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Assessment of urban wind energy resource in Hong Kong based on multi-instrument observations

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Listed:
  • He, J.Y.
  • Chan, P.W.
  • Li, Q.S.
  • Huang, Tao
  • Yim, Steve Hung Lam

Abstract

Urban wind power is an appealing alternative for electricity supply. Comprehensive urban wind resource assessment is a prerequisite for cost-efficient deployment of wind turbines. Based on observations from multiple instruments, including a Doppler lidar (light detection and ranging) system, a microwave radiometer, and a cup anemometer/wind vane set, this study investigates the temporal (interannual, seasonal, and diurnal) variations of wind resources at various heights in a metropolitan city, Hong Kong. The long-term statistical distributions of wind speed, wind shear coefficient, and air density are analyzed, and their variations with height, wind direction, season, and time of day are thoroughly examined. Moreover, the wind power density and capacity factor of prototype wind turbines are estimated. It is observed that the statistical distributions of wind speed and air density are best represented by the Kappa and Normal-Weibull mixture distributions, respectively. There is a significant diurnal variation of wind shear coefficient, from 0.1 in the daytime to 0.4 at night. Moreover, a moderate potential for wind energy harvesting with wind power density of 110 W/m2 is found at the height of 120 m. This is the first known study that jointly uses lidar, microwave radiometer, and anemometer/wind vane for urban wind resource assessment. These instruments enable the investigation of the temporal variations of wind shear coefficient, air density, and wind power density at multiple heights, which were rarely examined in urban wind energy studies before.

Suggested Citation

  • He, J.Y. & Chan, P.W. & Li, Q.S. & Huang, Tao & Yim, Steve Hung Lam, 2024. "Assessment of urban wind energy resource in Hong Kong based on multi-instrument observations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
  • Handle: RePEc:eee:rensus:v:191:y:2024:i:c:s1364032123009814
    DOI: 10.1016/j.rser.2023.114123
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    References listed on IDEAS

