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An Integrated Approach to Predict Wind Resource Energy from an Urban Wind Turbine in a Complex Built Environment

Received: 30 June 2021     Accepted: 15 July 2021     Published: 27 July 2021
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Abstract

Introducing an urban wind turbine in the crowded and complex City of North Sydney built environment can provide a significant opportunity to generate onsite wind energy and reduce electric demand and utility costs. Elevated turbulent conditions present a number of well-known challenges to urban wind turbines and as a result the energy production may reduce due to changes in wind speeds and directions. This current case study presents a procedure to optimize urban wind turbine energy production comprising key steps which include the project site potential for the installation of wind turbines, the estimation of the annual wind power available and the cost estimate for installation and maintenance. The wind potential for the project site was initially determined from statistical wind data cross-referenced with typical weather data for the Sydney region. Computational Fluid Dynamics (CFD) simulations of principal wind directions were then used to adjust the local wind climate data and establish a suitable wind turbine position. Finally, the annual energy production for a number of 10-20 kW commercially available wind turbines was estimated taking into account the wind turbine power curve and technical specifications. The CFD simulations in the current study accounted for the complex site topography and incorporated the shielding impact of nearby trees and other vegetation in order to find the least turbulent area for a successful installation. This study assessed all the parameters that have impact on the accuracy of the numerical model including, computational domain, mesh distribution, numerical scheme and CFD results integration with the localized weather data for the project site.

Published in Fluid Mechanics (Volume 7, Issue 2)
DOI 10.11648/j.fm.20210702.11
Page(s) 17-28
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

CFD, Urban Wind Energy, Urban Wind Turbines, Complex Terrain, Tree Modelling

References
[1] Cace, J, Horst, E., Syngellakis, K, Niel, M., Clement, A., Heppener, R., Peiranon, E. (2007). Urban Wind Turbines Guidelines for Small Wind Turbines in the Built Environment, Intelligent Energy Europe.
[2] Wineur (2007). Urban Wind Turbines Technology Review: A text to the Catalogue of European Urban Wind Turbine Manufacturers, Intelligent Energy Europe, 1-9.
[3] NSW Small Wind Turbine Consumer Guide (2010). NSW Office of Environmental and Heritage, 1-73. https://www.environment.nsw.gov.au/resources/households/NSWSmallWindTurbineConsumerGuide.pdf.
[4] Warwick Wind Trials Project: Final Report (2009). Encraft Project, UK.
[5] Smith, J., Forsyth, T., Sinclair, K., Oteri, F. (2012). Built-Environment Wind Turbine Roadmap; Technical Report NREL/TP-5000-50499, National Renewable Energy Laboratory: Golden, CO, USA.
[6] Biswal, G., Shukla, S. (2015) Site Selection for Wind Farm Installation, IJIREEICE 3 (8), 2321-2004.
[7] Hymas, M. (2012). Wind Energy in the Built Environment, Metropolitan Sustainability, 457-499.
[8] Tian, L., Zhu, W., Shen, W., Zhao. N., Shen, Z. (2015). Development and Validation of a New two-dimensional Wake Model for Wind Turbines. Journal of Wind Engineering an Industrial Aerodynamics, 137, 90-99.
[9] Wind PRO (2017). Remote sensing data and other data for download in Wind PRO. Web: http://www.emd.dk/files/windpro/WindPRO_OnlineData.pdf
[10] Open wind (2017), Web: http://software.awstruepower.com/openwind.
[11] Bckmore, P. (2008). Siting Micro-Wind Turbines on House Roofs; IHS BRE Press: Watford, UK, 1–25.
[12] Blocken, B., Stathopoulos, T. (2013). CFD Simulation of Pedestrian-level Wind Conditions Around Buildings: Past Achievements and Prospects, International Journal of Wind Engineering & Industrial Aerodynamics, Editorial to Virtual Special Issue, 1-14.
[13] Franke, J., Hirsch, C., Jensen, A., Krüs, H., Schatzmann, M., Westbury, P., Miles, S., J. Wisse, N Wright N. (2004). Recommendations on the use of CFD in Wind Engineering, International Conference on Urban Wind Engineering and Building Aerodynamics (Ed. van Beeck JPAJ).
[14] Al-Khalidy, N. (2016). The Role of Computational Fluid Dynamics in Solving Wind Engineering Problems, IEEE Computer Society Conference Publishing Services, Crete, Greece, ISBN: 978-960-474-398-8, 109-116.
[15] Al-Khalidy, N. (2012). Designing Better Building with Computational Fluid Dynamics Analysis, 4th International Congress on Computational Engineering and Sciences, Las Vegas, University of Nevada, Reno, USA.
[16] Al-Khalidy, N. (2018) Building Generated Wind Shear and Turbulence Prediction utilising Computational Fluid Dynamics, WSEAS Transactions on Fluid Mechanics, 13, 126-135.
[17] Toja-Silva, Kono, T., Peralta, C., Lopez-Garcia, O., Chen, J. (2018). A review of computational fluid dynamics (CFD) simulations of the wind flow around buildings for urban wind energy exploitation, Journal of Wind Engineering and Industrial Aerodynamics, INDAER, 3675, 2018.
[18] Pierik, J., Dekker, J., Braam, H., Bulder, B., Winkelaar, D., Larsen, G., Morfiadakis, E., Chaviaropoulos, P., Derrick, A., Molly, J. (1999). Wind energy for the Next Millennium. In Proceedings of the European Wind Energy Conference, Nice, France, 1–5.
[19] Yang, A., Su, Y., Wen, C., Juan, Y., Wang, W., Chen, C. (2016) Estimation of Wind Power Generation in Dense Urban Area, Applied Energy, 171, 213-230.
[20] Lanzafame's Lab. (2019). Micro H-Darrieus Wind Turbines: CFD Modeling and Experimental Validation, AIP Conference Proceedings, DOI: 10.1063/1.5138842
[21] Kono, T., Kogaki, T., and Kiwata, T. (2016). Numerical Investigation of Wind Conditions for Roof-Mounted Wind Turbines: Effects of Wind Direction and Horizontal Aspect Ratio of a High-Rise Cuboid Building, Energies, 9, 907.
[22] Ansys Fluent Theory Manual (2019), ANSYS, USA.
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  • APA Style

