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Optimized Numerical Model Based Assessment of Wave Power Potential of Marmara Sea

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Abstract

Marmara Sea, located between Black Sea and Aegean Sea, is an important sea for ocean engineering activities. In this study, wave power potential of Marmara Sea was investigated using the third generation spectral wind-wave model MIKE 21 SW with unstructured mesh. Wind data was obtained from ECMWF ERA-Interim re-analyses wind dataset at 10 m with a spatial resolution of 0.1° for the period of 1994 to 2014. The numerical model was calibrated with measured wave data from a buoy station located in Marmara Sea. Mesh optimization was also performed to obtain the most suitable mesh structure for the study area. This study is the first that dealt with the determination of wave energy potential of Marmara Sea. The numerical model results are presented in terms of monthly, seasonal and annual average of wave power flux (kW m−1). The maximum wave power flux is 1.13 kW m−1 and occurs in November. The overall annual mean wave power flux during 1994–2014 is found to be 0.27 kW m−1 in the offshore regions.

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References

  • Abdollahzadehmoradi, Y., Özger, M., and Altunkaynak, A., 2018. Long–term macro–scale assessment of wave power of Black Sea by an optimized numerical model. Iranian Journal of Science and Technology, Transactions of Civil Engineering, 42 (4): 1–24. DOI: 10.1007/s40996–018–0108–1.

    Article  Google Scholar 

  • Akpınar, A., and Kömürcü, M. I., 2013. Assessment of wave energy resource of the Black Sea based on 15–year numerical hindcast data. Applied Energy, 101: 502–512. DOI: 10.1016/j.apenergy.2012.06.005.

    Article  Google Scholar 

  • Akpınar, A., Bingölbali, B., and Van vledder, G. P., 2017. Longterm analysis of wave power potential in the Black Sea, based on 31–year SWAN simulations. Ocean Engineering, 130: 482–497. DOI: 10.1016/j.oceaneng.2016.12.023.

    Article  Google Scholar 

  • Alonso, R., Solari, S., and Teixeira, L., 2015. Wave energy resource assessment in Uruguay. Energy, 93: 683–696. DOI: 10. 1016/j.energy.2015.08.114.

    Article  Google Scholar 

  • Altunkaynak, A., and Nigussie, T. A., 2015. Prediction of daily rainfall by a hybrid wavelet–season–neuro technique. Journal of Hydrology, 529: 287–301. DOI: 10.1016/j.jhydrol.2015.07.046.

    Article  Google Scholar 

  • Arslan, O., 2010. Technoeconomic analysis of electricity generation from wind energy in Kutahya, Turkey. Energy, 35: 120–131. DOI: 10.1016/j.energy.2009.09.002.

    Article  Google Scholar 

  • Aydoğan, B., Ayat, B., and Yüksel, Y., 2013. Black Sea wave energy atlas from 13 years hindcasted wave data. Renewable Energy, 57: 436–447. DOI: 10.1016/j.renene.2013.01.047.

    Article  Google Scholar 

  • Besio, G., Mentaschi, L., and Mazzino, A., 2016. Wave energy resource assessment in the Mediterranean Sea on the basis of a 35–year hindcast. Energy, 94: 50–63. DOI: 10.1016/j.energy. 2015.10.044.

    Article  Google Scholar 

  • Camus, P., Losada, I. J., Izaguirre, C., Espejo, A., Menéndez, M., and Pérez, J., 2017. Statistical wave climate projections for coastal impact assessments. Earth’s Future, 5: 918–933. DOI: 10.1002/2017EF000609.

    Article  Google Scholar 

  • Chong, W. Z., and Chong, Y. L., 2015. Variation of the wave energy and significant wave height in the China Sea and adjacent waters. Renewable and Sustainable Energy Reviews, 43: 381–387. DOI: 10.1016/j.rser.2014.11.001.

    Article  Google Scholar 

  • Coe, R. G., Yu, Y.–H., and van Rij, J., 2018. A survey of WEC reliability, survival and design practices. Energies, 11 (1): 4. DOI: 10.3390/en11010004.

