Evaluation of wind potential and its trends in the mid-Atlantic

Abstract

This work utilized a 37-year (1980–2016) 10 m wind field dataset got from the European Center for Medium Range Weather Forecast (ECMWF) to examine the wind energy potential in the mid-Atlantic by using the Weibull parameters. The region generally showed a fairly good wind characteristics. The computed annual average wind power (170.23 w/m2) attributes the region as fairly suitable for wind power applications. Furthermore, locations such as State of Ceara and Sao Vicente in the southern and northern mid-Atlantic exhibits higher wind power of approximately 330 w/m2 and are therefore suitable for grid connected wind power applications. In all years and seasons, increasing positive trends in wind power density dominate waters between States of Ceara and Amapa in the southern mid-Atlantic. The wind power density showed an increasing trend of 0.13 w/m2/year in the mid-Atlantic throughout the study period. The trend inclined (1.1 w/m2/year) in winter and declined (− 0.51 w/m2/year) during summer.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19

References

  1. Ahmed AS (2012) Investigation potential wind power generation in South Egypt. J Renew Sustain Energy Rev 16 1528–1536

    Article  Google Scholar 

  2. Ahmed Shata AS, Hanitsch R (2006) The potential of electricity generation on the east coasts on Red Sea in Egypt. Renew Energy 31(10):1597–1615

    Article  Google Scholar 

  3. Akdag SA, Dinler A (2009) A new method to estimate Weibull parameters for wind energy applications. Energy Convers Manage 50(7):1761–1766

    Article  Google Scholar 

  4. Al-Nhoud O, Al-Smairan M (2015) Assessment of wind energy potential as a power generation source in the Azraq South, Northeast Badia, Jordan. Modern Mech Eng 5:87–96. https://doi.org/10.4236/mme.2015.53008

    Article  Google Scholar 

  5. Ammari HD, Maaitah A (2003) Assessment of wind-generation potentiality inJordan using the site effectiveness approach. Energy 28:1579–1592

    Article  Google Scholar 

  6. Bagiorgas HS, Mihalakakou G, Rehman S, AlHadhrami LM (2012) Offshore wind speed and wind power characteristics for ten locations in Aegean and Ionian Seas. J Earth Syst Sci 121(4):975–987

    Article  Google Scholar 

  7. Bailey B, Brennan S, Kinal B, Markus M, Kreiselman J (2002) Long Islands offshore wind energy development potential: phase 1. preliminary, assessment, AWS Scientific

  8. Buflasa HA, Infield Watson S, Thomson M (2008) Wind resource assessment for the Kingdom of Bahrain. Wind Eng 32(5):439–448

    Article  Google Scholar 

  9. Buhairi MHA (2006) A statistical analysis of wind speed data and an assessment of wind energy potential in Taiz-Yemen. Environ Res 9(2):13–21

    Google Scholar 

  10. Dvorak MJ, Archer CL, Jacobson MZ (2009) California offshore wind energy potential. Renew Energy. https://doi.org/10.1016/j.renene.2009.11.022

    Google Scholar 

  11. Elamouri M, Amar FB (2008) Wind energy potential in Tunisia. Renew Energy 33:758–768

    Article  Google Scholar 

  12. Elliott D, Schwartz M (1993) Wind energy potential in the United States. Pacific Northwest Laboratory PNL-SA-23109, Richland, WA

  13. El-Osta W, Califa Y (2003) Prospects of wind power plants in Libya: A case study. Renew Energy 28:363–371

    Article  Google Scholar 

  14. Essa KSM, Mubarak F (2006) Survey and assessment of wind-speed and wind-power inEgypt including air density variation. Wind Eng 30(2):95–106

    Article  Google Scholar 

  15. EWEA (2010) Statistics, Offshore and eastern Europe new growth drivers for wind power in Europe, http://www.ewea.org/index .php?id = 60&no cache = 1&tx ttnews[tt news] = 1896&tx ttnews [backPid] = 1&cHash = 8b64626e4bf6996eea71ec3c08994b0a

  16. Fyrippis I, Axaopoulos PJ, Panayiotou G (2010) Wind energy potential assessment in Naxos Island. Greece Appl Energy 87(2):577–586

    Article  Google Scholar 

  17. Gökçek M, Bayülken A, Bekdemir S (2007) Investigation of wind characteristics and wind energy potential in Kirklareli, Turkey. Renew Energy 32(10):1739–1752

    Article  Google Scholar 

  18. Jamil M, Parsa S, Majidi M (1995) Wind power statistics and evaluation of wind energy density. Renew Energ 6(5–6):623–628

