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Wind resource assessment and comparative economic analysis using AMOS data on a 30 MW wind farm at Yulchon district in Korea

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  • Kim, Hyeonwu
  • Kim, Bumsuk

Abstract

Detailed feasibility studies are necessary for wind farm development projects because the profitability changes greatly according to wind resource, wind turbine, CAPEX (capital expenduture), OPEX (operation expenditure), SMP (system marginal price), and REC (renewable energy certificate) price. Although measuring wind data over one year in the proposed site is essential, it is a cost-intensive and time-consuming process; hence, in the early stages of development, pre-feasibility studies are conducted using reference wind data from the neighboring areas. In the present study, a pre-feasibility study was conducted in Yulchon district of South Korea to develop a 30-MW wind farm. A wind resource map of Yulchon district was predicted using the AMOS (Aerodome Meteorological Observation System) wind data measured at Yeosu Airport. Three cases of wind farms each with different wind turbines were designed, and comparative economic analysis was carried out. The wind farm designed with SL3000/113 wind turbine recorded the highest profitability with project NPV of 33.62 billion KRW(33.29 million USD, 24.33 million EUR) and project IRR of 9.81%.

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  • Kim, Hyeonwu & Kim, Bumsuk, 2016. "Wind resource assessment and comparative economic analysis using AMOS data on a 30 MW wind farm at Yulchon district in Korea," Renewable Energy, Elsevier, vol. 85(C), pages 96-103.
    • Handle: RePEc:eee:renene:v:85:y:2016:i:c:p:96-103
    DOI: 10.1016/j.renene.2015.06.039
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Sajid Ali & Choon-Man Jang, 2019. "Selection of Best-Suited Wind Turbines for New Wind Farm Sites Using Techno-Economic and GIS Analysis in South Korea," Energies, MDPI, vol. 12(16), pages 1-22, August.
    2. Sajid Ali & Sang-Moon Lee & Choon-Man Jang, 2017. "Techno-Economic Assessment of Wind Energy Potential at Three Locations in South Korea Using Long-Term Measured Wind Data," Energies, MDPI, vol. 10(9), pages 1-24, September.
    3. Sajid Ali & Sang-Moon Lee & Choon-Man Jang, 2017. "Determination of the Most Optimal On-Shore Wind Farm Site Location Using a GIS-MCDM Methodology: Evaluating the Case of South Korea," Energies, MDPI, vol. 10(12), pages 1-22, December.
    4. Rabbani, Rabab & Zeeshan, Muhammad, 2022. "Impact of policy changes on financial viability of wind power plants in Pakistan," Renewable Energy, Elsevier, vol. 193(C), pages 789-806.
    5. Mohammed H. Alsharif & Jeong Kim & Jin Hong Kim, 2018. "Opportunities and Challenges of Solar and Wind Energy in South Korea: A Review," Sustainability, MDPI, vol. 10(6), pages 1-23, June.
    6. Laudari, R. & Sapkota, B. & Banskota, K., 2018. "Validation of wind resource in 14 locations of Nepal," Renewable Energy, Elsevier, vol. 119(C), pages 777-786.
    7. Jung, Seunghoon & Jeoung, Jaewon & Kang, Hyuna & Hong, Taehoon, 2021. "Optimal planning of a rooftop PV system using GIS-based reinforcement learning," Applied Energy, Elsevier, vol. 298(C).
    8. Ali, Sajid & Lee, Sang-Moon & Jang, Choon-Man, 2018. "Statistical analysis of wind characteristics using Weibull and Rayleigh distributions in Deokjeok-do Island – Incheon, South Korea," Renewable Energy, Elsevier, vol. 123(C), pages 652-663.

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