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A mathematical approach to minimizing the cost of energy for large utility wind turbines

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  • Chen, Jincheng
  • Wang, Feng
  • Stelson, Kim A.

Abstract

With the aim of reducing green gas emission, wind turbine installations worldwide have grown rapidly in recent years. Wind energy itself is free, but has costs due to the wind turbine infrastructure and maintenance. The installation size of the wind turbine at a specific location is not only determined by the wind statistics at that location, but also by the turbine infrastructure and the maintenance cost. The payback time of the turbine is determined by the turbine cost of energy (COE). In this paper, a mathematical approach is proposed to minimize the turbine cost of energy based on wind statistics. Turbine annual energy production (AEP) is calculated based on turbine output power and annual wind speed distribution. A wind turbine cost model developed by U.S. National Renewable Energy Laboratory (NREL) is used for turbine cost analysis. The turbine cost of energy model includes the turbine rated power and the turbine rated wind speed. Finally a general guideline to minimize the turbine COE is presented. Three case studies are conducted to show the effectiveness of the proposed approach.

Suggested Citation

  • Chen, Jincheng & Wang, Feng & Stelson, Kim A., 2018. "A mathematical approach to minimizing the cost of energy for large utility wind turbines," Applied Energy, Elsevier, vol. 228(C), pages 1413-1422.
    • Handle: RePEc:eee:appene:v:228:y:2018:i:c:p:1413-1422
    DOI: 10.1016/j.apenergy.2018.06.150
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    as
    1. Albadi, M.H. & El-Saadany, E.F., 2010. "Optimum turbine-site matching," Energy, Elsevier, vol. 35(9), pages 3593-3602.
    2. Taslimi-Renani, Ehsan & Modiri-Delshad, Mostafa & Elias, Mohamad Fathi Mohamad & Rahim, Nasrudin Abd., 2016. "Development of an enhanced parametric model for wind turbine power curve," Applied Energy, Elsevier, vol. 177(C), pages 544-552.
    3. Gao, Xiaoxia & Yang, Hongxing & Lu, Lin, 2014. "Study on offshore wind power potential and wind farm optimization in Hong Kong," Applied Energy, Elsevier, vol. 130(C), pages 519-531.
    4. Diaf, S. & Notton, G. & Belhamel, M. & Haddadi, M. & Louche, A., 2008. "Design and techno-economical optimization for hybrid PV/wind system under various meteorological conditions," Applied Energy, Elsevier, vol. 85(10), pages 968-987, October.
    5. Oscar Barambones, 2012. "Sliding Mode Control Strategy for Wind Turbine Power Maximization," Energies, MDPI, vol. 5(7), pages 1-21, July.
    6. Feng, Ju & Shen, Wen Zhong, 2017. "Design optimization of offshore wind farms with multiple types of wind turbines," Applied Energy, Elsevier, vol. 205(C), pages 1283-1297.
    7. Chang, Tian-Pau & Liu, Feng-Jiao & Ko, Hong-Hsi & Cheng, Shih-Ping & Sun, Li-Chung & Kuo, Shye-Chorng, 2014. "Comparative analysis on power curve models of wind turbine generator in estimating capacity factor," Energy, Elsevier, vol. 73(C), pages 88-95.
    8. 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.
    9. Saidur, R. & Islam, M.R. & Rahim, N.A. & Solangi, K.H., 2010. "A review on global wind energy policy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(7), pages 1744-1762, September.
    10. Pinar Pérez, Jesús María & García Márquez, Fausto Pedro & Tobias, Andrew & Papaelias, Mayorkinos, 2013. "Wind turbine reliability analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 463-472.
    11. Capuzzi, M. & Pirrera, A. & Weaver, P.M., 2014. "A novel adaptive blade concept for large-scale wind turbines. Part I: Aeroelastic behaviour," Energy, Elsevier, vol. 73(C), pages 15-24.
