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Wind Resource Assessment of the Southernmost Region of Thailand Using Atmospheric and Computational Fluid Dynamics Wind Flow Modeling

Author

Listed:
  • Jompob Waewsak

    (Research Center in Energy and Environment, Division of Physics, Faculty of Science, Thaksin University (Phatthalung Campus), Songkhla 90000, Thailand)

  • Chana Chancham

    (Research Center in Energy and Environment, Division of Physics, Faculty of Science, Thaksin University (Phatthalung Campus), Songkhla 90000, Thailand)

  • Somphol Chiwamongkhonkarn

    (Research Center in Energy and Environment, Division of Physics, Faculty of Science, Thaksin University (Phatthalung Campus), Songkhla 90000, Thailand)

  • Yves Gagnon

    (Department of Sciences, Université de Moncton, Edmundston, NB E3V 2S8, Canada)

Abstract

This paper presents the wind resource assessment of the southernmost region of Thailand using atmospheric and computational fluid dynamics (CFD) wind flow modeling. The predicted wind data by the Weather Research and Forecasting (WRF) atmospheric modeling, assimilated to a virtual met mast, along with high-resolution topographic and roughness digital data, are then used as the main input for the CFD microscale wind flow modeling and high resolution wind resource mapping at elevations of 80 m, 100 m, 120 m, and 140 m agl. Numerical results are validated using measured wind data. Results show that the potential area where the wind speeds at 120 m agl are above 8.0 m/s is 86 km 2 , corresponding to a technical power potential in the order of 300 MW. The installation of wind power plants in the areas with the best wind resource could generate 690 GWh/year of electricity, thus avoiding greenhouse gas emissions of 1.2 million tonnes CO 2eq /year to the atmosphere. On the other hand, developing power plants with International Electrotechnical Commission (IEC) Class IV wind turbines in areas of lower wind resource, but with easier access, could generate nearly 3000 GWh/yr of energy, with a CO 2eq emissions avoidance of 5 million tonnes CO 2eq on a yearly basis.

Suggested Citation

  • Jompob Waewsak & Chana Chancham & Somphol Chiwamongkhonkarn & Yves Gagnon, 2019. "Wind Resource Assessment of the Southernmost Region of Thailand Using Atmospheric and Computational Fluid Dynamics Wind Flow Modeling," Energies, MDPI, vol. 12(10), pages 1-18, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:10:p:1899-:d:232332
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    References listed on IDEAS

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    1. Nicolas Gasset & Mathieu Landry & Yves Gagnon, 2012. "A Comparison of Wind Flow Models for Wind Resource Assessment in Wind Energy Applications," Energies, MDPI, vol. 5(11), pages 1-35, October.
    2. Karagali, Ioanna & Badger, Merete & Hahmann, Andrea N. & Peña, Alfredo & B. Hasager, Charlotte & Sempreviva, Anna Maria, 2013. "Spatial and temporal variability of winds in the Northern European Seas," Renewable Energy, Elsevier, vol. 57(C), pages 200-210.
    3. Waewsak, Jompob & Landry, Mathieu & Gagnon, Yves, 2015. "Offshore wind power potential of the Gulf of Thailand," Renewable Energy, Elsevier, vol. 81(C), pages 609-626.
    4. Oh, Ki-Yong & Kim, Ji-Young & Lee, Jun-Shin & Ryu, Ki-Wahn, 2012. "Wind resource assessment around Korean Peninsula for feasibility study on 100 MW class offshore wind farm," Renewable Energy, Elsevier, vol. 42(C), pages 217-226.
    5. Waewsak, Jompob & Landry, Mathieu & Gagnon, Yves, 2013. "High resolution wind atlas for Nakhon Si Thammarat and Songkhla provinces, Thailand," Renewable Energy, Elsevier, vol. 53(C), pages 101-110.
    6. Giannaros, Theodore M. & Melas, Dimitrios & Ziomas, Ioannis, 2017. "Performance evaluation of the Weather Research and Forecasting (WRF) model for assessing wind resource in Greece," Renewable Energy, Elsevier, vol. 102(PA), pages 190-198.
    7. Chingulpitak, Sakkarin & Wongwises, Somchai, 2014. "Critical review of the current status of wind energy in Thailand," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 312-318.
    8. Nor, Khalid Mohamed & Shaaban, Mohamed & Abdul Rahman, Hasimah, 2014. "Feasibility assessment of wind energy resources in Malaysia based on NWP models," Renewable Energy, Elsevier, vol. 62(C), pages 147-154.
    9. De Meij, A. & Vinuesa, J.-F. & Maupas, V. & Waddle, J. & Price, I. & Yaseen, B. & Ismail, A., 2016. "Wind energy resource mapping of Palestine," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 551-562.
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    Cited by:

    1. Waewsak, Jompob & Ali, Shahid & Natee, Warut & Kongruang, Chuleerat & Chancham, Chana & Gagnon, Yves, 2020. "Assessment of hybrid, firm renewable energy-based power plants: Application in the southernmost region of Thailand," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    2. Lattawan Niyomtham & Charoenporn Lertsathittanakorn & Jompob Waewsak & Yves Gagnon, 2022. "Mesoscale/Microscale and CFD Modeling for Wind Resource Assessment: Application to the Andaman Coast of Southern Thailand," Energies, MDPI, vol. 15(9), pages 1-19, April.

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