    Neihad Hussen Al-Khalidy. (2021). An Integrated Approach to Predict Wind Resource Energy from an Urban Wind Turbine in a Complex Built Environment. Fluid Mechanics, 7(2), 17-28. https://doi.org/10.11648/j.fm.20210702.11

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    ACS Style

    Neihad Hussen Al-Khalidy. An Integrated Approach to Predict Wind Resource Energy from an Urban Wind Turbine in a Complex Built Environment. Fluid Mech. 2021, 7(2), 17-28. doi: 10.11648/j.fm.20210702.11

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    AMA Style

    Neihad Hussen Al-Khalidy. An Integrated Approach to Predict Wind Resource Energy from an Urban Wind Turbine in a Complex Built Environment. Fluid Mech. 2021;7(2):17-28. doi: 10.11648/j.fm.20210702.11

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  • @article{10.11648/j.fm.20210702.11,
      author = {Neihad Hussen Al-Khalidy},
      title = {An Integrated Approach to Predict Wind Resource Energy from an Urban Wind Turbine in a Complex Built Environment},
      journal = {Fluid Mechanics},
      volume = {7},
      number = {2},
      pages = {17-28},
      doi = {10.11648/j.fm.20210702.11},
      url = {https://doi.org/10.11648/j.fm.20210702.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.fm.20210702.11},
      abstract = {Introducing an urban wind turbine in the crowded and complex City of North Sydney built environment can provide a significant opportunity to generate onsite wind energy and reduce electric demand and utility costs. Elevated turbulent conditions present a number of well-known challenges to urban wind turbines and as a result the energy production may reduce due to changes in wind speeds and directions. This current case study presents a procedure to optimize urban wind turbine energy production comprising key steps which include the project site potential for the installation of wind turbines, the estimation of the annual wind power available and the cost estimate for installation and maintenance. The wind potential for the project site was initially determined from statistical wind data cross-referenced with typical weather data for the Sydney region. Computational Fluid Dynamics (CFD) simulations of principal wind directions were then used to adjust the local wind climate data and establish a suitable wind turbine position. Finally, the annual energy production for a number of 10-20 kW commercially available wind turbines was estimated taking into account the wind turbine power curve and technical specifications. The CFD simulations in the current study accounted for the complex site topography and incorporated the shielding impact of nearby trees and other vegetation in order to find the least turbulent area for a successful installation. This study assessed all the parameters that have impact on the accuracy of the numerical model including, computational domain, mesh distribution, numerical scheme and CFD results integration with the localized weather data for the project site.},
     year = {2021}
    }
    

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    T1  - An Integrated Approach to Predict Wind Resource Energy from an Urban Wind Turbine in a Complex Built Environment
    AU  - Neihad Hussen Al-Khalidy
    Y1  - 2021/07/27
    PY  - 2021
    N1  - https://doi.org/10.11648/j.fm.20210702.11
    DO  - 10.11648/j.fm.20210702.11
    T2  - Fluid Mechanics
    JF  - Fluid Mechanics
    JO  - Fluid Mechanics
    SP  - 17
    EP  - 28
    PB  - Science Publishing Group
    SN  - 2575-1816
    UR  - https://doi.org/10.11648/j.fm.20210702.11
    AB  - Introducing an urban wind turbine in the crowded and complex City of North Sydney built environment can provide a significant opportunity to generate onsite wind energy and reduce electric demand and utility costs. Elevated turbulent conditions present a number of well-known challenges to urban wind turbines and as a result the energy production may reduce due to changes in wind speeds and directions. This current case study presents a procedure to optimize urban wind turbine energy production comprising key steps which include the project site potential for the installation of wind turbines, the estimation of the annual wind power available and the cost estimate for installation and maintenance. The wind potential for the project site was initially determined from statistical wind data cross-referenced with typical weather data for the Sydney region. Computational Fluid Dynamics (CFD) simulations of principal wind directions were then used to adjust the local wind climate data and establish a suitable wind turbine position. Finally, the annual energy production for a number of 10-20 kW commercially available wind turbines was estimated taking into account the wind turbine power curve and technical specifications. The CFD simulations in the current study accounted for the complex site topography and incorporated the shielding impact of nearby trees and other vegetation in order to find the least turbulent area for a successful installation. This study assessed all the parameters that have impact on the accuracy of the numerical model including, computational domain, mesh distribution, numerical scheme and CFD results integration with the localized weather data for the project site.
    VL  - 7
    IS  - 2
    ER  - 

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Author Information
  • CFD, Wind & Energy Technical Discipline, SLR Consulting, Sydney, Australia

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