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Prediction Study of Solar Modules Considering the Shadow Effect

그림자 효과를 고려한 태양전지 모듈의 발전량 예측 연구

  • Kim, Minsu (School of Chemical Engineering, Yeungnam University) ;
  • Ji, Sangmin (School of Chemical Engineering, Yeungnam University) ;
  • Oh, Soo Young (School of Chemical Engineering, Yeungnam University) ;
  • Jung, Jae Hak (School of Chemical Engineering, Yeungnam University)
  • 김민수 (화학공학부, 영남대학교) ;
  • 지상민 (화학공학부, 영남대학교) ;
  • 오수영 (화학공학부, 영남대학교) ;
  • 정재학 (화학공학부, 영남대학교)
  • Received : 2016.06.02
  • Accepted : 2016.06.07
  • Published : 2016.06.30

Abstract

Since the last five years it has become a lot of solar power plants installed. However, by installing the large-scale solar power station it is not easy to predict the actual generation years. Because there are a variety of factors, such as changes daily solar radiation, temperature and humidity. If the power output can be measured accurately it predicts profits also we can measure efficiency for solar power plants precisely. Therefore, Prediction of power generation is forecast to be a useful research field. In this study, out discovering the factors that can improve the accuracy of the prediction of the photovoltaic power generation presents the means to apply them to the power generation amount prediction.

Keywords

References

  1. U. S. Department of Energy, "2010 Solar Technologies Market Report", November 2011.
  2. Mark Mikofski, Mike Anderson, Sander Caldwell, Dave DeGraaff, Ernest Hasselbrink, David Kavulak, Ryan Lacerda, David Okawa, Yu-Chen Shen, Arya Tediasaputra, Akira Terao, Zhiogang Xie, 26th European photovoltaic soar energy conference and exhibition, 105-112, 2011.
  3. Min Su Kim, "Optimal design for Silicon based Photovoltaic system",Master's thesis,2006.
  4. Sangmin Ji,"Development of solar power generation prediction simulator for solar power plant optimal design", Master's thesis, 2016.