신재생 에너지 기술: 태양광 기술과 기후예측 기술과의 융합

  • 유성현 (고려대학교 전기전자공학부) ;
  • 안춘기 (고려대학교 전기전자공학부)
  • Published : 2018.02.01

Abstract

Keywords

References

  1. http://times.kaist.ac.kr/news/articleView.html?idxno=101
  2. 나무위키
  3. 한국수출입은행 2016년 세계 신재생에너지 산업 전망 및 이슈
  4. 한국에너지 관리공단
  5. SK 에너지 블로그
  6. New Energy Finance
  7. http://www.industrynews.co.kr/news/articleView.html?idxno=9008
  8. 국가환경산업기술정보시스템 (KONETIC)
  9. E. B. Ssekulima, M. B. Anwar, A. A. Hinai, and M. S. E. Moursi, "Wind speed and solar irradiance forecasting techniques for enhanced renewable energy integration with the grid: a review", IET Renewable Power Generation, Vol 10, No 7, 885 - 989, 2016 https://doi.org/10.1049/iet-rpg.2015.0477
  10. M. Wittmann, H, Breitkreuz, M, Schroedter-Homscheidt, and M. Eck, "Case Studies on the Use of Solar Irradiance Forecast for Optimized Operation Strategies of Solar Thermal Power Plants", IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 1, No 1, 18 - 27, 2008 https://doi.org/10.1109/JSTARS.2008.2001152
  11. W. Traunmuller and G. Steinmaurer, "Solar irradiance forecasting, benchmarking ofdifferent techniques and applications of energy meteorology". Proc. EuroSun 2010 Conf., 2010
  12. P. Bacher, H. Madsen, H. A. Nielsen, "Online short-term solar power forecasting", Sol. Energy, 83, (10), pp. 1772-1783, 2009 https://doi.org/10.1016/j.solener.2009.05.016
  13. https://medium.com/@xenonstack/overview-of-artificial-neural-networks-and-its-applications-2525c1addff7
  14. https://www.tutorialspoint.com/artificial_intelligence/artificial_intelligence_fuzzy_logic_systems.htm
  15. http://www.mdpi.com/2078-2489/6/3/300