    Article  Google Scholar 

  • Cornett, A. M., 2008. A global wave energy resource assessment. In: The Proceedings of the Eighteenth (2008) International Offshore and Polar Engineering Conference. Vancouver, 318–326.

    Google Scholar 

  • Cruz, J., 2008. Ocean Wave Energy: Current Status and Future Prespectives. Springer Berlin Heidelberg, 431pp.

    Book  Google Scholar 

  • Defne, Z., Haas, K. A., and Fritz, H. M., 2009. Wave power potential along the Atlantic coast of the southeastern USA. Renewable Energy, 34 (10): 2197–2205. DOI: 10.1016/j.renene.2009.02.019.

    Article  Google Scholar 

  • DHI, 2012. MIKE 21 spectral wave module. Scientific documentation, DHI Water & Environment.

    Google Scholar 

  • Gray, A., Dickens, B., Bruce, T., Ashton, I., and Johanning, L., 2017. Reliability and O&M sensitivity analysis as a consequence of site specific characteristics for wave energy converters. Ocean Engineering, 141: 493–511. DOI: 10.1016/j.oceaneng.2017.06.043.

    Article  Google Scholar 

  • Hoel, M., and Kverndokk, S., 1996. Depletion of fossil fuels and the impacts of global warming. Resource and Energy Economics, 18 (2): 115–136. DOI: 10.1016/0928–7655(96)00005–X.

    Article  Google Scholar 

  • Iglesias, G., and Carballo, R., 2009. Wave energy resource in the Estaca de Bares area (Spain). Renewable Energy, 35: 1574–1584. DOI: 10.1016/j.renene.2009.10.019.

    Article  Google Scholar 

  • Iglesias, G., López, M., Carballo, R., and Castro, A., Fraguela, J. A., and Frigaard, P., 2009. Wave energy potential in Galicia (NW Spain). Renewable Energy, 34 (11): 2323–2333. DOI: 10.1016/j.renene.2009.03.030.

    Article  Google Scholar 

  • Jadidoleslam, N., Özger, M., and Ağıralioğlu, N., (2016). Wave power potential assessment of Aegean Sea with an integrated 15–year data. Renewable Energy, 86: 1045–1059. DOI: 10. 1016/j.renene.2015.09.022.

    Google Scholar 

  • Jose, F., and Stone, G. W., 2006. Forecast of nearshore wave heights using MIKE–21 spectral wave model. Gulf Coast Association of Geological Societies Transactions, 56: 323–327.

    Google Scholar 

  • Kick, C., 2011. How is 100% renewable energy possible for Turkey by 2020? Global Energy Network Institute (GENI), http://www.geni.org/.

    Google Scholar 

  • Komen, G. J., Cavaleri, L., Donelan, M., Hasselmann, K., Hasselmann, S., and Janssen, P. A. E. M., 1996. Dynamics and Modelling of Ocean Waves. Cambridge University Press, Cambridge, 560pp.

    Google Scholar 

  • Liberti, L., Carillo, A., and Sannino, G., 2013. Wave energy resource assessment in the Mediterranean, the Italian perspective. Renewable Energy, 50: 938–949. DOI: 10.1016/j.renene.2012.08.023.

    Article  Google Scholar 

  • Mackay, E. B. L., Bahaj, A. S., and Challenor, P. G., 2010b. Uncertainty in wave energy resource assessment. Part 2: Variability and predictability. Renewable Energy, 35 (8): 1809–1819. DOI: 10.1016/j.renene.2009.10.027.

    Article  Google Scholar 

  • Mackay, E. B. L., Bahaj, A. S., and Challenor, P. G., 2010a. Uncertainty in wave energy resource assessment. Part 1: Historic data. Renewable Energy, 35 (8): 1792–1808. DOI: 10. 1016/j. renene.2009.10.026.

    Article  Google Scholar 

  • Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Binger, R. L., Harmel, R. D., and Veith, T. L., 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 50 (3): 885–900.

    Article  Google Scholar 

  • Mørk, G., Barstow, S., Kabuth, A., and Pontes, M. T., 2010. Assessing the global wave energy potential. In: Proceedings of OMAE2010 29th International Conference on Ocean, Offshore Mechanics and Arctic Engineering. Shanghai, 6–11.

