IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i10p2728-d175080.html
   My bibliography  Save this article

Optimal Design of Rated Wind Speed and Rotor Radius to Minimizing the Cost of Energy for Offshore Wind Turbines

Author

Listed:
  • Longfu Luo

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Xiaofeng Zhang

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Dongran Song

    (School of Information Science and Engineering, Central South University, Changsha 410083, China)

  • Weiyi Tang

    (School of Information Science and Engineering, Central South University, Changsha 410083, China)

  • Jian Yang

    (School of Information Science and Engineering, Central South University, Changsha 410083, China)

  • Li Li

    (School of Information Science and Engineering, Central South University, Changsha 410083, China)

  • Xiaoyu Tian

    (School of Information Science and Engineering, Central South University, Changsha 410083, China)

  • Wu Wen

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

Abstract

As onshore wind energy has depleted, the utilization of offshore wind energy has gradually played an important role in globally meeting growing green energy demands. However, the cost of energy (COE) for offshore wind energy is very high compared to the onshore one. To minimize the COE, implementing optimal design of offshore turbines is an effective way, but the relevant studies are lacking. This study proposes a method to minimize the COE of offshore wind turbines, in which two design parameters, including the rated wind speed and rotor radius are optimally designed. Through this study, the relation among the COE and the two design parameters is explored. To this end, based on the power-coefficient power curve model, the annual energy production (AEP) model is designed as a function of the rated wind speed and the Weibull distribution parameters. On the other hand, the detailed cost model of offshore turbines developed by the National Renewable Energy Laboratory is formulated as a function of the rated wind speed and the rotor radius. Then, the COE is formulated as the ratio of the total cost and the AEP. Following that, an iterative method is proposed to search the minimal COE which corresponds to the optimal rated wind speed and rotor radius. Finally, the proposed method has been applied to the wind classes of USA, and some useful findings have been obtained.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:10:p:2728-:d:175080
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/10/2728/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/10/2728/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Tar, Károly, 2008. "Some statistical characteristics of monthly average wind speed at various heights," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(6), pages 1712-1724, August.
    3. 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.
    4. Yichao Liu & Daoyi Chen & Qian Yi & Sunwei Li, 2017. "Wind Profiles and Wave Spectra for Potential Wind Farms in South China Sea. Part I: Wind Speed Profile Model," Energies, MDPI, vol. 10(1), pages 1-24, January.
    5. Willis, D.J. & Niezrecki, C. & Kuchma, D. & Hines, E. & Arwade, S.R. & Barthelmie, R.J. & DiPaola, M. & Drane, P.J. & Hansen, C.J. & Inalpolat, M. & Mack, J.H. & Myers, A.T. & Rotea, M., 2018. "Wind energy research: State-of-the-art and future research directions," Renewable Energy, Elsevier, vol. 125(C), pages 133-154.
    6. Yichao Liu & Sunwei Li & Qian Yi & Daoyi Chen, 2017. "Wind Profiles and Wave Spectra for Potential Wind Farms in South China Sea. Part II: Wave Spectrum Model," Energies, MDPI, vol. 10(1), pages 1-24, January.
    7. 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.
    8. Ferdoues, Mst Sunzida & Ebrahimi, Sasan & Vijayaraghavan, Krishna, 2017. "Multi-objective optimization of the design and operating point of a new external axis wind turbine," Energy, Elsevier, vol. 125(C), pages 643-653.
    9. Song, Dongran & Fan, Xinyu & Yang, Jian & Liu, Anfeng & Chen, Sifan & Joo, Young Hoon, 2018. "Power extraction efficiency optimization of horizontal-axis wind turbines through optimizing control parameters of yaw control systems using an intelligent method," Applied Energy, Elsevier, vol. 224(C), pages 267-279.
