Skip to main content

Advertisement

Log in

Marine current energy estimation using the generalized gamma distribution: a case study for the upper layer of the Dardanelles Strait

  • Case Study
  • Published:
Journal of Ocean Engineering and Marine Energy Aims and scope Submit manuscript

Abstract

Sea currents could produce as much energy as wind currents because the average density of the oceans is about 850 times greater than that of air. Being able to accurately predict current power data is of critical importance in extracting the renewable energy potential of a specific ocean region. However, the classical power prediction formulas do not take into account the fluctuations around the mean, or turbulence. Because ocean currents are turbulent, a greater understanding of the existence of turbulence is a key factor in current power estimations. This paper principally investigates the use of the generalized gamma distribution in developing a new current power prediction formula that takes into account deviations from the mean. In addition, mean power and energy fluxes are calculated with the developed formula for the upper layers of the ocean (between 0 and 20 m) at the southern outlet of the Dardanelles as a case study. To estimate mean power and energy fluxes, 3-year hourly time series data with an average current speed of 0.381 m/s are used. Finally, the mean power and the energy fluxes are estimated to be 46.45 W/m2 and 407.23 kWh/m2/year, respectively.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Abundo, M. L., Nerves, A. C., Ang, M. R. C., Paringit, E. C., Bernardo, L. P., and Villanoy, C. L. (2011) Energy potential metric for rapid macro-level resource assessment of tidal in-stream energy in the Philippines. In 2011 10th International Conference on Environment and Electrical Engineering (pp. 1–4). IEEE.

  • Altunkaynak A (2014) Extended wave power formulation by perturbation theory and its applications. Ocean Eng 88:46–54

    Article  Google Scholar 

  • Altunkaynak A, Erdik T, Dabanlı İ, Şen Z (2012) Theoretical derivation of wind power probability distribution function and applications. Appl Energy 92:809–814

    Article  Google Scholar 

  • Ashkar F, Bobée B, Leroux D, Morisette D (1988) The generalized method of moments as applied to the generalized gamma distribution. Stoch Hydrol Hydraul 2(3):161–174

    Article  Google Scholar 

  • Bakker M, Schaars F (2013) Modeling steady sea water intrusion with single-density groundwater codes. Groundwater 51(1):135–144

    Article  Google Scholar 

  • Birdas, M., Srinil, N., and Van den Abeele, F. (2015) Assessment of pipeline walking with coupled triggering mechanisms by finite element approach. In ASME 2015 34th International Conference on Ocean, Offshore and Arctic Engineering

  • Blain CA, Cambazoglu MK, Kourafalou, VH (2009) Modeling the Dardanelles strait outflow plume using a coupled model system. In OCEANS 2009 (pp. 1–8). IEEE.

  • Blue Energy Canada Inc., 2000. Canada. http://www.bluenergy.com

  • Campisi-Pinto S, Gianchandani K, Ashkenazy Y (2020) Statistical tests for the distribution of surface wind and current speeds across the globe. Renewable Energy 149:861–876

    Article  Google Scholar 

  • Cordeiro GM, Ortega EM, Silva GO (2011) The exponentiated generalized gamma distribution with application to lifetime data. J Stat Comput Simul 81(7):827–842

    Article  MathSciNet  Google Scholar 

  • Cox C, Chu H, Schneider MF, Munoz A (2007) Parametric survival analysis and taxonomy of hazard functions for the generalized gamma distribution. Stat Med 26(23):4352–4374

    Article  MathSciNet  Google Scholar 

  • De Pascoa MA, Ortega EM, Cordeiro GM (2011) The Kumaraswamy generalized gamma distribution with application in survival analysis. Statistical Methodol 8(5):411–433

    Article  MathSciNet  Google Scholar 

  • EandPDC (Engineering and Power Development Consultants Ltd.), 1993. Tidal Stream Energy Review, ETSU T/05/00155/REP, United Kingdom.

  • Gomès O, Combes C, Dussauchoy A (2008) Parameter estimation of the generalized gamma distribution. Math Comput Simul 79(4):955–963

    Article  MathSciNet  Google Scholar 

  • Hirose H (2000) Maximum likelihood parameter estimation by model augmentation with applications to the extended four-parameter generalized gamma distribution. Math Comput Simul 54(1–3):81–97

    Article  MathSciNet  Google Scholar 

  • Kanarska Y, Maderich V (2008) Modelling of seasonal exchange flows through the Dardanelles Strait. Estuar Coast Shelf Sci 79(3):449–458

    Article  Google Scholar 

  • Kaplan YA (2015) Overview of wind energy in the world and assessment of current wind energy policies in Turkey. Renew Sustain Energy Rev 43:562–568

    Article  Google Scholar 

  • Khodabina M, Ahmadabadib A (2010) Some properties of generalized gamma distribution. Mathematical Sciences 4:9–28

