IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v16y2012i7p4809-4817.html
   My bibliography  Save this article

Integral analysis of rotors of a wind generator

Author

Listed:
  • Romão da Silva Melo, Rafael
  • da Silveira Neto, Aristeu

Abstract

The world's population needs new sources of energy, especially those that are clean and renewable. This paper provides a brief introduction to wind energy and the types of existing turbines, which are classified using the orientation of the rotation axis. Subsequently, an integral analysis is performed for vertical axis turbines. The known variables are the wind speed, the type of blade, the radius of the rotor and the angular velocity. The fluid velocity and the angle of attack on the blade are subsequently determined. From these two results, the lift and drag forces acting on the blades for each position of the rotor are calculated. The resultant torque and power generated are also calculated to evaluate the turbine power coefficient. Due to the rotation and the robustness of this type of turbine, a distortion in the flow direction occurs in its vicinity. The flow is modeled on a control volume, which is defined based on the variation in the wind direction.

Suggested Citation

  • Romão da Silva Melo, Rafael & da Silveira Neto, Aristeu, 2012. "Integral analysis of rotors of a wind generator," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4809-4817.
  • Handle: RePEc:eee:rensus:v:16:y:2012:i:7:p:4809-4817
    DOI: 10.1016/j.rser.2012.03.070
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032112002547
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.rser.2012.03.070?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. Ibenholt, Karin, 2002. "Explaining learning curves for wind power," Energy Policy, Elsevier, vol. 30(13), pages 1181-1189, October.
    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. Bolinger, Mark & Wiser, Ryan, 2009. "Wind power price trends in the United States: Struggling to remain competitive in the face of strong growth," Energy Policy, Elsevier, vol. 37(3), pages 1061-1071, March.
    2. Samadi, Sascha, 2018. "The experience curve theory and its application in the field of electricity generation technologies – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2346-2364.
    3. Greaker, Mads & Lund Sagen, Eirik, 2008. "Explaining experience curves for new energy technologies: A case study of liquefied natural gas," Energy Economics, Elsevier, vol. 30(6), pages 2899-2911, November.
    4. Brito, Thiago Luis Felipe & Islam, Towhidul & Stettler, Marc & Mouette, Dominique & Meade, Nigel & Moutinho dos Santos, Edmilson, 2019. "Transitions between technological generations of alternative fuel vehicles in Brazil," Energy Policy, Elsevier, vol. 134(C).
    5. Enevoldsen, Peter & Valentine, Scott Victor & Sovacool, Benjamin K., 2018. "Insights into wind sites: Critically assessing the innovation, cost, and performance dynamics of global wind energy development," Energy Policy, Elsevier, vol. 120(C), pages 1-7.
    6. Wagner Sousa de Oliveira & Antonio Jorge Fernandes, 2012. "Optimization Model for Economic Evaluation of Wind Farms - How to Optimize a Wind Energy Project Economically and Technically," International Journal of Energy Economics and Policy, Econjournals, vol. 2(1), pages 10-20.
    7. Yeh, Sonia & Rubin, Edward S., 2012. "A review of uncertainties in technology experience curves," Energy Economics, Elsevier, vol. 34(3), pages 762-771.
    8. Xu, Mei & Xie, Pu & Xie, Bai-Chen, 2020. "Study of China's optimal solar photovoltaic power development path to 2050," Resources Policy, Elsevier, vol. 65(C).
    9. Kumbaroglu, Gürkan & Madlener, Reinhard & Demirel, Mustafa, 2008. "A real options evaluation model for the diffusion prospects of new renewable power generation technologies," Energy Economics, Elsevier, vol. 30(4), pages 1882-1908, July.
    10. Díaz, Guzmán & Moreno, Blanca & Coto, José & Gómez-Aleixandre, Javier, 2015. "Valuation of wind power distributed generation by using Longstaff–Schwartz option pricing method," Applied Energy, Elsevier, vol. 145(C), pages 223-233.
    11. Williams, Eric & Hittinger, Eric & Carvalho, Rexon & Williams, Ryan, 2017. "Wind power costs expected to decrease due to technological progress," Energy Policy, Elsevier, vol. 106(C), pages 427-435.
    12. Berglund, Christer & Soderholm, Patrik, 2006. "Modeling technical change in energy system analysis: analyzing the introduction of learning-by-doing in bottom-up energy models," Energy Policy, Elsevier, vol. 34(12), pages 1344-1356, August.
    13. Jamasb, T., 2006. "Technical Change Theory and Learning Curves: Patterns of Progress in Energy Technologies," Cambridge Working Papers in Economics 0625, Faculty of Economics, University of Cambridge.
    14. Jong-Hyun Kim & Yong-Gil Lee, 2018. "Learning Curve, Change in Industrial Environment, and Dynamics of Production Activities in Unconventional Energy Resources," Sustainability, MDPI, vol. 10(9), pages 1-11, September.
    15. Rout, Ullash K. & Fahl, Ulrich & Remme, Uwe & Blesl, Markus & Voß, Alfred, 2009. "Endogenous implementation of technology gap in energy optimization models--a systematic analysis within TIMES G5 model," Energy Policy, Elsevier, vol. 37(7), pages 2814-2830, July.
    16. Elia, A. & Taylor, M. & Ó Gallachóir, B. & Rogan, F., 2020. "Wind turbine cost reduction: A detailed bottom-up analysis of innovation drivers," Energy Policy, Elsevier, vol. 147(C).
    17. Junginger, M. & Faaij, A. & Turkenburg, W. C., 2005. "Global experience curves for wind farms," Energy Policy, Elsevier, vol. 33(2), pages 133-150, January.
    18. Nouni, M.R. & Mullick, S.C. & Kandpal, T.C., 2007. "Techno-economics of small wind electric generator projects for decentralized power supply in India," Energy Policy, Elsevier, vol. 35(4), pages 2491-2506, April.
    19. Gosens, Jorrit & Hedenus, Fredrik & Sandén, Björn A., 2017. "Faster market growth of wind and PV in late adopters due to global experience build-up," Energy, Elsevier, vol. 131(C), pages 267-278.
    20. Grafström, Jonas, 2021. "Ratio Working Paper No. 351: Knowledge Spillovers in the Solar energy sector," Ratio Working Papers 351, The Ratio Institute.

    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:16:y:2012:i:7:p:4809-4817. 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.