IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v55y2013icp202-211.html
   My bibliography  Save this article

Mapping the wind resource over UK cities

Author

Listed:
  • Millward-Hopkins, J.T.
  • Tomlin, A.S.
  • Ma, L.
  • Ingham, D.B.
  • Pourkashanian, M.

Abstract

Decentralised energy sources, such as small-scale-wind energy, have a number of well-known advantages. However, within urban areas, the potential for energy generation from the wind is not currently fully utilised. One of the most significant reasons for this is that the complexity of air flows within the urban boundary layer makes accurate predictions of the wind resource difficult to achieve. Without sufficiently accurate methods of predicting this resource, there is a danger that wind turbines will either be installed at unsuitable locations or that many viable sites will be overlooked. In this paper, we compare the accuracy of three different analytical methodologies for predicting above-roof mean wind speeds across a number of UK cities. The first is based upon a methodology developed by the UK Meteorological Office. We then implement two more complex methods which utilise maps of surface aerodynamic parameters derived from detailed building data. The predictions are compared with measured mean wind speeds from a wide variety of UK urban locations. The results show that the methodologies are generally more accurate when more complexity is used in the approach, particularly for the sites which are well exposed to the wind. The best agreement with measured data is achieved when the influence of wind direction is thoroughly considered and aerodynamic parameters are derived from detailed building data. However, some uncertainties in the building data add to the errors inherent within the methodologies. Consequently, it is suggested that a detailed description of both the shapes and heights of the local building roofs is required to maximise the accuracy of wind speed predictions.

Suggested Citation

  • Millward-Hopkins, J.T. & Tomlin, A.S. & Ma, L. & Ingham, D.B. & Pourkashanian, M., 2013. "Mapping the wind resource over UK cities," Renewable Energy, Elsevier, vol. 55(C), pages 202-211.
    • Handle: RePEc:eee:renene:v:55:y:2013:i:c:p:202-211
    DOI: 10.1016/j.renene.2012.12.039
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148112008051
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2012.12.039?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. Weekes, S.M. & Tomlin, A.S., 2013. "Evaluation of a semi-empirical model for predicting the wind energy resource relevant to small-scale wind turbines," Renewable Energy, Elsevier, vol. 50(C), pages 280-288.
    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. Charles Newbold & Mohammad Akrami & Mahdieh Dibaj, 2021. "Scenarios, Financial Viability and Pathways of Localized Hybrid Energy Generation Systems around the United Kingdom," Energies, MDPI, vol. 14(18), pages 1-27, September.
    2. Hernández, Ó. Soto & Volkov, K. & Martín Mederos, A.C. & Medina Padrón, J.F. & Feijóo Lorenzo, A.E., 2015. "Power output of a wind turbine installed in an already existing viaduct," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 287-299.
    3. De Silva, P.N.K. & Simons, S.J.R. & Stevens, P., 2016. "Economic impact analysis of natural gas development and the policy implications," Energy Policy, Elsevier, vol. 88(C), pages 639-651.
    4. Yang, An-Shik & Su, Ying-Ming & Wen, Chih-Yung & Juan, Yu-Hsuan & Wang, Wei-Siang & Cheng, Chiang-Ho, 2016. "Estimation of wind power generation in dense urban area," Applied Energy, Elsevier, vol. 171(C), pages 213-230.
    5. Millward-Hopkins, J.T. & Tomlin, A.S. & Ma, L. & Ingham, D.B. & Pourkashanian, M., 2013. "Assessing the potential of urban wind energy in a major UK city using an analytical model," Renewable Energy, Elsevier, vol. 60(C), pages 701-710.
    6. Jens Koehrsen, 2017. "Boundary Bridging Arrangements: A Boundary Work Approach to Local Energy Transitions," Sustainability, MDPI, vol. 9(3), pages 1-23, March.
    7. Isabel Cristina Gil-García & María Socorro García-Cascales & Angel Molina-García, 2022. "Urban Wind: An Alternative for Sustainable Cities," Energies, MDPI, vol. 15(13), pages 1-20, June.
    8. Kumar, Rakesh & Raahemifar, Kaamran & Fung, Alan S., 2018. "A critical review of vertical axis wind turbines for urban applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 281-291.
    9. Drew, D.R. & Barlow, J.F. & Cockerill, T.T. & Vahdati, M.M., 2015. "The importance of accurate wind resource assessment for evaluating the economic viability of small wind turbines," Renewable Energy, Elsevier, vol. 77(C), pages 493-500.
    10. Luca Salvadori & Annalisa Di Bernardino & Giorgio Querzoli & Simone Ferrari, 2021. "A Novel Automatic Method for the Urban Canyon Parametrization Needed by Turbulence Numerical Simulations for Wind Energy Potential Assessment," Energies, MDPI, vol. 14(16), pages 1-22, August.
    11. Daniel Micallef & Gerard Van Bussel, 2018. "A Review of Urban Wind Energy Research: Aerodynamics and Other Challenges," Energies, MDPI, vol. 11(9), pages 1-27, August.