    MathSciNet  Google Scholar 

  • Lee MQ, Lu CN, Huang HS (2009) Reliability and cost analyses of electricity collection systems of a marine current farm—A Taiwanese case study. Renew Sustain Energy Rev 13(8):2012–2021

    Article  Google Scholar 

  • Lindquist DC, Shaw RF (2005) Effects of current speed and turbidity on stationary light-trap catches of larval and juvenile fishes. Fish Bull 103(2):438–444

    Google Scholar 

  • Liu M, Li W, Wang C, Billinton R, Yu J (2015) Reliability evaluation of a tidal power generation system considering tidal current speeds. IEEE Trans Power Syst 31(4):3179–3188

    Article  Google Scholar 

  • Maur AA (2001) Statistical tools for drop size distributions: Moments and generalized gamma. J Atmos Sci 58(4):407–418

    Article  Google Scholar 

  • Nadarajah S (2008) On the use of the generalised gamma distribution. Int J Electron 95(10):1029–1032

    Article  Google Scholar 

  • Nasab NM, Kilby J, Bakhtiaryfard L (2020) The Potential for integration of wind and tidal power in New Zealand. Sustainability 12(5):1–21

    Google Scholar 

  • Noufaily A, Jones MC (2013) On maximization of the likelihood for the generalized gamma distribution. Comput Statistics 28(2):505–517

    Article  MathSciNet  Google Scholar 

  • Oguz T, Sur HI (1989) A 2-layer model of water exchange through the Dardanelles Strait. Oceanol Acta 12(1):23–31

    Google Scholar 

  • Okorie, P. O., and Owen, A. (2008) Turbulence: Characteristics and its implications in tidal current energy device testing. In OCEANS 2008 (pp. 1–6). IEEE.

  • Ozturk M, Sahin C, Yuksel Y (2017) Current power potential of a sea strait: the bosphorus. Renewable Energy 114:191–203

    Article  Google Scholar 

  • Rama S, Kamlesh Kumar S (2019) A generalization of generalized gamma distribution. Inter J Computational Theoretical Statistics 6(1):34

    Article  Google Scholar 

  • Şen Z (2012) Energy generation possibility from ocean currents: Bosphorus, Istanbul. Ocean Eng 50:31–37

    Article  Google Scholar 

  • Sheng L, Zhou Z, Charpentier JF, Benbouzid MEH (2017) Stand-alone island daily power management using a tidal turbine farm and an ocean compressed air energy storage system. Renewable Energy 103:286–294

    Article  Google Scholar 

  • Stacy EW (1962) A generalization of the gamma distribution. Ann Math Stat 33(3):1187–1192

    Article  MathSciNet  Google Scholar 

  • Stashchuk N, Hutter K (2001) Modelling of water exchange through the strait of the Dardanelles. Cont Shelf Res 21(13–14):1361–1382

    Article  Google Scholar 

  • Twidell J, Weir T (2015) Renewable Energy Resources. Routledge

    Book  Google Scholar 

  • Ünlülata, Ü., Oğuz, T., Latif, M. A., and Özsoy, E. (1990). On the physical oceanography of the Turkish Straits. In The Physical Oceanography of Sea Straits (pp. 25–60). Springer, Dordrecht.

  • Waldman S, Yamaguchi S, Murray RH, Woolf D (2017) Tidal resource and interactions between multiple channels in the Goto Islands, Japan. International Journal of Marine Energy 19:332–344

    Article  Google Scholar 

  • Yaltırak C, Alpar B, Sakınç M, Yüce H (2000) Origin of the Strait of Çanakkale (Dardanelles): regional tectonics and the Mediterranean–Marmara incursion. Mar Geol 164(3–4):139–156

    Article  Google Scholar 

  • Yilmaz H, Sazak HS (2014) Double-looped maximum likelihood estimation for the parameters of the generalized gamma distribution. Math Comput Simul 98:18–30

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

This study was supported by Istanbul Technical University Scientific Research Project Coordination Unit (ITU BAP) with grant number 42373. The authors wish to thank the Turkish State Meteorological Service for providing current velocity data of the Dardanelles Strait. I.C.U. acknowledges the support of Turkish Council of Higher Education (CoHE) for 100/2000 CoHE doctoral scholarship.

Funding

This research was supported by the Istanbul Technical University (ITU) under the BAP Unit (Grant No. 42373).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ismail Can Ulusoy.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ulusoy, I.C., Erdik, T. Marine current energy estimation using the generalized gamma distribution: a case study for the upper layer of the Dardanelles Strait. J. Ocean Eng. Mar. Energy 7, 481–492 (2021). https://doi.org/10.1007/s40722-021-00210-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40722-021-00210-1

Keywords

Navigation