기상청 공공데이터를 활용한 대한민국 서해안 일대의 바람자원 분석
Analysis of Wind Energy Potential on the West Coast of South Korea Using Public Data from the Korea Meteorological Administration
2
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
The significance of renewable energy has been on the rise, as evidenced by the 3020 renewable energy plan and the 2050 carbon neutrality strategy, which seek to advance a low-carbon economy by implementing a power supply strategy centered around renewable energy sources. This study examines the wind resources on the west coast of South Korea and confirms the potential for wind power generation in the area. Wind speed data was collected from 22 automatic weather system stations and four light house automatic weather system stations provided by the Korea Meteorological Administration to evaluate potential sites for wind farms. Weibull distribution was used to analyze the wind data and calculate wind power density. Annual energy production and capacity factors were estimated for 15-20 MW-class large wind turbines through the height correction of observed wind speeds. These findings offer valuable information for selecting wind power generation sites, predicting economic feasibility, and determining optimal equipment capacity for future wind power generation sites in the region.
Abstract
The significance of renewable energy has been on the rise, as evidenced by the 3020 renewable energy plan and the 2050 carbon neutrality strategy, which seek to advance a low-carbon economy by implementing a power supply strategy centered around renewable energy sources. This study examines the wind resources on the west coast of South Korea and confirms the potential for wind power generation in the area. Wind speed data was collected from 22 automatic weather system stations and four light house automatic weather system stations provided by the Korea Meteorological Administration to evaluate potential sites for wind farms. Weibull distribution was used to analyze the wind data and calculate wind power density. Annual energy production and capacity factors were estimated for 15-20 MW-class large wind turbines through the height correction of observed wind speeds. These findings offer valuable information for selecting wind power generation sites, predicting economic feasibility, and determining optimal equipment capacity for future wind power generation sites in the region.
참고문헌 (31)
- Kang, D., "Comparative study of different methods for estimating weibull parameters : A case study on Jeju Island, South Korea", Energies, 11(2), pp.1~19 (2018)
- Global wind report 2022, "Global Wind Energy Council(GWEC)", ~ (2022)
- Korea wind energy industry association, "Wind power facilities in operation status 2022edition", ~ (2022)
- Köse, R., "An evaluation of wind energy potential as a power generation source in Kütahya, Turkey", Energy Conversion and Management, 45(11∼12), pp.1631~1641 (2004)
- Kang, S., "Comparison of different statistical methods used to estimate Weibull parameters for wind speed contribution in nearby an offshore site, Republic of Korea", Energy Reports, 7, pp.7358~7373 (2021)
- Mahmoodi, K., "Wind energy potential assessment in the Persian Gulf : A spatial and temporal analysis", Ocean Engineering, 216, pp.107674~ (2020)[DOI]
- Onea, F., "A spatial analysis of the offshore wind energy potential related to the Mediterranean islands", Energy Reports, 8, pp.99~105 (2022)
- Wen, Y., "Assessment of long-term offshore wind energy potential in the south and southeast coasts of China based on a 55-year dataset", Energy, 224, pp.120225~ (2021)[DOI]
- Gualtieri, G., "Analysing the uncertainties of reanalysis data used for wind resource assessment : A critical review", Renewable and Sustainable Energy Reviews, 167, pp.112741~ (2022)[DOI]
- Oh, K. Y., "Wind resource assessment around Korean Peninsula for feasibility study on 100MW class offshore wind farm", Renewable Energy, 42, pp.217~226 (2012)
- 강금석, "터빈설치를 위한 한국 연안 해상풍력발전 부존량 평가", 한국해안·해양공학회논문집, 30(4), pp.191~199 (2018), 한국해안,해양공학회[DOI]
- Murthy, K. S. R., "A comprehensive review of wind resource assessment", Renewable and Sustainable Energy Reviews, 72, pp.1320~1342 (2017)
- 강상균, "새만금 고군산군도 말도 유역에 대한 바람에너지 분석", 풍력에너지저널, 9(4), pp.65~71 (2018), 한국풍력에너지학회[DOI]
- "Open MET data portal"[URL]
- Korea Meteorological Administration, "Ground meteorological observation guidelines", ~ (2016)
- Korea Meteorological Administration, "Meteorological climate data catalog", ~ (2018)
- Hwang, Y. S., "Effectiveness of wind data from automated weather stations for wind resources prediction", Journal of Industrial Technology, (29), pp.181~186 (2009), Kangwon Natl. Univ
- Azad, A. K., "Statistical diagnosis of the best Weibull methods for wind power assessment for agricultural applications", Energies, 7(5), pp.3056~3085 (2014)
- Ryu, K. W., "Development of web-based wind data analysis system for hemosu-1", Journal of Wind Energy, 4(1), pp.60~67 (2013)
- Justus, C. G., "Methods for estimating wind speed frequency distribution", Journal of applied meteorology, 17, pp.350~353 (1978)
- Hove, T., "Mapping wind power density for Zimbabwe : A suitable weibull-parameter calculation method", Journal of Energy in Southern Africa, 25(4), pp.37~47 (2014)
- Shu, Z. R., "Estimation of Weibull parameters for wind energy analysis across the UK", Journal of Renewable and Sustainable Energy, 13(2), pp.1~13 (2021)
- International Electrotechnical Commission, "IEC 61400-12-1, Wind energy generation systems–Part 12-1: Power performance measurements of electricity producing wind turbines", ~ (2017)
- Rabbani, R., "Exploring the suitability of MERRA-2 reanalysis data for wind energy estimation, analysis of wind characteristics and energy potential assessment for selected sites in Pakistan", Renewable Energy, 154, pp.1240~1251 (2020)
- Arenas-López, J. P., "Analysis of the offshore wind resource and its economic assessment in two zones of Mexico", Sustainable Energy Technologies and Assessments, 52, pp.101997~ (2022)[DOI]
- Mirsadeghi, M., "Review of external convective heat transfer coefficient models in building energy simulation programs: Implementation and uncertainty", Applied Thermal Engineering, 56, pp.134~151 (2013)
- Chavan, D. S., "Impact of vertical wind shear on wind turbine performance", 2017International Conference on circuits Power and Computing Technologies, pp.1~6 (2017)
- IEA Wind TCP Task 37: Definition of the IEA 15 MW offshore reference wind turbine, "Gaertner, E.", ~, pp.Technical report NREL (2020), TP-5000-75698
- Upwind 20MW wind turbine pre-design blade design and control, "Peeringa, J.", ~, pp.ECN-11-017 (2011)
- 오기용, "해상부이 데이터 분석을 통한 한반도 해역의 바람자원 평가", 신재생에너지, 7(1), pp.15~21 (2011), 한국신·재생에너지학회
- 김진영, "풍력단지 발전량 예측에 대한 재해석 자료 ERA5의 현장적응", 한국태양에너지학회 논문집, 42(4), pp.79~91 (2022), 한국태양에너지학회[DOI]