IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v25y2013icp122-134.html
   My bibliography  Save this article

Review of computer-aided numerical simulation in wind energy

Author

Listed:
  • Miller, Aaron
  • Chang, Byungik
  • Issa, Roy
  • Chen, Gerald

Abstract

Many advances have been made during the last decade in the development and application of computational fluid dynamics (CFD), finite element analysis (FEA), numerical weather modeling, and other numerical methods as applied to the wind energy industry. The current information about this area of study may help researchers gage research efforts. Specifically, micro-siting, wind modeling and prediction, blade optimization and modeling, high resolution turbine flow modeling, support structure analysis, and noise prediction have been the main focuses of recent research. The advances in this area of research are enabling better designs and greater efficiencies than were possible previously. The trends toward system coupling, parallel computing, and replacing experiments are discussed. The shortcomings of recent research and areas of possible future research are also presented.

Suggested Citation

  • Miller, Aaron & Chang, Byungik & Issa, Roy & Chen, Gerald, 2013. "Review of computer-aided numerical simulation in wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 122-134.
  • Handle: RePEc:eee:rensus:v:25:y:2013:i:c:p:122-134
    DOI: 10.1016/j.rser.2013.03.059
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032113002189
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.rser.2013.03.059?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Maheri, Alireza & Noroozi, Siamak & Toomer, Chris A. & Vinney, John, 2006. "WTAB, a computer program for predicting the performance of horizontal axis wind turbines with adaptive blades," Renewable Energy, Elsevier, vol. 31(11), pages 1673-1685.
    2. Pinon, Grégory & Mycek, Paul & Germain, Grégory & Rivoalen, Elie, 2012. "Numerical simulation of the wake of marine current turbines with a particle method," Renewable Energy, Elsevier, vol. 46(C), pages 111-126.
    3. Chowdhury, Souma & Zhang, Jie & Messac, Achille & Castillo, Luciano, 2012. "Unrestricted wind farm layout optimization (UWFLO): Investigating key factors influencing the maximum power generation," Renewable Energy, Elsevier, vol. 38(1), pages 16-30.
    4. Thumthae, Chalothorn & Chitsomboon, Tawit, 2009. "Optimal angle of attack for untwisted blade wind turbine," Renewable Energy, Elsevier, vol. 34(5), pages 1279-1284.
    5. Kim, Hogeon & Lee, Seunghoon & Son, Eunkuk & Lee, Seungmin & Lee, Soogab, 2012. "Aerodynamic noise analysis of large horizontal axis wind turbines considering fluid–structure interaction," Renewable Energy, Elsevier, vol. 42(C), pages 46-53.
    6. McTavish, S. & Feszty, D. & Sankar, T., 2012. "Steady and rotating computational fluid dynamics simulations of a novel vertical axis wind turbine for small-scale power generation," Renewable Energy, Elsevier, vol. 41(C), pages 171-179.
    7. Tadamasa, A. & Zangeneh, M., 2011. "Numerical prediction of wind turbine noise," Renewable Energy, Elsevier, vol. 36(7), pages 1902-1912.
    8. Lanzafame, R. & Mauro, S. & Messina, M., 2013. "Wind turbine CFD modeling using a correlation-based transitional model," Renewable Energy, Elsevier, vol. 52(C), pages 31-39.
    9. Kubik, M.L. & Coker, P.J. & Barlow, J.F. & Hunt, C., 2013. "A study into the accuracy of using meteorological wind data to estimate turbine generation output," Renewable Energy, Elsevier, vol. 51(C), pages 153-158.
    10. Song, M.X. & Chen, K. & He, Z.Y. & Zhang, X., 2012. "Wake flow model of wind turbine using particle simulation," Renewable Energy, Elsevier, vol. 41(C), pages 185-190.
    11. Raciti Castelli, Marco & Englaro, Alessandro & Benini, Ernesto, 2011. "The Darrieus wind turbine: Proposal for a new performance prediction model based on CFD," Energy, Elsevier, vol. 36(8), pages 4919-4934.
    12. Maheri, Alireza & Noroozi, Siamak & Vinney, John, 2007. "Application of combined analytical/FEA coupled aero-structure simulation in design of wind turbine adaptive blades," Renewable Energy, Elsevier, vol. 32(12), pages 2011-2018.
    13. Ledo, L. & Kosasih, P.B. & Cooper, P., 2011. "Roof mounting site analysis for micro-wind turbines," Renewable Energy, Elsevier, vol. 36(5), pages 1379-1391.
    14. Wan, Chunqiu & Wang, Jun & Yang, Geng & Gu, Huajie & Zhang, Xing, 2012. "Wind farm micro-siting by Gaussian particle swarm optimization with local search strategy," Renewable Energy, Elsevier, vol. 48(C), pages 276-286.
