| Title |
Real-time Energy Demand Prediction Method Using Weather Forecasting Data and Solar Model |
| Authors |
곽영훈(Young-Hoon Kwak) ; 천세환(Se-Hwan Cheon) ; 장철용(Cheol-Yong Jang) ; 허정호(Jung-Ho Huh) |
| DOI |
http://dx.doi.org/10.6110/KJACR.2013.25.6.310 |
| Keywords |
실시간 에너지 수요예측 ; 기상 예보 데이터 ; 일사 모델 ; BCVTB ; 에너지플러스 Real-time Energy Demand Prediction ; Weather Forecasting Data ; Solar Model ; BCVTB ; EnergyPlus |
| 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. |