Journal of Wind Energy (풍력에너지저널)

Korea Wind Energy Association (한국풍력에너지학회)
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Evaluation Study of LCOE for 8 MW Offshore Floating Wind Turbine in Ulsan Region

울산 앞바다 8 MW급 부유식 해상풍력터빈의 LCOE 연구

  • Dong Hoon Lee ;
  • Hee Chang Lim
  • 이동훈 (부산대학교 기계공학부) ;
  • 임희창 (부산대학교 기계공학부 )
  • Received : 2022.07.22
  • Accepted : 2023.01.30
  • Published : 2023.03.31
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Abstract

The commercialization has been of great importance to the clean energy research sector for investing the wind farm development, but it would be difficult to reach a social consensus on the need to expand the economic feasibility of renewable energy due to the lack of reliable and continuous information on levelized cost of Energy (LCOE). Regarding this fact, this paper presents the evaluation of LCOE, focusing on Ulsan offshore region targeting to build the first floating offshore wind farm. Energy production is estimated by the meteorology data combined with the Leanwind Project power curve of an exemplar wind turbine. This work aims to analyze the costs of the Capex depending on site-specific variables. The cost of final LCOE was estimated by using Monte-Carlo method, and it became an average range 297,090 KRW/MWh, a minimum of 251,080 KRW/MWh, and a maximum of 341,910 KRW/MWh. In the year 2021, the SMP (system marginal price) and 4.5 REC (renewable energy certificate) can be paid if 1 MWh of electricity is generated by renewable energy. Considering current SMP and REC price, the floating platform industry, which can earn around 502,000 KRW/MWh, can be finally estimated highly competitive in the Korean market.

Keywords

Acknowledgement

본 연구는 한국전력공사의 2021년 착수 기초연구개발 과제연구비에 의해 지원되었음(과제 번호 : R21XO02-12). 그리고, 본 과제(결과물)는 교육부와 한국연구재단의 재원으로 지원을 받아 수행된 3단계 산학연협력 선도대학 육성사업(LINC 3.0)의 연구결과입니다. 또한, 본 연구는 2022년도 중소기업기술혁신개발사업의 재원으로 중소벤처기업부(TIPA)의 지원을 받아 수행한 연구과제입니다. (No. S3313372 실고장 데이터 기반 머신러닝 탑재 풍력발전기 진동 및 모션증폭 설비진단 시각화 시스템의 개발)

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