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Wind Farm Site Selection Using WAsP Tool for Application in the Tropical Region

Author

Listed:
  • Ismail Kamdar

    (Energy Technology Program, Faculty of Engineering, Prince of Songkla University, Hat Yai 90110, Songkhla, Thailand)

  • Shahid Ali

    (School of Engineering and Built Environment, Griffith University, Southport, QLD 4222, Australia)

  • Juntakan Taweekun

    (Department of Mechanical and Mechatronics Engineering, Faculty of Engineering, Prince of Songkla University, Hat Yai 90110, Songkhla, Thailand)

  • Hafiz Muhammad Ali

    (Mechanical Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Saudi Arabia
    Interdisciplinary Research Center for Renewable Energy and Power Systems (IRC–REPS), King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia)

Abstract

Wind energy is one of the most promising renewable energy technologies worldwide; however, assessing potential sites for wind energy exploitation is a challenging task. This study presents a site suitability analysis to develop a small–scale wind farm in south–eastern Thailand. To this aim, the most recent available data from 2017 to 2019, recorded near the surface, at nine weather stations of the Thai Meteorological Department (TMD) were acquired. The analysis was conducted using standard wind–industry software WAsP. It was found that the mountain peaks and ridges are highly suitable for small–scale wind farm development. Nevertheless, the wind data analysis indicates that regions fall in low–to–moderate wind classes. The selected sites in south–eastern Thailand have mean wind speeds ranging from 5.1 m/s to 9.4 m/s. Moreover, annual energy production (AEP) of 102 MWh to 311 MWh could be generated using an Enercon E–18 wind turbine with a rated power of 80-kW at the hub height of 28.5 m. The Levelized Cost of Energy (LCOE) reveals that the development cost of a small–scale wind farm is lowest in the Songkhla and Yala provinces of Thailand, therefore these two locations from the investigated study region are financially most suitable. The findings could encourage researchers to further investigate low–speed wind energy mechanisms in tropical regions, and the demonstrated approach could be reused for other regions.

Suggested Citation

  • Ismail Kamdar & Shahid Ali & Juntakan Taweekun & Hafiz Muhammad Ali, 2021. "Wind Farm Site Selection Using WAsP Tool for Application in the Tropical Region," Sustainability, MDPI, vol. 13(24), pages 1-25, December.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:24:p:13718-:d:700786
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    References listed on IDEAS

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    Cited by:

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    2. Mohammed Ifkirne & Houssam El Bouhi & Siham Acharki & Quoc Bao Pham & Abdelouahed Farah & Nguyen Thi Thuy Linh, 2022. "Multi-Criteria GIS-Based Analysis for Mapping Suitable Sites for Onshore Wind Farms in Southeast France," Land, MDPI, vol. 11(10), pages 1-26, October.
    3. Wimhurst, Joshua J. & Greene, J. Scott & Koch, Jennifer, 2023. "Predicting commercial wind farm site suitability in the conterminous United States using a logistic regression model," Applied Energy, Elsevier, vol. 352(C).
    4. Bukurije Hoxha & Igor K. Shesho & Risto V. Filkoski, 2022. "Analysis of Wind Turbine Distances Using a Novel Techno-Spatial Approach in Complex Wind Farm Terrains," Sustainability, MDPI, vol. 14(20), pages 1-16, October.

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