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Statistical analysis of wind characteristics based on Weibull methods for estimation of power generation in Lithuania

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  • Katinas, Vladislovas
  • Marčiukaitis, Mantas
  • Gecevičius, Giedrius
  • Markevičius, Antanas

Abstract

The study analyzes application of Weibull probability distribution methodologies by summarizing wind power density in selected locations. Reliability of determination of Weibull probability density function of shape k and scale c parameters has been analyzed by means of eight methods. For the assessment of reliability of the methodology, root mean square error, coefficient of determination, chi-square test and relative error were calculated. Measurements of wind characteristics have been carried out in the coastal and continental part of the Lithuania. It has been determined that many calculation methods of the probability density function allow obtaining quite reliable results. However, depending on the geographical location of the area, the height from the ground level, and the influence of other factors on the wind power density, some methods are not acceptable, as they give over-large (up 13.44% and more) relative errors.

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  • Katinas, Vladislovas & Marčiukaitis, Mantas & Gecevičius, Giedrius & Markevičius, Antanas, 2017. "Statistical analysis of wind characteristics based on Weibull methods for estimation of power generation in Lithuania," Renewable Energy, Elsevier, vol. 113(C), pages 190-201.
  • Handle: RePEc:eee:renene:v:113:y:2017:i:c:p:190-201
    DOI: 10.1016/j.renene.2017.05.071
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    as
    1. Ahmed Shata, A.S. & Hanitsch, R., 2008. "Electricity generation and wind potential assessment at Hurghada, Egypt," Renewable Energy, Elsevier, vol. 33(1), pages 141-148.
    2. Yaniktepe, B. & Koroglu, T. & Savrun, M.M., 2013. "Investigation of wind characteristics and wind energy potential in Osmaniye, Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 703-711.
    3. Ayodele, T.R. & Ogunjuyigbe, A.S.O., 2016. "Wind energy potential of Vesleskarvet and the feasibility of meeting the South African׳s SANAE IV energy demand," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 226-234.
    4. Feijóo, Andrés & Villanueva, Daniel, 2016. "Assessing wind speed simulation methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 473-483.
    5. El Alimi, Souheil & Maatallah, Taher & Dahmouni, Anouar Wajdi & Ben Nasrallah, Sassi, 2012. "Modeling and investigation of the wind resource in the gulf of Tunis, Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5466-5478.
    6. Sinden, Graham, 2007. "Characteristics of the UK wind resource: Long-term patterns and relationship to electricity demand," Energy Policy, Elsevier, vol. 35(1), pages 112-127, January.
    7. Ucar, Aynur & Balo, Figen, 2009. "Evaluation of wind energy potential and electricity generation at six locations in Turkey," Applied Energy, Elsevier, vol. 86(10), pages 1864-1872, October.
    8. Chang, Tsang-Jung & Wu, Yu-Ting & Hsu, Hua-Yi & Chu, Chia-Ren & Liao, Chun-Min, 2003. "Assessment of wind characteristics and wind turbine characteristics in Taiwan," Renewable Energy, Elsevier, vol. 28(6), pages 851-871.
    9. Safari, Bonfils & Gasore, Jimmy, 2010. "A statistical investigation of wind characteristics and wind energy potential based on the Weibull and Rayleigh models in Rwanda," Renewable Energy, Elsevier, vol. 35(12), pages 2874-2880.
    10. Chang, Tian Pau, 2011. "Performance comparison of six numerical methods in estimating Weibull parameters for wind energy application," Applied Energy, Elsevier, vol. 88(1), pages 272-282, January.
    11. Abul Kalam Azad & Mohammad Golam Rasul & Talal Yusaf, 2014. "Statistical Diagnosis of the Best Weibull Methods for Wind Power Assessment for Agricultural Applications," Energies, MDPI, vol. 7(5), pages 1-30, May.
    12. Mostafaeipour, Ali & Sedaghat, Ahmad & Ghalishooyan, Morteza & Dinpashoh, Yagob & Mirhosseini, Mojtaba & Sefid, Mohammad & Pour-Rezaei, Maryam, 2013. "Evaluation of wind energy potential as a power generation source for electricity production in Binalood, Iran," Renewable Energy, Elsevier, vol. 52(C), pages 222-229.
    13. Gualtieri, Giovanni & Secci, Sauro, 2012. "Methods to extrapolate wind resource to the turbine hub height based on power law: A 1-h wind speed vs. Weibull distribution extrapolation comparison," Renewable Energy, Elsevier, vol. 43(C), pages 183-200.
    14. Lun, Isaac Y.F & Lam, Joseph C, 2000. "A study of Weibull parameters using long-term wind observations," Renewable Energy, Elsevier, vol. 20(2), pages 145-153.
    15. Himri, Y. & Himri, S. & Stambouli, A. Boudghene, 2010. "Wind power resource in the south-western region of Algeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(1), pages 554-556, January.
    16. Weekes, S.M. & Tomlin, A.S., 2014. "Data efficient measure-correlate-predict approaches to wind resource assessment for small-scale wind energy," Renewable Energy, Elsevier, vol. 63(C), pages 162-171.
    17. 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, Elsevier, vol. 44(1), pages 710-719.
    18. Weisser, D, 2003. "A wind energy analysis of Grenada: an estimation using the ‘Weibull’ density function," Renewable Energy, Elsevier, vol. 28(11), pages 1803-1812.
    19. Dahmouni, A.W. & Ben Salah, M. & Askri, F. & Kerkeni, C. & Ben Nasrallah, S., 2011. "Assessment of wind energy potential and optimal electricity generation in Borj-Cedria, Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 815-820, January.
    Full references (including those not matched with items on IDEAS)

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