Wind resource assessment and comparative economic analysis using AMOS data on a 30 MW wind farm at Yulchon district in Korea. (January 2016)

• Record Type: Journal Article
• Authors: Kim, Hyeonwu; Kim, Bumsuk
• Is Part Of: Renewable energy. Volume 85(2016)
• Page Start: 96
• Page End: 103
• Publication Date: 2016-01
• Subjects: Aerodome meteorological observation system -- Wind resource map -- Wind turbine -- Annual energy production -- Economic analysis; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2015.06.039
• Languages: English
• ISSNs: 0960-1481

Abstract

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%. Highlights: Pre-feasibility study was conducted to develop a 30 MW wind farm in Korea. Economic analysis shows that the proposed site has financial feasibility. Project NPV showed the greatest deviation according to changes in AEP. Project IRR was most sensitive to CAPEX with values at 11.76% Max and 8.26% Min.