IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i21p13886-d953473.html
   My bibliography  Save this article

Developing an Extended Virtual Blade Model for Efficient Numerical Modeling of Wind and Tidal Farms

Author

Listed:
  • Soheil Radfar

    (Department of Civil and Environmental Engineering, Tarbiat Modares University, Tehran 14117-13116, Iran)

  • Bijan Kianoush

    (Faculty of Civil Engineering, Khaje Nasir Toosi University of Technology, Tehran 19967-15433, Iran)

  • Meysam Majidi Nezhad

    (Department of Astronautics, Electrical and Energy Engineering (DIAEE), Sapienza University of Rome, 00184 Roma, Italy)

  • Mehdi Neshat

    (Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW 2007, Australia)

Abstract

Harnessing renewable and clean energy resources from winds and tides are promising technologies to alter the high level of consumption of traditional energy resources because of their great global potential. In this regard, developing farms with multiple energy converters is of great interest due to the skyrocketing demand for sustainable energy resources. However, the numerical simulation of these farms during the planning phase might pose challenges, the most significant of which is the computational cost. One of the most well-known approaches to resolve this concern is to use the virtual blade model (VBM). VBM is the implementation of the blade element model (BEM). This was done by coupling the blade element momentum theory equations to simulate rotor operation with the Reynolds averaged Navier–Stokes (RANS) equation to simulate rotor wake and the turbulent flow field around it. The exclusion of the actual geometry of blades enables a lower computational cost. Additionally, due to simplifications in the meshing procedure, VBM is easier to set up than the models that consider the actual geometry of blades. One of the main unaddressed limitations of the VBM code is the constraint of modeling up to 10 renewable energy converters within one computational domain. This paper provides a detailed and well-documented general methodology to develop a virtual blade model for the simulation of 10-plus converters within one computational domain to remove the limitation of this widely used and robust code. The extended code is validated for both the single- and multi-converter scenarios. It is strongly believed that the technical contribution of this paper, combined with the current advancement of available computational resources and hardware, can open the gates to simulate farms with any desired number of wind or tidal energy converters, and, accordingly, secure the sustainability and feasibility of clean energies.

Suggested Citation

  • Soheil Radfar & Bijan Kianoush & Meysam Majidi Nezhad & Mehdi Neshat, 2022. "Developing an Extended Virtual Blade Model for Efficient Numerical Modeling of Wind and Tidal Farms," Sustainability, MDPI, vol. 14(21), pages 1-17, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:13886-:d:953473
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/21/13886/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/21/13886/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Li, Xiaorong & Li, Ming & Jordan, Laura-Beth & McLelland, Stuart & Parsons, Daniel R. & Amoudry, Laurent O. & Song, Qingyang & Comerford, Liam, 2019. "Modelling impacts of tidal stream turbines on surface waves," Renewable Energy, Elsevier, vol. 130(C), pages 725-734.
    2. Soheil Radfar & Roozbeh Panahi & Meysam Majidi Nezhad & Mehdi Neshat, 2022. "A Numerical Methodology to Predict the Maximum Power Output of Tidal Stream Arrays," Sustainability, MDPI, vol. 14(3), pages 1-13, January.
    3. Ian Masters & Alison Williams & T. Nick Croft & Michael Togneri & Matt Edmunds & Enayatollah Zangiabadi & Iain Fairley & Harshinie Karunarathna, 2015. "A Comparison of Numerical Modelling Techniques for Tidal Stream Turbine Analysis," Energies, MDPI, vol. 8(8), pages 1-21, July.
    4. Nachtane, M. & Tarfaoui, M. & Goda, I. & Rouway, M., 2020. "A review on the technologies, design considerations and numerical models of tidal current turbines," Renewable Energy, Elsevier, vol. 157(C), pages 1274-1288.
    5. Aguayo, Maichel M. & Fierro, Pablo E. & De la Fuente, Rodrigo A. & Sepúlveda, Ignacio A. & Figueroa, Dante M., 2021. "A mixed-integer programming methodology to design tidal current farms integrating both cost and benefits: A case study in the Chacao Channel, Chile," Applied Energy, Elsevier, vol. 294(C).
    6. Siyavash Filom & Soheil Radfar & Roozbeh Panahi & Erfan Amini & Mehdi Neshat, 2021. "Exploring Wind Energy Potential as a Driver of Sustainable Development in the Southern Coasts of Iran: The Importance of Wind Speed Statistical Distribution Model," Sustainability, MDPI, vol. 13(14), pages 1-24, July.
    7. Sufian, Sufian. F. & Li, Ming & O’Connor, Brian A., 2017. "3D modelling of impacts from waves on tidal turbine wake characteristics and energy output," Renewable Energy, Elsevier, vol. 114(PA), pages 308-322.
    8. Federico Attene & Francesco Balduzzi & Alessandro Bianchini & M. Sergio Campobasso, 2020. "Using Experimentally Validated Navier-Stokes CFD to Minimize Tidal Stream Turbine Power Losses Due to Wake/Turbine Interactions," Sustainability, MDPI, vol. 12(21), pages 1-26, October.
    9. Funke, S.W. & Farrell, P.E. & Piggott, M.D., 2014. "Tidal turbine array optimisation using the adjoint approach," Renewable Energy, Elsevier, vol. 63(C), pages 658-673.
    10. Eurek, Kelly & Sullivan, Patrick & Gleason, Michael & Hettinger, Dylan & Heimiller, Donna & Lopez, Anthony, 2017. "An improved global wind resource estimate for integrated assessment models," Energy Economics, Elsevier, vol. 64(C), pages 552-567.
    Full references (including those not matched with items on IDEAS)

