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Wind energy potential assessment for the offshore areas of Taiwan west coast and Penghu Archipelago

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  • Fang, Hsin-Fa

Abstract

The average wind speed and wind power density of Taiwan had been evaluated at 10 m, 30 m and 50 m by simulation of mesoscale numerical weather prediction model (MM5). The results showed that wind energy potential of this area is excellent. Taiwan has offered funds to encourage the founding of offshore wind farms in this area. The purpose of this study is to make a high resolution wind energy assessment for the offshore area of Taiwan west coast and Penghu archipelago by using WAsP. The result of this study has been used to the relative financial planning of offshore wind farm projects in Taiwan. The basic inputs of WAsP include wind weather data and terrain data. The wind weather data was from a monitoring station located on a remote island, Tongi, because that all of weather stations in the area of Taiwan west coast are affected by urbanization. SRTM was selected to be used as terrain data and downloaded from CGIAR-CSI for voids problem. The coverage of considered terrain area in this assessment work is about 300 km × 400 km that made some difficulties to run wind energy assessment of the whole area with a high resolution of 100 m. So the interested area of this study is divided into 19 areas for the wind energy assessment and mapping. The assessment results show the Changhua area has best wind energy potential in the area of Taiwan west coast which power density is above 1000 W/m2 height and the areas of Penghu archipelago are above 1300 W. These results are higher than the expected from NWP. 180 of 3 MW wind turbines were used in the study of micro sitting in the Changhua area.

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  • Fang, Hsin-Fa, 2014. "Wind energy potential assessment for the offshore areas of Taiwan west coast and Penghu Archipelago," Renewable Energy, Elsevier, vol. 67(C), pages 237-241.
    • Handle: RePEc:eee:renene:v:67:y:2014:i:c:p:237-241
    DOI: 10.1016/j.renene.2013.11.047
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    References listed on IDEAS

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    1. Kim, Choong-Ki & Jang, Seonju & Kim, Tae Yun, 2018. "Site selection for offshore wind farms in the southwest coast of South Korea," Renewable Energy, Elsevier, vol. 120(C), pages 151-162.
    2. Birgir Freyr Ragnarsson & Gudmundur V. Oddsson & Runar Unnthorsson & Birgir Hrafnkelsson, 2015. "Levelized Cost of Energy Analysis of a Wind Power Generation System at Búrfell in Iceland," Energies, MDPI, vol. 8(9), pages 1-22, September.
    3. Nguyen, Thi Anh Tuyet & Chou, Shuo-Yan, 2018. "Impact of government subsidies on economic feasibility of offshore wind system: Implications for Taiwan energy policies," Applied Energy, Elsevier, vol. 217(C), pages 336-345.
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    6. 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.
    7. Ke-Sheng Cheng & Cheng-Yu Ho & Jen-Hsin Teng, 2020. "Wind Characteristics in the Taiwan Strait: A Case Study of the First Offshore Wind Farm in Taiwan," Energies, MDPI, vol. 13(24), pages 1-21, December.
    8. Shih-Chieh Liao & Shih-Chieh Chang & Tsung-Chi Cheng, 2021. "Managing the Volatility Risk of Renewable Energy: Index Insurance for Offshore Wind Farms in Taiwan," Sustainability, MDPI, vol. 13(16), pages 1-27, August.
    9. Yong Wan & Chenqing Fan & Yongshou Dai & Ligang Li & Weifeng Sun & Peng Zhou & Xiaojun Qu, 2018. "Assessment of the Joint Development Potential of Wave and Wind Energy in the South China Sea," Energies, MDPI, vol. 11(2), pages 1-26, February.
    10. 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.
    11. Li, Yi & Wu, Xiao-Peng & Li, Qiu-Sheng & Tee, Kong Fah, 2018. "Assessment of onshore wind energy potential under different geographical climate conditions in China," Energy, Elsevier, vol. 152(C), pages 498-511.
    12. Chuang, Ming-Tung & Chang, Shih-Yu & Hsiao, Ta-Chih & Lu, Yun-Ru & Yang, Tsung-Yeh, 2019. "Analyzing major renewable energy sources and power stability in Taiwan by 2030," Energy Policy, Elsevier, vol. 125(C), pages 293-306.
    13. Commin, Andrew N. & French, Andrew S. & Marasco, Matteo & Loxton, Jennifer & Gibb, Stuart W. & McClatchey, John, 2017. "The influence of the North Atlantic Oscillation on diverse renewable generation in Scotland," Applied Energy, Elsevier, vol. 205(C), pages 855-867.
    14. Jing-Jin Tieo & Tieh-Yong Koh & Martin Skote & Narasimalu Srikanth, 2018. "Variance Characteristics of Tropical Radiosonde Winds Using a Vector-Tensor Method," Energies, MDPI, vol. 11(1), pages 1-22, January.
    15. Majidi Nezhad, M. & Heydari, A. & Groppi, D. & Cumo, F. & Astiaso Garcia, D., 2020. "Wind source potential assessment using Sentinel 1 satellite and a new forecasting model based on machine learning: A case study Sardinia islands," Renewable Energy, Elsevier, vol. 155(C), pages 212-224.
    16. 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.
    17. Nie, Bingchuan & Li, Jiachun, 2018. "Technical potential assessment of offshore wind energy over shallow continent shelf along China coast," Renewable Energy, Elsevier, vol. 128(PA), pages 391-399.

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