    Article  Google Scholar 

  19. Justus C, Hargraves W, Mikhail A, Graber D (1978) Methods for estimating wind speed frequency distributions. J Appl Meteorol 17(3):350–353

    Article  Google Scholar 

  20. Karamanis D, Tsabaris C, Stamoulis K, Georgopoulos D (2011) Wind energy resources in the Ionian Sea. Renew Energy 36(2):815–822

    Article  Google Scholar 

  21. Khan JK, Ahmed F, Uddin Z, Iqbal ST, Saif UJ, Siddiqui AA, Aijaz A (2015) Determination of Weibull parameter by four numerical methods and prediction of wind speed in Jiwani (Balochistan). J Basic Appl Sci 11:62–68. https://doi.org/10.6000/1927-5129.2015.11.08

    Article  Google Scholar 

  22. Manwell JF, McGowan JG, Rogers AL (2002) Wind energy explained: theory, design and application, Amherst (USA). Wiley, Hoboken

    Google Scholar 

  23. Marafia AH, Ashour HA (2003) Economics of off-shore/on-shore wind energy systems in Qatar. Renew Energy 28:1953–1963

    Article  Google Scholar 

  24. Menendez M, Garcıa-Diez M, Fita L, Fernandez J, Mendez FJ, Gutierrez JM (2014) High-resolution sea wind hindcasts over the Mediterranean area. Clim Dyn 42:1857–1872. https://doi.org/10.1007/s00382-013-1912-8

    Article  Google Scholar 

  25. Ohunakin O, Adaramola M, Oyewola O (2011) Wind energy evaluation for electricity generation using WECS in seven selected locations in Nigeria. Appl Energy 88(9):3197–3206

    Article  Google Scholar 

  26. Onea F, Raileanu A, Rusu E (2015) Evaluation of the wind energy potential in the coastal environment of two enclosed seas. Adv Meteorol 2015:14

    Article  Google Scholar 

  27. Osinowo AA, Lin X, Zhao D, Wang Z (2016) Wind energy potentials and its trend in the South China Sea. Energy Environ Res 6(2):36 (ISSN 1927–0569, E-ISSN 1927–0577)

    Article  Google Scholar 

  28. Osinowo AA, Lin X, Zhao D, Zheng K (2017) On the wind energy resource and its trend in the East China Sea. J Renew Energy 2017:14. https://doi.org/10.1155/2017/9643130 (Hindawi Publishing Corporation)

    Google Scholar 

  29. Rinne H (2010) The Weibull distribution: a handbook. CRC Press, Boca Raton

    Google Scholar 

  30. Rose S, Jaramillo P, Small MJ, Grossmann I, Apt J (2011) Quantifying the hurricane risk to offshore wind turbines. Proc Natl Acad Sci USA 109:3247–3252. https://doi.org/10.1073/pnas.1111769109

    Article  Google Scholar 

  31. Saleh H, Abou El-Azm Aly A, Abdel-Hady S (2012) Assessment of different methods used to estimate Weibull distribution parameters for wind speed in Zafarana wind farm, Suez Gulf, Egypt. Energy 44(1):710–719

    Article  Google Scholar 

  32. Sathyajith M (2006) Wind energy: fundamentals, resource analysis and economics. Springer, Berlin

    Google Scholar 

  33. Stevens M, Smulders P (1979) The estimation of the parameters of the Weibull wind speed distribution for wind energy utilization purposes. Wind Eng 3:132–145

    Google Scholar 

  34. Tchinda R, Kendjio J, Kaptouom E, Njomo D (2000) Estimation of mean wind energy available in far north Cameroon. Energy Convers Manage 41(17):1917–1929

    Article  Google Scholar 

  35. Wilks DS (1995) Statistical methods in the atmospheric sciences: an introduction. Academic Press, San Diego

    Google Scholar 

  36. Xydis G, Koroneos C, Loizidou M (2009) Exergy analysis in a wind speed prognostic model as a wind farm sitting selection tool: a case study in Southern Greece. Appl Energy 86(11):2411–2420

    Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Adekunle Ayodotun Osinowo.

Ethics declarations

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Osinowo, A.A., Okogbue, E.C., Eresanya, E.O. et al. Evaluation of wind potential and its trends in the mid-Atlantic. Model. Earth Syst. Environ. 3, 1199–1213 (2017). https://doi.org/10.1007/s40808-017-0399-4

Download citation

Keywords

  • Wind power
  • Weibull
  • Trend
  • Potentials
  • Region
  • Variation