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Estimation of wind speed profile using adaptive neuro-fuzzy inference system (ANFIS)

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  • Mohandes, M.
  • Rehman, S.
  • Rahman, S.M.

Abstract

Wind energy has become a major competitor of traditional fossil fuel energy, particularly with the successful operation of multi-megawatt sized wind turbines. However, wind with reasonable speed is not adequately sustainable everywhere to build an economical wind farm. The potential site has to be thoroughly investigated at least with respect to wind speed profile and air density. Wind speed increases with height, thus an increase of the height of turbine rotor leads to more generated power. Therefore, it is imperative to have a precise knowledge of wind speed profiles in order to assess the potential for a wind farm site. This paper proposes a clustering algorithm based neuro-fuzzy method to find wind speed profile up to height of 100m based on knowledge of wind speed at heights 10, 20, 30, 40m. The model estimated wind speed at 40m based on measured data at 10, 20, and 30m has 3% mean absolute percent error when compared with measured wind speed at height 40m. This close agreement between estimated and measured wind speed at 40m indicates the viability of the proposed method. The comparison with the 1/7th law and experimental wind shear method further proofs the suitability of the proposed method for generating wind speed profile based on knowledge of wind speed at lower heights.

Suggested Citation

  • Mohandes, M. & Rehman, S. & Rahman, S.M., 2011. "Estimation of wind speed profile using adaptive neuro-fuzzy inference system (ANFIS)," Applied Energy, Elsevier, vol. 88(11), pages 4024-4032.
    • Handle: RePEc:eee:appene:v:88:y:2011:i:11:p:4024-4032
    DOI: 10.1016/j.apenergy.2011.04.015
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    1. 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," Applied Energy, Elsevier, vol. 86(11), pages 2411-2420, November.
    2. Rehman, S. & El-Amin, I.M. & Ahmad, F. & Shaahid, S.M. & Al-Shehri, A.M. & Bakhashwain, J.M., 2007. "Wind power resource assessment for Rafha, Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(5), pages 937-950, June.
    3. Fadare, D.A., 2010. "The application of artificial neural networks to mapping of wind speed profile for energy application in Nigeria," Applied Energy, Elsevier, vol. 87(3), pages 934-942, March.
    4. Ilinca, Adrian & McCarthy, Ed & Chaumel, Jean-Louis & Rétiveau, Jean-Louis, 2003. "Wind potential assessment of Quebec Province," Renewable Energy, Elsevier, vol. 28(12), pages 1881-1897.
    5. Ucar, Aynur & Balo, Figen, 2009. "Investigation of wind characteristics and assessment of wind-generation potentiality in Uludag-Bursa, Turkey," Applied Energy, Elsevier, vol. 86(3), pages 333-339, March.
    6. Dvorak, Michael J. & Archer, Cristina L. & Jacobson, Mark Z., 2010. "California offshore wind energy potential," Renewable Energy, Elsevier, vol. 35(6), pages 1244-1254.
    7. Rehman, Shafiqur & Al-Abbadi, Naif M., 2007. "Wind shear coefficients and energy yield for Dhahran, Saudi Arabia," Renewable Energy, Elsevier, vol. 32(5), pages 738-749.
    8. Al-Nassar, W. & Alhajraf, S. & Al-Enizi, A. & Al-Awadhi, L., 2005. "Potential wind power generation in the State of Kuwait," Renewable Energy, Elsevier, vol. 30(14), pages 2149-2161.
    9. Marafia, A-Hamid & Ashour, Hamdy A., 2003. "Economics of off-shore/on-shore wind energy systems in Qatar," Renewable Energy, Elsevier, vol. 28(12), pages 1953-1963.
    10. Ajayi, Oluseyi O., 2009. "Assessment of utilization of wind energy resources in Nigeria," Energy Policy, Elsevier, vol. 37(2), pages 750-753, February.
    11. Rehman, Shafiqur & Halawani, Talal Omar, 1994. "Statistical characteristics of wind in Saudi Arabia," Renewable Energy, Elsevier, vol. 4(8), pages 949-956.
    12. Morales, J.M. & Mínguez, R. & Conejo, A.J., 2010. "A methodology to generate statistically dependent wind speed scenarios," Applied Energy, Elsevier, vol. 87(3), pages 843-855, March.
    13. Raichle, Brian W. & Carson, W. Richard, 2009. "Wind resource assessment of the Southern Appalachian Ridges in the Southeastern United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(5), pages 1104-1110, June.
    14. Oliver Probst & Diego Cárdenas, 2010. "State of the Art and Trends in Wind Resource Assessment," Energies, MDPI, vol. 3(6), pages 1-55, June.
    15. Li, Gong & Shi, Jing, 2010. "On comparing three artificial neural networks for wind speed forecasting," Applied Energy, Elsevier, vol. 87(7), pages 2313-2320, July.
    16. Painuly, J.P, 2001. "Barriers to renewable energy penetration; a framework for analysis," Renewable Energy, Elsevier, vol. 24(1), pages 73-89.
    17. Ahmed Shata, A.S. & Hanitsch, R., 2006. "The potential of electricity generation on the east coast of Red Sea in Egypt," Renewable Energy, Elsevier, vol. 31(10), pages 1597-1615.
    18. Kaldellis, J.K. & Kavadias, K.A. & Filios, A.E., 2009. "A new computational algorithm for the calculation of maximum wind energy penetration in autonomous electrical generation systems," Applied Energy, Elsevier, vol. 86(7-8), pages 1011-1023, July.
    19. Ammari, H.D. & Al-Maaitah, A., 2003. "Assessment of wind-generation potentiality in Jordan using the site effectiveness approach," Energy, Elsevier, vol. 28(15), pages 1579-1592.
    20. Pinson, P. & Nielsen, H.Aa. & Madsen, H. & Kariniotakis, G., 2009. "Skill forecasting from ensemble predictions of wind power," Applied Energy, Elsevier, vol. 86(7-8), pages 1326-1334, July.
    21. Luickx, Patrick J. & Delarue, Erik D. & D'haeseleer, William D., 2008. "Considerations on the backup of wind power: Operational backup," Applied Energy, Elsevier, vol. 85(9), pages 787-799, September.
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