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ESTIMATING WIND ENERGY POTENTIAL WITH PREDICTING BURR LSM PARAMETERS: A DIFFERENT APPROACH

Year 2018, Volume: 36 Issue: 2, 389 - 404, 01.06.2018

Abstract

Estimating wind energy potential and wind speed frequency are important for planning wind energy conversion plants. Probability distribution functions are utilized to model wind speed distributions.
In this study, an estimation was model designed by using the least squares method to predict the wind speed density with the Burr distribution, which has not been studied before. To confirm this model, the annual data of eight different weather stations were analysed, and the results were compared with the Weibull distribution model, which is the most popular one in the literature. For predicting the parameters of both models least square method and maximum likely methods were used. Regarding the comparison results, the performance of designed estimation model (Burr LSM) is higher than the Weibull distribution models, especially for the locations with higher average wind speeds. The results show that the Burr LSM is better than the others for seven of eight weather stations in terms of the power density.

References

  • ⦁ Morgan, EC., Lockner, M., Vogel, RM., Base, LG., (2011). Probability distributions for offshore wind speeds. Energy Conversion and Management, vol. 52, p. 15-56, DOI:10.1016/j.enconman.2010. 06.015
  • ⦁ Ilkılıç, C., Aydin, H., (2015). Wind Power Potential and Usage in the Coastal of regions of Turkey. Renewable and Sustainable Energy Reviews, vol. 44, p. 78-86, DOI:10.1016/j.rser.2014.12.010.
  • ⦁ Installed power capacity of Turkey by sources, from ⦁ www.eie.gov.tr//document/elektrik_kurulu_ guc_kaynaklar_2002_2012.pdf, accessed on 2015. 02. 28.
  • ⦁ Kaplan, YA., (2015). Overview of wind energy in the world and assessment of current wind energy policies in Turkey, Renewable and Sustainable Energy Reviews; vol. 43, p. 562–568, DOI:10.1016/j.rser.2014.11.027.
  • ⦁ Lo Brano, V., Orioli, A., Ciulla, G., Cullata, S., (2011). Quality of wind speed fitting distributions for the urban area of Palermo, Italy, Renewable Energy, vol. 36, p. 1026-1039, DOI:10.1016/j.renene.2010.09.009.
  • ⦁ İnstalled power capacity of Turkey by sources, from ⦁ http://www.emo.org.tr/ekler/18ff249800ead7f _ek.pdf, accessed on 2016.03.28
  • ⦁ Gökçek, M., Bayülken, A., Bekdemir, Ş., (2007). Investigates of Wind Characteristics and Wind Energy Potential in Kırklareli, Turkey. Renewable Energy, vol. 32, p. 1739-1752, DOI:10.1016/j.renene. 2006.11.017
  • ⦁ Akpınar, S., Akpınar, EK., (2009). Estimation of wind energy potential using finite mixture distribution models, Energy Conversion and Management, vol. 50, p. 877-884, DOI:10.1016/j.enconman.2009.01.007.
  • ⦁ Eskin, N., Artar, H., Tolun, S., (2008). Wind energy potential of Gökçeada Island in Turkey. Renewable and Sustainable Energy Reviews, vol. 12, p. 839–851, DOI:10.1016/j.rser.2006.05.016.
  • ⦁ Akdag, SA., Guler, O., (2010 ). Evaluation of wind energy investment interestand electricity generation cost analysis for Turkey. Applied Energy, vol. 87, p. 2574–2580, DOI:10.1016/j.apenergy.2010.03.015.
  • ⦁ Ucar, A., Balo, F., (2009). Evaluation of wind energy potential and electricity generation at six locations in Turkey. Applied Energy, vol. 86, p. 1864–1872,
  • ⦁ Ulgen, K., Hepbasli, A., (2002). Determination of Weibull parameters for wind energy analysis of Izmir, Turkey. International Journal of Energy Research, vol. 26, p. 495–506, DOI:10.1002/er.798
  • ⦁ Fyrippis, I., Axaopoulos, PJ., Panayiotou, G., (2010). Wind energy potential assessment in Naxos Island, Greece. Applied Energy, vol. 87, p. 577–586, DOI:10.1016/j.apenergy.2009.05.031.
  • ⦁ 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, vol. 86, p. 2411–2420, DOI:10.1016/j.apenergy.2009.03.017.
  • ⦁ Weigt, H., (2009). Germany's wind energy: the potential for fossil capacity replacement and cost saving. Applied Energy, vol. 86, p.1857–1863, DOI:10.1016/j.apenergy.2008.11.031.
  • ⦁ Carta, JA., Ramirez, P., Valazquez, S., (2009). A review of wind speed probability distributions used in wind energy analysis case studies in the Canary Islands. Renewable and Sustainable Energy Reviews, vol.13, p. 933-955, DOI:10.1016/j.rser.2008.05.005.
  • ⦁ Mirhosseini, M., Sharifi, F., Sedaghat, A., (2011) Assessing the wind energy potential locations in province of Semnanin Iran. Renewable and Sustainable Energy Reviews, 15, p. 449–505, ⦁ doi:10.1016/j.rser.2010.09.029
