| 논문명 |
기존 건축물을 위한 건물 에너지 프로파일링 시스템 개발 / Development of a Profiling System for Energy Performance Assessment of Existing Buildings |
| 저자명 |
안기언 ; 김영민 ; 김용세 ; 윤성환 ; 신한솔 ; 박철수 |
| 수록사항 |
대한건축학회논문집 구조계, Vol.32 No.12 (2016-12) |
| 주제어 |
건물 에너지 성능평가 ; 프로파일링 시스템 ; 인공신경망 ; 에너지플러스 ; Building Energy Performance Assessment ; Profiling System ; Artificial Neural Network ; EnergyPlus |
| 요약2 |
The building sector contributes to about 40% of total energy consumption in South Korea. In particular, existing buildings older than 15 years account for 75% of the energy consumption by the entire building sector in South Korea. When assessing energy performance of existing buildings by the use of dynamic simulation tools, there are a variety of barriers, e.g. cost, time, expertise, lack of building information, etc. In this study, the authors developed a building energy profiling system that provides quick and easy energy performance assessment of existing buildings. The building energy profiling system is based on a number of EnergyPlus simulation runs and Artificial Neural Network models. For the ANN models, a series of EnergyPlus pre-simulations were sampled by a Monte Carlo technique. Though the profiling system requires minimalistic inputs, it can provide information on (1) energy performance level of a given building, (2) energy benchmarking against peer buildings, and (3) quantification of energy conservation measures. |
