풍력기상자원지도 산출방법에 따른 풍력자원 비교
Comparison of Wind Resource Characteristics in Korea According to Different Mapping Method
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초록
Two types of wind resource maps for Korea were developed. The first wind resource map was a TMY (TypicalMeteorological Year) wind resource map based on the WRF (Weather Research and Forecasting) model using the NCEP FNL for theTMY period from 1998 to 2009. The second wind resource map was a KLAPS (Korea Local Analysis and Prediction System) windresource map based on the WRF model using the high resolution KLAPS reanalysis data of a continuous period from 2010 to 2013. Acomparative verification was carried out using the observation data of the ASOS sites. The KLAPS wind resource map was improvedby 17.9% (0.24 m s-1, mean bias) and 10.6% (0.24 m s-1, mean RMSE) compared to the TMY wind resource map. The wind speedverification at an 80 m height of the KLAPS wind resource map was conducted for the Gochang site (onshore) and HeMOSU-1 site(offshore). As a result, the bias was 0.5 m s-1and -0.2 m s-1, and the RMSE was 2.1 m s-1and 2.0 m s-1, respectively. The wind speed ofthe KLAPS wind resource map was strong in winter (onshore) and spring (offshore), and weak in summer. Moreover the wind speedduring the daytime was stronger than that at night. The wind resource map depicted the average wind speed, maximum wind speed,prevailing wind direction, frequency of 3 ~ 25 m s-1wind speed, and Weibull distribution in major wind farms for the development ofwind energy.
Abstract
Two types of wind resource maps for Korea were developed. The first wind resource map was a TMY (TypicalMeteorological Year) wind resource map based on the WRF (Weather Research and Forecasting) model using the NCEP FNL for theTMY period from 1998 to 2009. The second wind resource map was a KLAPS (Korea Local Analysis and Prediction System) windresource map based on the WRF model using the high resolution KLAPS reanalysis data of a continuous period from 2010 to 2013. Acomparative verification was carried out using the observation data of the ASOS sites. The KLAPS wind resource map was improvedby 17.9% (0.24 m s-1, mean bias) and 10.6% (0.24 m s-1, mean RMSE) compared to the TMY wind resource map. The wind speedverification at an 80 m height of the KLAPS wind resource map was conducted for the Gochang site (onshore) and HeMOSU-1 site(offshore). As a result, the bias was 0.5 m s-1and -0.2 m s-1, and the RMSE was 2.1 m s-1and 2.0 m s-1, respectively. The wind speed ofthe KLAPS wind resource map was strong in winter (onshore) and spring (offshore), and weak in summer. Moreover the wind speedduring the daytime was stronger than that at night. The wind resource map depicted the average wind speed, maximum wind speed,prevailing wind direction, frequency of 3 ~ 25 m s-1wind speed, and Weibull distribution in major wind farms for the development ofwind energy.
참고문헌 (25)
- "Global Wind Report : Annual market updata 2015" (2016)[URL]
- "Global Wind 2006 Report" (2007)[URL]
- Kim, T. Y., "Offshore wind farm site selection study around Jeju island, South Korea", Renew. Energy, 94, pp.619~628 (2016)
- 김현구, "수치바람모의에 의한 저해상도 국가 바람지도의 구축", 한국태양에너지학회 논문집, 26(4), pp.31~38 (2006), 한국태양에너지학회
- 김현구, "남한 풍력자원 잠재량의 예비적 산정", 한국태양에너지학회 논문집, 28(6), pp.1~7 (2008), 한국태양에너지학회
- 이순환, "한반도 풍력 자원 지도의 공간 해상도가 풍력자원 예측 정확도에 미치는 영향에 관한 수치연구", 한국환경과학회지, 18(8), pp.885~897 (2009), 한국환경과학회
- 김현구, "한반도 풍력자원지도 - 2010년판", 한국풍공학회지, 16(4), pp.167~172 (2012), 한국풍공학회
- 김현구, "상업용 남한 풍력자원지도의 비교분석", 한국풍공학회지, 19(1), pp.11~16 (2015), 한국풍공학회
- 변재영, "중규모 모델 WRF로부터 모의된 한반도 풍력-기상자원 특성 Characteristics of a Wind Map over the Korean Peninsula Based on Mesoscale Model WRF", 대기, 20(2), pp.195~210 (2010), 한국기상학회
- 김혜중, "통계적 바람장모형에의한 고해상도(1Km×1Km)풍력에너지지도 작성에 관한 연구", 응용통계연구, 23(6), pp.1157~1167 (2010), 한국통계학회
- Xue, Y., "A review on regional dynamical downscaing in intraseasonal to seasonal simulation", prediction and major factors that affect downscaling ability, 2014, pp.147-148, 68~85
- 김용상, "기상연구소의 국지규모 기상 분석 및 예측 시스템(KLAPS)의 실시간 운영", 한국기상학회지, 38(1), pp.1~10 (2002), 한국기상학회
- A description of the advanced research WRF version 3, "Skamarock, W. C.", National Center for Atmospheric Research, 125~, pp.NCAR Tech. Note NCAR (2008), TN-475+STR
- Mellor, G.L., "A hierarchy of turbulence closure models for planetary boundary layers", J. Atmos. Sci., 31, pp.1791~1806 (1974)
- Smirnova, T. G., "Parameterization of cold-season proce", sses in the MAPS land-surface scheme, 2000, pp.105(D3), 4077~4086
- Lim, K.-S., "Development of effective double-moment cloud microphysics scheme with prognostic cloud condensation nuclei (CCN) for weather and climate models", Mon. Wea. Rev., 138, pp.1578~1612 (2010)
- Avissar, R., "A parameterization of heterogeneous land surfaces for atmospheric numerical models and its impact on regional meteorology", Mon. Wea. Rev., 117, pp.2113~2136 (1989)
- Chen, F., "Coupling an advanced land surface-hydrology model with Penn State – NCAR MM5 modeling system. Part I: Model Implementation and Sensitivity", Mon. Wea. Rev., 129, pp.569~585 (2001)
- Oh, K. -Y., "Wind resource assessment around Korean Peninsula for feasibility study on 100MW class offshore wind farm", Renew. Energy, 42, pp.217~226 (2012)
- Lee, M. E., "Assessment of offshore wind energy at Younggwang in Korea", Renew, and Sustainable Energy Rev., 21, pp.131~141 (2013)
- 이기남, "HeMOSU-1호 관측풍속의 불확실성을 고려한 서남해안의 풍력 발전량 예측", 신재생에너지, 10(2), pp.19~28 (2014), 한국신·재생에너지학회
- Kotroni, V., "High-resolution model-based wind atlas for Greece", Renew. and Sustainable Energy Rev., 33, pp.479~489 (2014)
- Carvalho, D., "WRF wind simulation and wind energy production estimated forced by different reanalyses:Comparison with observed data for Portugal", Appl. Energy, 117, pp.116~126 (2014)
- Gualtieri, G., "Atmospheric stability varying wind shear coefficients to improve wind resource extrapolation:A temporal analysis", Renew. Energy, 87, pp.376~390 (2016)
- Cristina L. Archer, "Evaluation of global wind power", Journal of Geophysical Research, 110(D12) (2005), American Geophysical Union (AGU)[DOI]