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Wind turbine selection method based on the statistical analysis of nominal specifications for estimating the cost of energy

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  • Arias-Rosales, Andrés
  • Osorio-Gómez, Gilberto

Abstract

Wind turbine selection is a critical engineering problem in the overall cost-effectiveness of a wind project. With the wide spreading and democratization of wind energy technologies, non-expert stakeholders are being faced with the challenge of selecting among very different wind turbines. As a comprehensive indicator, the cost of energy can serve as a guide, but reportedly misleading publicity and commonly unavailable information render its calculation more inaccessible and less reliable. Accordingly, this work proposes a method to compare wind turbines, on the basis of the cost of energy, from only nominal specifications and a standard characterization of the local wind conditions. For this endeavor, it was identified that two key variables are not usually available at a preliminary stage: the total efficiency and a feasible hub height. Through a systematic statistical analysis of the trends in a constructed dataset of 176 turbines, it was possible to establish regression models for the estimation of both variables. These models were tested in a validation set and their estimations were found to correctly characterize the central trend of the data without significant deviations. The uncertainty related to the use of both models was addressed by analyzing the 95% Prediction Intervals and the stochastic rank dominance. The established statistical models were then used as the core of the proposed selection method. When the available information is limited or not trustworthy, the steps of the method can be followed as an approach to estimate the cost of energy of a given horizontal axis wind turbine in a given location.

Suggested Citation

  • Arias-Rosales, Andrés & Osorio-Gómez, Gilberto, 2018. "Wind turbine selection method based on the statistical analysis of nominal specifications for estimating the cost of energy," Applied Energy, Elsevier, vol. 228(C), pages 980-998.
    • Handle: RePEc:eee:appene:v:228:y:2018:i:c:p:980-998
    DOI: 10.1016/j.apenergy.2018.06.103
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    as
    1. Alexis Dinno, 2015. "Nonparametric pairwise multiple comparisons in independent groups using Dunn's test," Stata Journal, StataCorp LP, vol. 15(1), pages 292-300, March.
    2. Jowder, Fawzi A.L., 2009. "Wind power analysis and site matching of wind turbine generators in Kingdom of Bahrain," Applied Energy, Elsevier, vol. 86(4), pages 538-545, April.
    3. 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.
    4. Aslam Bhutta, Muhammad Mahmood & Hayat, Nasir & Farooq, Ahmed Uzair & Ali, Zain & Jamil, Sh. Rehan & Hussain, Zahid, 2012. "Vertical axis wind turbine – A review of various configurations and design techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(4), pages 1926-1939.
    5. Alam, Md. Mahbub & Rehman, Shafiqur & Meyer, Josua P. & Al-Hadhrami, Luai M., 2011. "Review of 600–2500kW sized wind turbines and optimization of hub height for maximum wind energy yield realization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(8), pages 3839-3849.
    6. Díaz, Santiago & Carta, José A. & Matías, José M., 2018. "Performance assessment of five MCP models proposed for the estimation of long-term wind turbine power outputs at a target site using three machine learning techniques," Applied Energy, Elsevier, vol. 209(C), pages 455-477.
    7. Ederer, Nikolaus, 2014. "The right size matters: Investigating the offshore wind turbine market equilibrium," Energy, Elsevier, vol. 68(C), pages 910-921.
    8. Mirhosseini, M. & Sharifi, F. & Sedaghat, A., 2011. "Assessing the wind energy potential locations in province of Semnan in Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 449-459, January.
    9. Sedaghat, Ahmad & Hassanzadeh, Arash & Jamali, Jamaloddin & Mostafaeipour, Ali & Chen, Wei-Hsin, 2017. "Determination of rated wind speed for maximum annual energy production of variable speed wind turbines," Applied Energy, Elsevier, vol. 205(C), pages 781-789.
    10. Perkin, Samuel & Garrett, Deon & Jensson, Pall, 2015. "Optimal wind turbine selection methodology: A case-study for Búrfell, Iceland," Renewable Energy, Elsevier, vol. 75(C), pages 165-172.
    11. Lins, Isis Didier & Droguett, Enrique López & Moura, Márcio das Chagas & Zio, Enrico & Jacinto, Carlos Magno, 2015. "Computing confidence and prediction intervals of industrial equipment degradation by bootstrapped support vector regression," Reliability Engineering and System Safety, Elsevier, vol. 137(C), pages 120-128.
    12. Dai, Kaoshan & Bergot, Anthony & Liang, Chao & Xiang, Wei-Ning & Huang, Zhenhua, 2015. "Environmental issues associated with wind energy – A review," Renewable Energy, Elsevier, vol. 75(C), pages 911-921.
    13. EL-Shimy, M., 2010. "Optimal site matching of wind turbine generator: Case study of the Gulf of Suez region in Egypt," Renewable Energy, Elsevier, vol. 35(8), pages 1870-1878.
    14. Vasel-Be-Hagh, Ahmadreza & Archer, Cristina L., 2017. "Wind farm hub height optimization," Applied Energy, Elsevier, vol. 195(C), pages 905-921.
    15. Fazelpour, Farivar & Soltani, Nima & Soltani, Sina & Rosen, Marc A., 2015. "Assessment of wind energy potential and economics in the north-western Iranian cities of Tabriz and Ardabil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 87-99.
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    2. Al-Masri, Hussein M.K. & AbuElrub, Ahmad & Almehizia, Abdullah A. & Ehsani, Mehrdad, 2019. "Multi-figure of merit optimization for global scale sustainable power systems," Renewable Energy, Elsevier, vol. 134(C), pages 538-549.
    3. Longfu Luo & Xiaofeng Zhang & Dongran Song & Weiyi Tang & Jian Yang & Li Li & Xiaoyu Tian & Wu Wen, 2018. "Optimal Design of Rated Wind Speed and Rotor Radius to Minimizing the Cost of Energy for Offshore Wind Turbines," Energies, MDPI, vol. 11(10), pages 1-17, October.
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    6. Mytilinou, Varvara & Kolios, Athanasios J., 2019. "Techno-economic optimisation of offshore wind farms based on life cycle cost analysis on the UK," Renewable Energy, Elsevier, vol. 132(C), pages 439-454.

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