    12. Chowdhury, Souma & Zhang, Jie & Messac, Achille & Castillo, Luciano, 2013. "Optimizing the arrangement and the selection of turbines for wind farms subject to varying wind conditions," Renewable Energy, Elsevier, vol. 52(C), pages 273-282.
    13. 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.
    14. Kaplan, Yusuf Alper, 2015. "Overview of wind energy in the world and assessment of current wind energy policies in Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 562-568.
    15. Thapar, Vinay & Agnihotri, Gayatri & Sethi, Vinod Krishna, 2011. "Critical analysis of methods for mathematical modelling of wind turbines," Renewable Energy, Elsevier, vol. 36(11), pages 3166-3177.
    16. Shen, Xin & Chen, Jin-Ge & Zhu, Xiao-Cheng & Liu, Peng-Yin & Du, Zhao-Hui, 2015. "Multi-objective optimization of wind turbine blades using lifting surface method," Energy, Elsevier, vol. 90(P1), pages 1111-1121.
    17. Savino, Matteo M. & Manzini, Riccardo & Della Selva, Vincenzo & Accorsi, Riccardo, 2017. "A new model for environmental and economic evaluation of renewable energy systems: The case of wind turbines," Applied Energy, Elsevier, vol. 189(C), pages 739-752.
    18. 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.
    19. Kusiak, Andrew & Zheng, Haiyang & Song, Zhe, 2009. "On-line monitoring of power curves," Renewable Energy, Elsevier, vol. 34(6), pages 1487-1493.
    20. Ulas Eminoglu & Saffet Ayasun, 2014. "Modeling and Design Optimization of Variable-Speed Wind Turbine Systems," Energies, MDPI, vol. 7(1), pages 1-18, January.
    21. Chehouri, Adam & Younes, Rafic & Ilinca, Adrian & Perron, Jean, 2015. "Review of performance optimization techniques applied to wind turbines," Applied Energy, Elsevier, vol. 142(C), pages 361-388.
    22. Velázquez, Sergio & Carta, José A. & Matías, J.M., 2011. "Comparison between ANNs and linear MCP algorithms in the long-term estimation of the cost per kWh produced by a wind turbine at a candidate site: A case study in the Canary Islands," Applied Energy, Elsevier, vol. 88(11), pages 3869-3881.
    23. Dong, Yao & Wang, Jianzhou & Jiang, He & Shi, Xiaomeng, 2013. "Intelligent optimized wind resource assessment and wind turbines selection in Huitengxile of Inner Mongolia, China," Applied Energy, Elsevier, vol. 109(C), pages 239-253.
    24. Capuzzi, M. & Pirrera, A. & Weaver, P.M., 2014. "A novel adaptive blade concept for large-scale wind turbines. Part II: Structural design and power performance," Energy, Elsevier, vol. 73(C), pages 25-32.
    25. Yang, Hongxing & Wei, Zhou & Chengzhi, Lou, 2009. "Optimal design and techno-economic analysis of a hybrid solar-wind power generation system," Applied Energy, Elsevier, vol. 86(2), pages 163-169, February.
    26. Ashuri, T. & Zaaijer, M.B. & Martins, J.R.R.A. & van Bussel, G.J.W. & van Kuik, G.A.M., 2014. "Multidisciplinary design optimization of offshore wind turbines for minimum levelized cost of energy," Renewable Energy, Elsevier, vol. 68(C), pages 893-905.
    27. Blanco, María Isabel, 2009. "The economics of wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1372-1382, August.
    28. Grassi, Stefano & Junghans, Sven & Raubal, Martin, 2014. "Assessment of the wake effect on the energy production of onshore wind farms using GIS," Applied Energy, Elsevier, vol. 136(C), pages 827-837.
    29. Lydia, M. & Kumar, S. Suresh & Selvakumar, A. Immanuel & Prem Kumar, G. Edwin, 2014. "A comprehensive review on wind turbine power curve modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 452-460.
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