    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. Yossri, W. & Ben Ayed, S. & Abdelkefi, A., 2023. "Evaluation of the efficiency of bioinspired blade designs for low-speed small-scale wind turbines with the presence of inflow turbulence effects," Energy, Elsevier, vol. 273(C).
    2. Bush, Ruth & Jacques, David A. & Scott, Kate & Barrett, John, 2014. "The carbon payback of micro-generation: An integrated hybrid input–output approach," Applied Energy, Elsevier, vol. 119(C), pages 85-98.
    3. Allen, D.J. & Tomlin, A.S. & Bale, C.S.E. & Skea, A. & Vosper, S. & Gallani, M.L., 2017. "A boundary layer scaling technique for estimating near-surface wind energy using numerical weather prediction and wind map data," Applied Energy, Elsevier, vol. 208(C), pages 1246-1257.
    4. Millward-Hopkins, J.T. & Tomlin, A.S. & Ma, L. & Ingham, D.B. & Pourkashanian, M., 2013. "Assessing the potential of urban wind energy in a major UK city using an analytical model," Renewable Energy, Elsevier, vol. 60(C), pages 701-710.
    5. Osvaldo Rodriguez-Hernandez & Manuel Martinez & Carlos Lopez-Villalobos & Hector Garcia & Rafael Campos-Amezcua, 2019. "Techno-Economic Feasibility Study of Small Wind Turbines in the Valley of Mexico Metropolitan Area," Energies, MDPI, vol. 12(5), pages 1-26, March.
    6. Simões, Teresa & Estanqueiro, Ana, 2016. "A new methodology for urban wind resource assessment," Renewable Energy, Elsevier, vol. 89(C), pages 598-605.
    7. Weekes, S.M. & Tomlin, A.S., 2014. "Comparison between the bivariate Weibull probability approach and linear regression for assessment of the long-term wind energy resource using MCP," Renewable Energy, Elsevier, vol. 68(C), pages 529-539.
    8. Veronesi, F. & Grassi, S. & Raubal, M., 2016. "Statistical learning approach for wind resource assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 836-850.
    9. Weekes, S.M. & Tomlin, A.S., 2014. "Data efficient measure-correlate-predict approaches to wind resource assessment for small-scale wind energy," Renewable Energy, Elsevier, vol. 63(C), pages 162-171.
    10. Hernández-Escobedo, Q. & Saldaña-Flores, R. & Rodríguez-García, E.R. & Manzano-Agugliaro, F., 2014. "Wind energy resource in Northern Mexico," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 890-914.
    11. Luca Salvadori & Annalisa Di Bernardino & Giorgio Querzoli & Simone Ferrari, 2021. "A Novel Automatic Method for the Urban Canyon Parametrization Needed by Turbulence Numerical Simulations for Wind Energy Potential Assessment," Energies, MDPI, vol. 14(16), pages 1-22, August.
    12. Grieser, Benno & Sunak, Yasin & Madlener, Reinhard, 2015. "Economics of small wind turbines in urban settings: An empirical investigation for Germany," Renewable Energy, Elsevier, vol. 78(C), pages 334-350.

    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:renene:v:55:y:2013:i:c:p:202-211. 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.journals.elsevier.com/renewable-energy .

    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.