    as
    1. Wang, Qiang & Wang, Jianwen & Hou, Yali & Yuan, Renyu & Luo, Kun & Fan, Jianren, 2018. "Micrositing of roof mounting wind turbine in urban environment: CFD simulations and lidar measurements," Renewable Energy, Elsevier, vol. 115(C), pages 1118-1133.
    2. Karthikeya, B.R. & Negi, Prabal S. & Srikanth, N., 2016. "Wind resource assessment for urban renewable energy application in Singapore," Renewable Energy, Elsevier, vol. 87(P1), pages 403-414.
    3. Li, Q.S. & Shu, Z.R. & Chen, F.B., 2016. "Performance assessment of tall building-integrated wind turbines for power generation," Applied Energy, Elsevier, vol. 165(C), pages 777-788.
    4. Gao, Xiaoxia & Yang, Hongxing & Lu, Lin, 2014. "Study on offshore wind power potential and wind farm optimization in Hong Kong," Applied Energy, Elsevier, vol. 130(C), pages 519-531.
    5. Škvorc, Petar & Kozmar, Hrvoje, 2021. "Wind energy harnessing on tall buildings in urban environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    6. Barrows, S.E. & Homer, J.S. & Orrell, A.C., 2021. "Valuing wind as a distributed energy resource: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    7. Navid Goudarzi & Kasra Mohammadi & Alexandra St. Pé & Ruben Delgado & Weidong Zhu, 2020. "Wind Resource Assessment and Economic Viability of Conventional and Unconventional Small Wind Turbines: A Case Study of Maryland," Energies, MDPI, vol. 13(22), pages 1-15, November.
    8. Chang, Tian-Pau & Liu, Feng-Jiao & Ko, Hong-Hsi & Cheng, Shih-Ping & Sun, Li-Chung & Kuo, Shye-Chorng, 2014. "Comparative analysis on power curve models of wind turbine generator in estimating capacity factor," Energy, Elsevier, vol. 73(C), pages 88-95.
    9. Gabriele Manoli & Simone Fatichi & Markus Schläpfer & Kailiang Yu & Thomas W. Crowther & Naika Meili & Paolo Burlando & Gabriel G. Katul & Elie Bou-Zeid, 2019. "Magnitude of urban heat islands largely explained by climate and population," Nature, Nature, vol. 573(7772), pages 55-60, September.
    10. He, J.Y. & Chan, P.W. & Li, Q.S. & Tong, H.W., 2023. "Mapping future offshore wind resources in the South China Sea under climate change by regional climate modeling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    11. Juan, Yu-Hsuan & Wen, Chih-Yung & Li, Zhengtong & Yang, An-Shik, 2021. "Impacts of urban morphology on improving urban wind energy potential for generic high-rise building arrays," Applied Energy, Elsevier, vol. 299(C).
    12. 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.
    13. Christopher Jung & Dirk Schindler, 2022. "Development of onshore wind turbine fleet counteracts climate change-induced reduction in global capacity factor," Nature Energy, Nature, vol. 7(7), pages 608-619, July.
    14. Chang, Tian Pau, 2011. "Performance comparison of six numerical methods in estimating Weibull parameters for wind energy application," Applied Energy, Elsevier, vol. 88(1), pages 272-282, January.
    15. Shu, Z.R. & Li, Q.S. & Chan, P.W., 2015. "Investigation of offshore wind energy potential in Hong Kong based on Weibull distribution function," Applied Energy, Elsevier, vol. 156(C), pages 362-373.
    16. 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.
    17. He, J.Y. & Chan, P.W. & Li, Q.S. & Lee, C.W., 2022. "Characterizing coastal wind energy resources based on sodar and microwave radiometer observations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    18. Jung, Christopher & Schindler, Dirk, 2019. "Wind speed distribution selection – A review of recent development and progress," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    19. Carta, José A. & Velázquez, Sergio & Cabrera, Pedro, 2013. "A review of measure-correlate-predict (MCP) methods used to estimate long-term wind characteristics at a target site," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 362-400.
    20. Gualtieri, Giovanni, 2019. "A comprehensive review on wind resource extrapolation models applied in wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 215-233.
    21. Emejeamara, F.C. & Tomlin, A.S., 2020. "A method for estimating the potential power available to building mounted wind turbines within turbulent urban air flows," Renewable Energy, Elsevier, vol. 153(C), pages 787-800.
    22. Simões, Teresa & Estanqueiro, Ana, 2016. "A new methodology for urban wind resource assessment," Renewable Energy, Elsevier, vol. 89(C), pages 598-605.
    23. Foley, Aoife M. & Leahy, Paul G. & Marvuglia, Antonino & McKeogh, Eamon J., 2012. "Current methods and advances in forecasting of wind power generation," Renewable Energy, Elsevier, vol. 37(1), pages 1-8.
    24. Matthew Gough & Mohamed Lotfi & Rui Castro & Amos Madhlopa & Azeem Khan & João P. S. Catalão, 2019. "Urban Wind Resource Assessment: A Case Study on Cape Town," Energies, MDPI, vol. 12(8), pages 1-20, April.
    25. He, Junyi & Chan, P.W. & Li, Qiusheng & Lee, C.W., 2020. "Spatiotemporal analysis of offshore wind field characteristics and energy potential in Hong Kong," Energy, Elsevier, vol. 201(C).
    26. He, J.Y. & Li, Q.S. & Chan, P.W. & Zhao, X.D., 2023. "Assessment of future wind resources under climate change using a multi-model and multi-method ensemble approach," Applied Energy, Elsevier, vol. 329(C).
    27. Ryan Wiser & Joseph Rand & Joachim Seel & Philipp Beiter & Erin Baker & Eric Lantz & Patrick Gilman, 2021. "Expert elicitation survey predicts 37% to 49% declines in wind energy costs by 2050," Nature Energy, Nature, vol. 6(5), pages 555-565, May.
    28. Juan, Yu-Hsuan & Rezaeiha, Abdolrahim & Montazeri, Hamid & Blocken, Bert & Wen, Chih-Yung & Yang, An-Shik, 2022. "CFD assessment of wind energy potential for generic high-rise buildings in close proximity: Impact of building arrangement and height," Applied Energy, Elsevier, vol. 321(C).
    29. Shu, Z.R. & Li, Q.S. & He, Y.C. & Chan, P.W., 2016. "Observations of offshore wind characteristics by Doppler-LiDAR for wind energy applications," Applied Energy, Elsevier, vol. 169(C), pages 150-163.
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