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Modelling the impact of flow-driven turbine power plants on great wind-driven ocean currents and the assessment of their energy potential

Nature Energy volume 5, pages 240–249 (2020)Cite this article

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Abstract

The persistence in the strength and direction of western boundary great ocean currents suggests that flow-driven turbines implemented in these currents have great potential for energy exploitation. However, technological developments in the design and installation of power-generating plants in the ocean are tied to our capacity to accurately identify the most favourable sites and provide practical assessments of the potentially recoverable energy. Here we use a global eddy-resolving ocean model to demonstrate that large ocean power plants may exert feedback on oceanic circulation that results in highly unpredictable changes in ocean currents. Regionally, these changes can drastically modify the path of the current. In extreme cases this corresponds to a decrease in the available power by more than 80% from initial expectations.

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Fig. 1: Mean currents at 15 m in a large sector of the Gulf-Stream and the Kuroshio.
Fig. 2: TAP.
Fig. 3: Scatter plot of HP as a function of TAP.
Fig. 4: Current at 32 m depth in the Florida Current.
Fig. 5: Current properties at 32 m depth in the Florida Current (site gs7).
Fig. 6: Current at 32 m depth north of Luzon Island.
Fig. 7: Mean flow and HP north of Luzon Island (site ks16).

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Data availability

The current velocity dataset that supports the findings of this study is available at https://doi.org/10.5281/zenodo.3631372. This dataset comprises the five-day zonal and meridional velocity components, from the surface down to 100 m depth, for the regions of the Gulf-Stream and Kuroshio that were considered in this study, for the 1/12° control and turbine simulations used in this study. These components are available in a NetCDF format that contains the appropriate metadata. Documentation that indicates the model coordinates of the points where the drag force was implemented is also provided. Source Data is provided for Figs. 1–7. The five years (2017–2011) of the 1/12° global model outputs of the control experiment and of the 1/36° control and turbine simulations are available only on request because of the large amount of storage space required. Contact: jean-marc.molines@univ-grenoble-alpes.fr.

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Acknowledgements

Research leading to these results benefited from support provided by the program Les Enveloppes Fluides et l’Environnemens (LEFE) of Institut des Sciences de l’Univers (INSU), the Partenariat Hubert Curien Kolmogorov (no. 38102RF) and project no. 14.W03.31.0006 of the Russian Ministry of Education and Science. This work benefited from the support given by INSU to the DRAKKAR international coordination network. It was granted access to high performance computing resources under the allocation x2014-010727 attributed by GENCI (Grand Equipement National de Calcul Intensif) to DRAKKAR, with simulations carried out at the supecomputer facility of the Centre Informatique National de l’Enseignement Supérieur (CINES). B.B., J.M.M., T.P., J.L.S., T.M. and P.B. are supported by Centre National de la Recherche Scientifique (CNRS). A.D. and P.C. were supported by Université Grenoble Alpes. S.G. is supported by the Russian Academy of Science. L.B. is supported by Ocean Next. We acknowledge the availability of the ADCP data on the Florida Atlantic University website. We thank our colleagues of the weekly Institut des Géosciences de l’Environnement Friday beer event who fostered our motivation for the study.

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Authors and Affiliations

  1. Institut des Géosciences de l’Environnement, Centre National de la Recherche Scientifique, Université Grenoble Alpes, CNRS/UGA/IRD/G-INP, Grenoble, France

    Bernard Barnier, Anastasiia Domina, Jean-Marc Molines, Thierry Penduff, Julien Le Sommer, Pierre Brasseur & Pedro Colombo

  2. Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russia

    Bernard Barnier & Sergey Gulev

  3. School of Environmental Sciences, University of Liverpool, Liverpool, UK

    Anastasiia Domina

  4. Laboratoire des Ecoulements Geophysiques et Industriels, Grenoble, France

    Thierry Maitre

  5. Ocean Next, Grenoble, France

    Laurent Brodeau

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Contributions

A.D. and B.B. conceived the study. B.B. and S.G. supervised the research. A.D., B.B., S.G. and L.B. produced the figures. J.-M.M. carried out the model simulations and managed the data base. P.C. designed and carried out the 1/36° simulations. A.D., B.B. and S.G. analysed model data, produced the results and wrote the paper. T.M. provided expertise on turbine theory. T.P., J.L.S., P.B., P.C. and L.B. provided expertise in the interpretation of the ocean model sensitivity and contributed to editing the paper.

Corresponding author

Correspondence to Bernard Barnier.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–12, Tables 1–4, Notes 1–8, refs. 1–5.

Source data

Source Data Fig. 1

Model data (in NetCDF format) used to plot Fig. 1c. The files contain the mean current field for the year 2008 of the control simulation for the Gulf-Stream and the Kuroshio domains. Variables given are depth, longitude, latitude, current direction, current speed and zonal and meridional velocity components, at ten different depths from the surface.

Source Data Fig. 2

The TAP calculated from the control simulation (mean of 2007–2011) for the global ocean (in NetCDF format).

Source Data Fig. 3

Mean TAP and HP values at each of the 16 TPP sites, for the control and turbine experiments and for all other sensitivity experiments. Sheet 1 is for Fig. 3a, and sheet 2 for Fig. 3b.

Source Data Fig. 4

Two NetCDF files containing the mean current field for the year 2008 of the control and of the turbine simulations for the Gulf-Stream domain. Variables given are longitude, latitude and current speed at the depth of 32 m. Barnier_SourceData_Fig4_Control.nc is used for Fig. 4a. Barnier_Sourcedata_Fig4_Turbine.nc is used for Fig. 4b. Figure 4c is the difference of the datasets.

Source Data Fig. 5

The time series of the current speed at site gs7 and the occurrence of the current speed and direction.

Source Data Fig. 6

Same as for Fig. 4, but for the Kuroshio domain.

Source Data Fig. 7

The time series of the TAP and HP at site ks16 and the occurrence distribution.

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Barnier, B., Domina, A., Gulev, S. et al. Modelling the impact of flow-driven turbine power plants on great wind-driven ocean currents and the assessment of their energy potential. Nat Energy 5, 240–249 (2020). https://doi.org/10.1038/s41560-020-0580-2

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