Korean Journal of Air-Conditioning and Refrigeration Engineering (설비공학논문집)

The Society of Air-Conditioning and Refrigerating Engineers of Korea (대한설비공학회)
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Real-time Energy Demand Prediction Method Using Weather Forecasting Data and Solar Model

기상 예보 데이터와 일사 예측 모델식을 활용한 실시간 에너지 수요예측

  • Kwak, Young-Hoon (Department of Architectural Engineering, University of Seoul) ;
  • Cheon, Se-Hwan (Department of Architectural Engineering, University of Seoul) ;
  • Jang, Cheol-Yong (Green Building Research Center, Korea Institute of Energy Research) ;
  • Huh, Jung-Ho (Department of Architectural Engineering, University of Seoul)
  • 곽영훈 (서울시립대학교 건축공학과) ;
  • 천세환 (서울시립대학교 건축공학과) ;
  • 장철용 (한국에너지기술연구원 녹색건축센터) ;
  • 허정호 (서울시립대학교 건축공학과)
  • Received : 2012.12.18
  • Published : 2013.06.10
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Abstract

This study was designed to investigate a method for short-term, real-time energy demand prediction, to cope with changing loads for the effective operation and management of buildings. Through a case study, a novel methodology for real-time energy demand prediction with the use of weather forecasting data was suggested. To perform the input and output operations of weather data, and to calculate solar radiation and EnergyPlus, the BCVTB (Building Control Virtual Test Bed) was designed. Through the BCVTB, energy demand prediction for the next 24 hours was carried out, based on 4 real-time weather data and 2 solar radiation calculations. The weather parameters used in a model equation to calculate solar radiation were sourced from the weather data of the KMA (Korea Meteorological Administration). Depending on the local weather forecast data, the results showed their corresponding predicted values. Thus, this methodology was successfully applicable to anywhere that local weather forecast data is available.

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References

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