    Google Scholar 

  • Neill, S. P., Lewis, M. J., Hashemi, M. R., Slater, E., Lawrence, J., and Spall, S. A., 2014. Inter–annual and inter–seasonal variability of the Orkney wave power resource. Applied Energy, 132: 339–348.

    Article  Google Scholar 

  • Ramanarayanan, T. S., Williams, J. R., Dugas, W. A., Hauck, L. M., and McFarland, A. M. S., 1997. Using APEX to identify alternative practices for animal waste management: Part II. Model application. ASAE Paper 97–2209.

    Google Scholar 

  • Reeve, D. E., Chen, Y., Pan, S., Magar, V., Simmonds, D. J., and Zacharioudaki, A., 2011. An investigation of the impacts of climate change on wave energy generation: The Wave Hub, Cornwall, UK. Renewable Energy, 36 (9): 2404–2413. DOI: 10.1016/j.renene.2011.02.020.

    Article  Google Scholar 

  • Reguero, B. G., Losada, I. J., and Méndez, F. J., 2015. A global wave power resource and its seasonal, interannual and longterm variability. Applied Energy, 148: 366–380. DOI: 10.1016/j.apenergy.2015.03.114.

    Article  Google Scholar 

  • Rusu, E., and Soares, C. G., 2009. Numerical modelling to estimate the spatial distribution of the wave energy in the Portuguese nearshore. Renewable Energy, 34: 1501–1516. DOI: 10. 1016/j.renene.2008.10.027.

    Article  Google Scholar 

  • Rusu, L., and Soares, C. G., 2012. Wave energy assessments in the Azores islands. Renewable Energy, 45: 183–196. DOI: 10. 1016/j.renene.2012.02.027.

    Article  Google Scholar 

  • Saket, A., and Etemad–Shahidi, A., 2012. Wave energy potential along the northern coasts of the Gulf of Oman, Iran. Renewable Energy, 40: 90–97. DOI: 10.1016/j.renene.2011.09.024.

    Article  Google Scholar 

  • Santo, H., Taylor, P. H., Eatock Taylor, R., and Stansby, P., 2016. Decadal variability of wave power production in the North–East Atlantic and North Sea for the M4 machine. Renewable Energy, 91: 442–450. DOI: 10.1016/j.renene.2016.01.086.

    Article  Google Scholar 

  • Sierra, J. P., Casas–Prat, M., and Campins, E., 2017. Impact of climate change on wave energy resource: The case of Menorca (Spain). Renewable Energy, 101: 275–285. DOI: 10.1016/j.renene.2016.08.060.

    Article  Google Scholar 

  • Sierra, J. P., Martín, C., Mösso, C., Mestres, M., and Jebbad, R., 2016. Wave energy potential along the Atlantic coast of Morocco. Renewable Energy, 96: 20–32. DOI: 10.1016/j.renene. 2016.04.071.

    Article  Google Scholar 

  • Thies, P. R., Smith, G. H., and Johanning, L., 2012. Addressing failure rate uncertainties of marine energy converters. Renewable Energy, 44: 359–367. DOI: http://dx.doi.org/10.1016/j.renene.2012.02.007.

    Article  Google Scholar 

  • Young, I. R., 1999. Wind Generated Ocean Waves. Ocean Engineering Book Series, Vol. 2. Elsevier, Oxford, 92pp.

    Google Scholar 

Download references

Acknowledgements

This research was funded by TÜBITAK (The Scientific and Technological Research Council of Turkey) (No. 112M 413). We thank the European Centre for Medium-Range Weather Forecasts for providing the wind data, the Marine Geoscience Data System for providing the bathymetry data, and Turkish Petroleum for providing the buoy wave data.

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Correspondence to Yasin Abdollahzadehmoradi.

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Abdollahzadehmoradi, Y., Özger, M. & Altunkaynak, A. Optimized Numerical Model Based Assessment of Wave Power Potential of Marmara Sea. J. Ocean Univ. China 18, 293–304 (2019). https://doi.org/10.1007/s11802-019-3826-5

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  • DOI: https://doi.org/10.1007/s11802-019-3826-5

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