    10. Ulas Eminoglu & Saffet Ayasun, 2014. "Modeling and Design Optimization of Variable-Speed Wind Turbine Systems," Energies, MDPI, vol. 7(1), pages 1-18, January.
    11. Yin, Minghui & Yang, Zhiqiang & Xu, Yan & Liu, Jiankun & Zhou, Lianjun & Zou, Yun, 2018. "Aerodynamic optimization for variable-speed wind turbines based on wind energy capture efficiency," Applied Energy, Elsevier, vol. 221(C), pages 508-521.
    12. 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.
    13. Song, Dongran & Yang, Jian & Cai, Zili & Dong, Mi & Su, Mei & Wang, Yinghua, 2017. "Wind estimation with a non-standard extended Kalman filter and its application on maximum power extraction for variable speed wind turbines," Applied Energy, Elsevier, vol. 190(C), pages 670-685.
    14. Song, Dongran & Yang, Jian & Dong, Mi & Joo, Young Hoon, 2017. "Model predictive control with finite control set for variable-speed wind turbines," Energy, Elsevier, vol. 126(C), pages 564-572.
    15. 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.
    16. Dongran Song & Jian Yang & Mei Su & Anfeng Liu & Yao Liu & Young Hoon Joo, 2017. "A Comparison Study between Two MPPT Control Methods for a Large Variable-Speed Wind Turbine under Different Wind Speed Characteristics," Energies, MDPI, vol. 10(5), pages 1-18, May.
    17. Ying Zhu & Ming Cheng & Wei Hua & Wei Wang, 2012. "A Novel Maximum Power Point Tracking Control for Permanent Magnet Direct Drive Wind Energy Conversion Systems," Energies, MDPI, vol. 5(5), pages 1-15, May.
    18. Dai, Juchuan & Yang, Xin & Wen, Li, 2018. "Development of wind power industry in China: A comprehensive assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 156-164.
    19. Xiaolian Zhang & Can Huang & Sipeng Hao & Fan Chen & Jingjing Zhai, 2016. "An Improved Adaptive-Torque-Gain MPPT Control for Direct-Driven PMSG Wind Turbines Considering Wind Farm Turbulences," Energies, MDPI, vol. 9(11), pages 1-16, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Song, Dongran & Liu, Junbo & Yang, Jian & Su, Mei & Wang, Yun & Yang, Xuebing & Huang, Lingxiang & Joo, Young Hoon, 2020. "Optimal design of wind turbines on high-altitude sites based on improved Yin-Yang pair optimization," Energy, Elsevier, vol. 193(C).
    2. Song, Dongran & Xu, Shanmin & Huang, Lingxiang & Xia, E. & Huang, Chaoneng & Yang, Jian & Hu, Yang & Fang, Fang, 2022. "Multi-site and multi-objective optimization for wind turbines based on the design of virtual representative wind farm," Energy, Elsevier, vol. 252(C).
    3. Alexandra G. Papadopoulou & George Vasileiou & Alexandros Flamos, 2020. "A Comparison of Dispatchable RES Technoeconomics: Is There a Niche for Concentrated Solar Power?," Energies, MDPI, vol. 13(18), pages 1-22, September.
    4. Yutaka Hara & Ayato Miyashita & Shigeo Yoshida, 2023. "Numerical Simulation of the Effects of Blade–Arm Connection Gap on Vertical–Axis Wind Turbine Performance," Energies, MDPI, vol. 16(19), pages 1-15, October.
    5. Eugen Rusu & Vengatesan Venugopal, 2019. "Special Issue “Offshore Renewable Energy: Ocean Waves, Tides and Offshore Wind”," Energies, MDPI, vol. 12(1), pages 1-4, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Song, Dongran & Yang, Yinggang & Zheng, Songyue & Tang, Weiyi & Yang, Jian & Su, Mei & Yang, Xuebing & Joo, Young Hoon, 2019. "Capacity factor estimation of variable-speed wind turbines considering the coupled influence of the QN-curve and the air density," Energy, Elsevier, vol. 183(C), pages 1049-1060.
    2. Song, Dongran & Liu, Junbo & Yang, Jian & Su, Mei & Wang, Yun & Yang, Xuebing & Huang, Lingxiang & Joo, Young Hoon, 2020. "Optimal design of wind turbines on high-altitude sites based on improved Yin-Yang pair optimization," Energy, Elsevier, vol. 193(C).
    3. Dongran Song & Jian Yang & Mei Su & Anfeng Liu & Yao Liu & Young Hoon Joo, 2017. "A Comparison Study between Two MPPT Control Methods for a Large Variable-Speed Wind Turbine under Different Wind Speed Characteristics," Energies, MDPI, vol. 10(5), pages 1-18, May.
    4. Song, Dongran & Yang, Jian & Su, Mei & Liu, Anfeng & Cai, Zili & Liu, Yao & Joo, Young Hoon, 2017. "A novel wind speed estimator-integrated pitch control method for wind turbines with global-power regulation," Energy, Elsevier, vol. 138(C), pages 816-830.