    15. Castellani, Francesco & Vignaroli, Andrea, 2013. "An application of the actuator disc model for wind turbine wakes calculations," Applied Energy, Elsevier, vol. 101(C), pages 432-440.
    16. Shen, Xin & Zhu, Xiaocheng & Du, Zhaohui, 2011. "Wind turbine aerodynamics and loads control in wind shear flow," Energy, Elsevier, vol. 36(3), pages 1424-1434.
    17. Kim, Bumsuk & Kim, Woojune & Lee, Sanglae & Bae, Sungyoul & Lee, Youngho, 2013. "Developement and verification of a performance based optimal design software for wind turbine blades," Renewable Energy, Elsevier, vol. 54(C), pages 166-172.
    18. Saavedra-Moreno, B. & Salcedo-Sanz, S. & Paniagua-Tineo, A. & Prieto, L. & Portilla-Figueras, A., 2011. "Seeding evolutionary algorithms with heuristics for optimal wind turbines positioning in wind farms," Renewable Energy, Elsevier, vol. 36(11), pages 2838-2844.
    19. Rajakumar, S. & Ravindran, D., 2012. "Iterative approach for optimising coefficient of power, coefficient of lift and drag of wind turbine rotor," Renewable Energy, Elsevier, vol. 38(1), pages 83-93.
    20. McWilliam, M.K. & van Kooten, G.C. & Crawford, C., 2012. "A method for optimizing the location of wind farms," Renewable Energy, Elsevier, vol. 48(C), pages 287-299.
    21. Hwang, In Seong & Lee, Yun Han & Kim, Seung Jo, 2009. "Optimization of cycloidal water turbine and the performance improvement by individual blade control," Applied Energy, Elsevier, vol. 86(9), pages 1532-1540, September.
    22. Li, Yuwei & Paik, Kwang-Jun & Xing, Tao & Carrica, Pablo M., 2012. "Dynamic overset CFD simulations of wind turbine aerodynamics," Renewable Energy, Elsevier, vol. 37(1), pages 285-298.
    23. Oh, Ki-Yong & Kim, Ji-Young & Lee, Jun-Shin, 2013. "Preliminary evaluation of monopile foundation dimensions for an offshore wind turbine by analyzing hydrodynamic load in the frequency domain," Renewable Energy, Elsevier, vol. 54(C), pages 211-218.
    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. Thé, Jesse & Yu, Hesheng, 2017. "A critical review on the simulations of wind turbine aerodynamics focusing on hybrid RANS-LES methods," Energy, Elsevier, vol. 138(C), pages 257-289.
    2. Cheng-Dar Yue & Che-Chih Liu & Chien-Cheng Tu & Ta-Hui Lin, 2019. "Prediction of Power Generation by Offshore Wind Farms Using Multiple Data Sources," Energies, MDPI, vol. 12(4), pages 1-24, February.
    3. Engeland, Kolbjørn & Borga, Marco & Creutin, Jean-Dominique & François, Baptiste & Ramos, Maria-Helena & Vidal, Jean-Philippe, 2017. "Space-time variability of climate variables and intermittent renewable electricity production – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 600-617.
    4. McKenna, R. & Ostman v.d. Leye, P. & Fichtner, W., 2016. "Key challenges and prospects for large wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1212-1221.
    5. Li, Yi & Wu, Xiao-Peng & Li, Qiu-Sheng & Tee, Kong Fah, 2018. "Assessment of onshore wind energy potential under different geographical climate conditions in China," Energy, Elsevier, vol. 152(C), pages 498-511.
    6. Benitz, M.A. & Lackner, M.A. & Schmidt, D.P., 2015. "Hydrodynamics of offshore structures with specific focus on wind energy applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 692-716.
    7. Wang, Long & Wang, Tongguang & Wu, Jianghai & Chen, Guoping, 2017. "Multi-objective differential evolution optimization based on uniform decomposition for wind turbine blade design," Energy, Elsevier, vol. 120(C), pages 346-361.
    8. Siddiqui, M. Salman & Rasheed, Adil & Tabib, Mandar & Kvamsdal, Trond, 2019. "Numerical investigation of modeling frameworks and geometric approximations on NREL 5 MW wind turbine," Renewable Energy, Elsevier, vol. 132(C), pages 1058-1075.
    9. Cheng, Xu & Yan, Bowen & Zhou, Xuhong & Yang, Qingshan & Huang, Guoqing & Su, Yanwen & Yang, Wei & Jiang, Yan, 2024. "Wind resource assessment at mountainous wind farm: Fusion of RANS and vertical multi-point on-site measured wind field data," Applied Energy, Elsevier, vol. 363(C).
    10. Bendjebbas, H. & Abdellah-ElHadj, A. & Abbas, M., 2016. "Full-scale, wind tunnel and CFD analysis methods of wind loads on heliostats: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 452-472.
    11. Long Wang & Ran Han & Tongguang Wang & Shitang Ke, 2018. "Uniform Decomposition and Positive-Gradient Differential Evolution for Multi-Objective Design of Wind Turbine Blade," Energies, MDPI, vol. 11(5), pages 1-19, May.
    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.

