고해상도 일사량 관측 자료를 이용한 UM-LDAPS 예보 모형 성능평가
Evaluation of UM-LDAPS Prediction Model for Solar Irradiance by using Ground Observation at Fine Temporal Resolution
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참고문헌
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초록
Day ahead forecast is necessary for the electricity market to stabilize the electricity penetration. Numerical weather prediction is usually employed to produce the solar irradiance as well as electric power forecast for longer than 12 hours forecast horizon. Korea Meteorological Administration operates the UM-LDAPS model to produce the 36 hours forecast of hourly total irradiance 4 times a day. This study interpolates the hourly total irradiance into 15 minute instantaneous irradiance and then compare them with observed solar irradiance at four ground stations at 1 minute resolution. Numerical weather prediction model employed here was produced at 00 UTC or 18 UTC from January to December, 2018. To compare the statistical model for the forecast horizon less than 3 hours, smart persistent model is used as a reference model. Relative root mean square error of 15 minute instantaneous irradiance are averaged over all ground stations as being 18.4% and 19.6% initialized at 18 and 00 UTC, respectively. Numerical weather prediction is better than smart persistent model at 1 hour after simulation began.
Abstract
Day ahead forecast is necessary for the electricity market to stabilize the electricity penetration. Numerical weather prediction is usually employed to produce the solar irradiance as well as electric power forecast for longer than 12 hours forecast horizon. Korea Meteorological Administration operates the UM-LDAPS model to produce the 36 hours forecast of hourly total irradiance 4 times a day. This study interpolates the hourly total irradiance into 15 minute instantaneous irradiance and then compare them with observed solar irradiance at four ground stations at 1 minute resolution. Numerical weather prediction model employed here was produced at 00 UTC or 18 UTC from January to December, 2018. To compare the statistical model for the forecast horizon less than 3 hours, smart persistent model is used as a reference model. Relative root mean square error of 15 minute instantaneous irradiance are averaged over all ground stations as being 18.4% and 19.6% initialized at 18 and 00 UTC, respectively. Numerical weather prediction is better than smart persistent model at 1 hour after simulation began.
참고문헌 (7)
- Kleissl, J., "Solar Energy Forecasting and Resource Assessment", pp.416~, Academic Press
- Diagne, M., "Review of Solar Irradiance Forecasting Methods and a Proposition for Small-scale Insular Grids", Renewable and Sustainable Energy Reviews, 27, pp.65~76 (2013)
- 이영미, "제주 실시간 일사량의 기계학습 예측 기법 연구", 한국환경과학회지, 26(4), pp.521~527 (2017), 한국환경과학회[DOI]
- 김창기, "태양광 발전 예보를 위한 UM-LDAPS 예보 모형 성능평가", 한국태양에너지학회 논문집, 39(2), pp.71~80 (2019), 한국태양에너지학회[DOI]
- Evaluation of Numerical Weather Prediction System (2016), "Korea Meteorological Administration", 198~, pp.TR11-1360709-000001-10 (2016)
- Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications, "Sengupta, M.", National Renewable Energy Laboratory, ~, pp.NREL (2017), TP-5D00-68886
- Mathiesen, P., "Evaluation of Numerical Weather Prediction for Intra-day Solar Forecasting in the Continental United States", Solar Energy, 85, pp.967~977 (2011)