    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. Nash, S. & Phoenix, A., 2017. "A review of the current understanding of the hydro-environmental impacts of energy removal by tidal turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 648-662.
    2. Stephen Nash & Agnieszka I. Olbert & Michael Hartnett, 2015. "Towards a Low-Cost Modelling System for Optimising the Layout of Tidal Turbine Arrays," Energies, MDPI, vol. 8(12), pages 1-19, November.
    3. Angus C. W. Creech & Alistair G. L. Borthwick & David Ingram, 2017. "Effects of Support Structures in an LES Actuator Line Model of a Tidal Turbine with Contra-Rotating Rotors," Energies, MDPI, vol. 10(5), pages 1-25, May.
    4. Yang, Zhixue & Ren, Zhouyang & Li, Hui & Pan, Zhen & Xia, Weiyi, 2024. "A review of tidal current power generation farm planning: Methodologies, characteristics and challenges," Renewable Energy, Elsevier, vol. 220(C).
    5. Zhang, Yidan & Shek, Jonathan K.H. & Mueller, Markus A., 2023. "Controller design for a tidal turbine array, considering both power and loads aspects," Renewable Energy, Elsevier, vol. 216(C).
    6. du Feu, R.J. & Funke, S.W. & Kramer, S.C. & Hill, J. & Piggott, M.D., 2019. "The trade-off between tidal-turbine array yield and environmental impact: A habitat suitability modelling approach," Renewable Energy, Elsevier, vol. 143(C), pages 390-403.
    7. Baheri, Ali & Ramaprabhu, Praveen & Vermillion, Christopher, 2018. "Iterative 3D layout optimization and parametric trade study for a reconfigurable ocean current turbine array using Bayesian Optimization," Renewable Energy, Elsevier, vol. 127(C), pages 1052-1063.
    8. Liang, Yushi & Wu, Chunbing & Ji, Xiaodong & Zhang, Mulan & Li, Yiran & He, Jianjun & Qin, Zhiheng, 2022. "Estimation of the influences of spatiotemporal variations in air density on wind energy assessment in China based on deep neural network," Energy, Elsevier, vol. 239(PC).
    9. Yao, Yao & Shen, Zhicheng & Wang, Qiliang & Du, Jiyun & Lu, Lin & Yang, Hongxing, 2023. "Development of an inline bidirectional micro crossflow turbine for hydropower harvesting from water supply pipelines," Applied Energy, Elsevier, vol. 329(C).
    10. Fouz, D.M. & Carballo, R. & López, I. & González, X.P. & Iglesias, G., 2023. "A methodology for cost-effective analysis of hydrokinetic energy projects," Energy, Elsevier, vol. 282(C).
    11. Martin-Short, R. & Hill, J. & Kramer, S.C. & Avdis, A. & Allison, P.A. & Piggott, M.D., 2015. "Tidal resource extraction in the Pentland Firth, UK: Potential impacts on flow regime and sediment transport in the Inner Sound of Stroma," Renewable Energy, Elsevier, vol. 76(C), pages 596-607.
    12. Fairley, I. & Masters, I. & Karunarathna, H., 2015. "The cumulative impact of tidal stream turbine arrays on sediment transport in the Pentland Firth," Renewable Energy, Elsevier, vol. 80(C), pages 755-769.
    13. Wu, Baigong & Zhan, Mingjing & Wu, Rujian & Zhang, Xiao, 2023. "The investigation of a coaxial twin-counter-rotating turbine with variable-pitch adaptive blades," Energy, Elsevier, vol. 267(C).
    14. Ulazia, Alain & Sáenz, Jon & Ibarra-Berastegi, Gabriel & González-Rojí, Santos J. & Carreno-Madinabeitia, Sheila, 2019. "Global estimations of wind energy potential considering seasonal air density changes," Energy, Elsevier, vol. 187(C).
    15. Hu, Jing & Harmsen, Robert & Crijns-Graus, Wina & Worrell, Ernst, 2019. "Geographical optimization of variable renewable energy capacity in China using modern portfolio theory," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    16. Dupont, Elise & Koppelaar, Rembrandt & Jeanmart, Hervé, 2018. "Global available wind energy with physical and energy return on investment constraints," Applied Energy, Elsevier, vol. 209(C), pages 322-338.
    17. Tian, Wenlong & Ni, Xiwen & Mao, Zhaoyong & Zhang, Tianqi, 2020. "Influence of surface waves on the hydrodynamic performance of a horizontal axis ocean current turbine," Renewable Energy, Elsevier, vol. 158(C), pages 37-48.
    18. Stansby, Peter & Stallard, Tim, 2016. "Fast optimisation of tidal stream turbine positions for power generation in small arrays with low blockage based on superposition of self-similar far-wake velocity deficit profiles," Renewable Energy, Elsevier, vol. 92(C), pages 366-375.
    19. Ruan, Pengcheng & Huang, Diangui, 2023. "Study of aerodynamic performance of built-in variable wavelength traveling wave turbine," Renewable Energy, Elsevier, vol. 205(C), pages 918-928.
    20. María José Suárez-López & Rodolfo Espina-Valdés & Víctor Manuel Fernández Pacheco & Antonio Navarro Manso & Eduardo Blanco-Marigorta & Eduardo Álvarez-Álvarez, 2019. "A Review of Software Tools to Study the Energetic Potential of Tidal Currents," Energies, MDPI, vol. 12(9), pages 1-19, May.

    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:jsusta:v:14:y:2022:i:21:p:13886-:d:953473. 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.