    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. Thé, Jesse & Yu, Hesheng, 2017. "A critical review on the simulations of wind turbine aerodynamics focusing on hybrid RANS-LES methods," Energy, Elsevier, vol. 138(C), pages 257-289.
    2. Bai, Chi-Jeng & Wang, Wei-Cheng, 2016. "Review of computational and experimental approaches to analysis of aerodynamic performance in horizontal-axis wind turbines (HAWTs)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 506-519.
    3. Kuo, Jim Y.J. & Romero, David A. & Beck, J. Christopher & Amon, Cristina H., 2016. "Wind farm layout optimization on complex terrains – Integrating a CFD wake model with mixed-integer programming," Applied Energy, Elsevier, vol. 178(C), pages 404-414.
    4. Guirguis, David & Romero, David A. & Amon, Cristina H., 2017. "Gradient-based multidisciplinary design of wind farms with continuous-variable formulations," Applied Energy, Elsevier, vol. 197(C), pages 279-291.
    5. Trivellato, F. & Raciti Castelli, M., 2014. "On the Courant–Friedrichs–Lewy criterion of rotating grids in 2D vertical-axis wind turbine analysis," Renewable Energy, Elsevier, vol. 62(C), pages 53-62.
    6. Serrano González, Javier & Burgos Payán, Manuel & Santos, Jesús Manuel Riquelme & González-Longatt, Francisco, 2014. "A review and recent developments in the optimal wind-turbine micro-siting problem," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 133-144.
    7. Kumar, Anuj & Saini, R.P., 2017. "Performance analysis of a Savonius hydrokinetic turbine having twisted blades," Renewable Energy, Elsevier, vol. 108(C), pages 502-522.
    8. Azlan, F. & Kurnia, J.C. & Tan, B.T. & Ismadi, M.-Z., 2021. "Review on optimisation methods of wind farm array under three classical wind condition problems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    9. Amiri, Mojtaba Maali & Shadman, Milad & Estefen, Segen F., 2020. "URANS simulations of a horizontal axis wind turbine under stall condition using Reynolds stress turbulence models," Energy, Elsevier, vol. 213(C).
    10. Su, Jie & Lei, Hang & Zhou, Dai & Han, Zhaolong & Bao, Yan & Zhu, Hongbo & Zhou, Lei, 2019. "Aerodynamic noise assessment for a vertical axis wind turbine using Improved Delayed Detached Eddy Simulation," Renewable Energy, Elsevier, vol. 141(C), pages 559-569.
    11. Lo Brutto, Ottavio A. & Thiébot, Jérôme & Guillou, Sylvain S. & Gualous, Hamid, 2016. "A semi-analytic method to optimize tidal farm layouts – Application to the Alderney Race (Raz Blanchard), France," Applied Energy, Elsevier, vol. 183(C), pages 1168-1180.
    12. Gu, Huajie & Wang, Jun, 2013. "Irregular-shape wind farm micro-siting optimization," Energy, Elsevier, vol. 57(C), pages 535-544.
    13. Kumar, Anuj & Saini, R.P., 2017. "Performance analysis of a single stage modified Savonius hydrokinetic turbine having twisted blades," Renewable Energy, Elsevier, vol. 113(C), pages 461-478.
    14. Russell McKenna & Stefan Pfenninger & Heidi Heinrichs & Johannes Schmidt & Iain Staffell & Katharina Gruber & Andrea N. Hahmann & Malte Jansen & Michael Klingler & Natascha Landwehr & Xiaoli Guo Lars', 2021. "Reviewing methods and assumptions for high-resolution large-scale onshore wind energy potential assessments," Papers 2103.09781, arXiv.org.
    15. Li, Chao & Xiao, Yiqing & Xu, You-lin & Peng, Yi-xin & Hu, Gang & Zhu, Songye, 2018. "Optimization of blade pitch in H-rotor vertical axis wind turbines through computational fluid dynamics simulations," Applied Energy, Elsevier, vol. 212(C), pages 1107-1125.
    16. McKenna, Russell & Pfenninger, Stefan & Heinrichs, Heidi & Schmidt, Johannes & Staffell, Iain & Bauer, Christian & Gruber, Katharina & Hahmann, Andrea N. & Jansen, Malte & Klingler, Michael & Landwehr, 2022. "High-resolution large-scale onshore wind energy assessments: A review of potential definitions, methodologies and future research needs," Renewable Energy, Elsevier, vol. 182(C), pages 659-684.
    17. Wekesa, David Wafula & Wang, Cong & Wei, Yingjie & Danao, Louis Angelo M., 2017. "Analytical and numerical investigation of unsteady wind for enhanced energy capture in a fluctuating free-stream," Energy, Elsevier, vol. 121(C), pages 854-864.
    18. Reddy, Sohail R., 2021. "A machine learning approach for modeling irregular regions with multiple owners in wind farm layout design," Energy, Elsevier, vol. 220(C).
    19. Jinghua Lin & You-Lin Xu & Yong Xia & Chao Li, 2019. "Structural Analysis of Large-Scale Vertical-Axis Wind Turbines, Part I: Wind Load Simulation," Energies, MDPI, vol. 12(13), pages 1-31, July.
    20. 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.

    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:eee:rensus:v:25:y:2013:i:c:p:122-134. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    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.