    5. Noyes, Carlos & Loth, Eric & Martin, Dana & Johnson, Kathryn & Ananda, Gavin & Selig, Michael, 2020. "Extreme-scale load-aligning rotor: To hinge or not to hinge?," Applied Energy, Elsevier, vol. 257(C).
    6. Yin, Minghui & Yang, Zhiqiang & Xu, Yan & Liu, Jiankun & Zhou, Lianjun & Zou, Yun, 2018. "Aerodynamic optimization for variable-speed wind turbines based on wind energy capture efficiency," Applied Energy, Elsevier, vol. 221(C), pages 508-521.
    7. 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.
    8. Song, Dongran & Fan, Xinyu & Yang, Jian & Liu, Anfeng & Chen, Sifan & Joo, Young Hoon, 2018. "Power extraction efficiency optimization of horizontal-axis wind turbines through optimizing control parameters of yaw control systems using an intelligent method," Applied Energy, Elsevier, vol. 224(C), pages 267-279.
    9. Song, Dongran & Liu, Junbo & Yang, Yinggang & Yang, Jian & Su, Mei & Wang, Yun & Gui, Ning & Yang, Xuebing & Huang, Lingxiang & Hoon Joo, Young, 2021. "Maximum wind energy extraction of large-scale wind turbines using nonlinear model predictive control via Yin-Yang grey wolf optimization algorithm," Energy, Elsevier, vol. 221(C).
    10. Kumarasamy Palanimuthu & Ganesh Mayilsamy & Ameerkhan Abdul Basheer & Seong-Ryong Lee & Dongran Song & Young Hoon Joo, 2022. "A Review of Recent Aerodynamic Power Extraction Challenges in Coordinated Pitch, Yaw, and Torque Control of Large-Scale Wind Turbine Systems," Energies, MDPI, vol. 15(21), pages 1-27, November.
    11. Cheng, Yi & Azizipanah-Abarghooee, Rasoul & Azizi, Sadegh & Ding, Lei & Terzija, Vladimir, 2020. "Smart frequency control in low inertia energy systems based on frequency response techniques: A review," Applied Energy, Elsevier, vol. 279(C).
    12. Xiao, Qing & Zhou, Shaowu, 2018. "Probabilistic power flow computation considering correlated wind speeds," Applied Energy, Elsevier, vol. 231(C), pages 677-685.
    13. Cao, Yankai & Zavala, Victor M. & D’Amato, Fernando, 2018. "Using stochastic programming and statistical extrapolation to mitigate long-term extreme loads in wind turbines," Applied Energy, Elsevier, vol. 230(C), pages 1230-1241.
    14. Tania García-Sánchez & Arbinda Kumar Mishra & Elías Hurtado-Pérez & Rubén Puché-Panadero & Ana Fernández-Guillamón, 2020. "A Controller for Optimum Electrical Power Extraction from a Small Grid-Interconnected Wind Turbine," Energies, MDPI, vol. 13(21), pages 1-16, November.
    15. Yao Liu & Lin Guan & Fang Guo & Jianping Zheng & Jianfu Chen & Chao Liu & Josep M. Guerrero, 2019. "A Reactive Power-Voltage Control Strategy of an AC Microgrid Based on Adaptive Virtual Impedance," Energies, MDPI, vol. 12(16), pages 1-15, August.
    16. Janusz Baran & Andrzej Jąderko, 2020. "An MPPT Control of a PMSG-Based WECS with Disturbance Compensation and Wind Speed Estimation," Energies, MDPI, vol. 13(23), pages 1-20, December.
    17. Li, Qing’an & Xu, Jianzhong & Kamada, Yasunari & Takao, Maeda & Nishimura, Shogo & Wu, Guangxing & Cai, Chang, 2020. "Experimental investigations of airfoil surface flow of a horizontal axis wind turbine with LDV measurements," Energy, Elsevier, vol. 191(C).
    18. Lin, Zhongwei & Chen, Zhenyu & Liu, Jizhen & Wu, Qiuwei, 2019. "Coordinated mechanical loads and power optimization of wind energy conversion systems with variable-weight model predictive control strategy," Applied Energy, Elsevier, vol. 236(C), pages 307-317.
    19. Luis M. López-Manrique & E. V. Macias-Melo & O. May Tzuc & A. Bassam & K. M. Aguilar-Castro & I. Hernández-Pérez, 2018. "Assessment of Resource and Forecast Modeling of Wind Speed through An Evolutionary Programming Approach for the North of Tehuantepec Isthmus (Cuauhtemotzin, Mexico)," Energies, MDPI, vol. 11(11), pages 1-22, November.
    20. Lin, Zi & Liu, Xiaolei, 2020. "Wind power forecasting of an offshore wind turbine based on high-frequency SCADA data and deep learning neural network," Energy, Elsevier, vol. 201(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:11:y:2018:i:10:p:2728-:d:175080. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.