  • ⦁ Mostafaeipour, A., Abarghooei, H., (2008) Harnessing wind energy at Manjilarea located in north of Iran. Renewable and Sustainable Energy Reviews, vol. 12:, p. 1758–66, doi:10.1016/j.rser.2007.01.029
  • ⦁ Najafi, G., Ghobadian, B., (2011) LLK 1694-wind energy resources and development in Iran. Renewable and Sustainable Energy Reviews, vol. 15(6), p. 2719–2728, doi:10.1016/j.rser.2011.03.002
  • ⦁ Ghorashi, AH., Rahimi A., (2011) Renewable and non-renewable energy status in Iran: art of know-how and technology-gap. Renewable and Sustainable Energy Reviews, vol. 15(1), p. 729–736, doi:10.1016/j.rser.2010.09.037
  • ⦁ Bakhoda, H., Almassi, M., Moharamnejad, N., Moghaddasi, R., Azkia, M., (2012) Energy production trend in Iran and its effect on sustainable development. Renewable and Sustainable Energy Reviews, vol. 16(2) p. 1335–9, doi:10.1016/j.rser.2011.10.014
  • ⦁ Alamdari, P., Nematollahi, O., Mirhosseini, M., (2012) Assessment of wind energy in Iran: a review. Renewable and Sustainable Energy Reviews, vol. 16(1), p. 836–60, doi:10.1016/j.rser.2011.09.007
  • ⦁ Mostafaeipour, A., Jadidi, M., Mohammadi, K., Sedaghat, A., (2014) An analysis of wind energy potential and economic evaluation in Zahedan, Iran. Renewable and Sustainable Energy Reviews, vol. 30, p. 641–650, ⦁ doi:10.1016/j.rser.2013.11.016
  • ⦁ Elhadidy, MA., Shaahid, SM., (1999) Feasibility of hybrid (Wind-Solar) power systems for Dhahran, Saudi Arabia. Renewable Energy, vol. 16, p. 970–976, ⦁ doi:10.1016/S0960-1481(98)00344-9
  • ⦁ Almalki, SJ., Nadarajah, S., (2014) Modifications of the Weibull distribution: A review. Reliability Engineering and System Safety, vol. 124, p. 32–55, doi:10.1016/j.ress.2013.11.010
  • ⦁ Wang, J., Qin, S., Jin, S., Wu, J., (2015) Estimation methods review and analysis of offshore extreme wind speeds and wind energy resources. Renewable and Sustainable Energy Reviews, vol. 42, p. 26–42, ⦁ doi:10.1016/j.rser.2014.09.042
  • ⦁ Arslan T., Bulut YM., Yavuz, AA., (2014) Comparative study of numerical methods for determining Weibull parameters for wind energy potential. Renewable and Sustainable Energy Reviews, vol. 40, p. 820–825, DOI:10.1016/j.rser.2014.08.009
  • ⦁ Genç, A., Erisoğlu, M., Pekgör, A., Oturanc, G., Hepbaşlı, A., Ülgen, K., (2005) Estimation of Wind Power Potential Using Weibull Distribution. Energy Sources, vol. 27, p.809-822, doi: 10.1080/00908310490450647
  • ⦁ Ramirez, P. Carta, J.A., The use of wind probability distributions derived from the maximum entropy principle in the analysis of wind energy. A case study, Energy Convers Manag, 47 (2006), pp. 2564–2577
  • ⦁ The measurement standards. MGM, from http://www.mgm.gov.tr/FILES/Haberler/2012/ruzgargunesteblig2012-01.pdf, accessed on 2015.03.15
  • ⦁ Akpınar, S., Akpınar, EK., (2007) Wind energy analysis based on maximum entropy principle (MEP)-type distribution function. Energy Conversion and Management, vol. 48, p. 1140-1149, DOI:10.1016/j.enconman.2006.10.004
  • ⦁ Ozdamar A., Gursel KT., Orer G., Pekbey Y., (2004) Investigation of the potential of wind–waves as a renewable energy resource: by the example of Cesme—Turkey. Renewable and Sustainable Energy Reviews, vol. 8, p. 581–592, DOI:10.1016/ j.rser.2004.01.007
  • ⦁ Kara, Ö., Özdamar, A., Ülgen, K., (2001) Rüzgar Hızlarının Daha Yükseğe Taşınmasında Hellmann Katsayısının Değişimi Üzerine Bir Araştırma: Söke Örneği, VI. Türk-Alman Enerji Sempozyumu Kitapçığı, p.435-440, İzmir, 21-24 Haziran 2001.
  • ⦁ http://www.koski.gov.tr/ (accessed on 10.09.2016)
  • ⦁ http://www.emo.org.tr/ekler/dc375089b790ef9_ek.pdf (accessed on 15.09.2016)
  • ⦁ Yaniktepe, B., T. Koroglu, and M. M. Savrun. 2013. “Investigation of Wind Characteristics and Wind Energy Potential in Osmaniye, Turkey.”Renewable and Sustainable Energy Reviews 21: 703–711. doi:10.1016/j.rser.2013.01.005.
There are 36 citations in total.

Details

Primary Language English
Journal Section Research Articles
Authors

Bayram Köse This is me 0000-0003-0256-5921

Murat Düz This is me 0000-0003-2387-4045

M. Tahir Güneşer This is me 0000-0003-3502-2034

Ziyaddin Recebli This is me 0000-0003-3110-9423

Publication Date June 1, 2018
Submission Date September 5, 2017
Published in Issue Year 2018 Volume: 36 Issue: 2

Cite

Vancouver Köse B, Düz M, Güneşer MT, Recebli Z. ESTIMATING WIND ENERGY POTENTIAL WITH PREDICTING BURR LSM PARAMETERS: A DIFFERENT APPROACH. SIGMA. 2018;36(2):389-404.

IMPORTANT NOTE: JOURNAL SUBMISSION LINK https://eds.yildiz.edu.tr/sigma/