the U.S. department of energy’s marine and hydrokinetic resource assessments. ISBN 978-0-309-26999-5, 114 p.
Neary, V., Gunawan, B., Richmond, M., Durgesh, V., Polagye, B., Thomson, J., Muste, M., &
Fontaine, A. (2011). Field measurements at rivers and tidal current sites for hydrokinetic energy development: best practices manual. Oak Ridge National Laboratory Technical Manual 2011/419.
Neill, S. P., Hashemi, M. R., & Lewis, M. J. (2014). The role of tidal asymmetry in characterizing the tidal energy resource of Orkney. Renewable Energy, 68, 337–350.
O’Rourke, F., Boyle, F., & Reynolds, A. (2010). Tidal current energy resource assessment in Ireland: Current status and future update. Renewable and Sustainable Energy Reviews, 14, 3206–3212.
Palodichuk, M., Polagye, B., & Thomson, J. (2013). Resource mapping at tidal energy sites.
Journal of Ocean Engineering, 38.
Pawlowicz, R., Beardsley, R., & Lentz, S. (2002). Classical tidal harmonic analysis including error estimates in MATLAB using T_TIDE. Computers & Geosciences, 28(8), 929–937.
Polagye, B., & Thomson, J. (2013). Tidal energy resource characterization: Methodology andfield study in Admiralty Inlet, Puget Sound, US. Proceedings of IMechE, Part A: Journal of Power and Energy, 227.
Polagye, B. L., & Malte, P. C. (2011). Far-field dynamics of tidal energy extraction in channel networks. Renewable Energy, 36(1), 222–234.
Polagye, B., Malte, P., Kawase, M., & Durran, D. (2008). Effect of large-scale kinetic power extraction on time-dependent estuaries. Proceedings of IMechE, Part A: Journal of Power and Energy, 222(5), 471–484.
Robins, P. E., Neill, S. P., Lewis, M. J., & Ward, S. L. (2015). Characterizing the spatial and temporal variability of the tidal-stream energy resource over the northwest European shelf seas.
Applied Energy, 147, 510–522.
Sanchez, M., Carballo, R., Ramos, V., Álvarez, M., Vazquez, A., & Iglesias, G. (2014). Impact of tidal stream energy exploitation on estuarine hydrodynamics. Coastal Engineering Proceed-ings, 1(34), 22.
Serhadlıoğlu, S., Adcock, T. A., Houlsby, G. T., Draper, S., & Borthwick, A. G. (2013). Tidal stream energy resource assessment of the Anglesey Skerries. International Journal of Marine Energy, 3, e98–e111.
Shapiro, G. I. (2011). Effect of tidal stream power generation on the region-wide circulation in a shallow sea. Ocean Science, 7, 165–174.
Tidal Energy Resource Measurements 135
Thomson, J., Richmond, M., Polagye, B., & Durgesh, V. (2012). Measurements of turbulence at two tidal energy sites. Journal of Ocean Engineering, 37.
Thomson, J., Talbert, J., de Klerk, A., Zippel, S., Guerra, M., & Kilcher, L. (2015). Turbulence measurements from moving platforms. In Currents, Waves, and Turbulence Measurements Workshop, St. Petersburg, FL.
Thyng. (2012). Numerical simulation of admiralty inlet, WA, with tidal hydrokinetic turbine siting application. PhD Thesis, University of Washington.
Thyng, K. M., Riley, J. J., & Thomson, J. (2013). Inference of turbulence parameters from a ROMS simulation using the k-ε closure scheme. Ocean Modelling, 72, 104–118.
Vennell, R. (2012). Realizing the potential of tidal currents and the efficiency of turbine farms in a channel. Renewable Energy, 47, 95–102.
Yang, Z., & Wang, T. (2013). Tidal residual eddies and their effect on water exchange in puget sound. Ocean Dynamics, 63, 995–1009.
Yang, Z., & Wang, T. (2015). Modeling the effects of tidal energy extraction on estuarine hydrodynamics in a stratified estuary. Estuaries and Coasts, 38(1 Supplement), 187–202.
doi:10.1007/s12237-013-9684-2.
136 J. Thomson et al.