| 학회 |
한국화학공학회 |
| 학술대회 |
2019년 봄 (04/24 ~ 04/26, 제주국제컨벤션센터) |
| 권호 |
25권 1호, p.198 |
| 발표분야 |
공정시스템(Process Systems Engineering) |
| 제목 |
기후변화적응을 위한 빅데이타분석기반 호텔에너지 사용량 예측 (클러스터링과 회기분석) |
| 초록 |
The hotel buildings are categorized as the highest energy consumption and considerably contributes to GHG emissions to our atmosphere, which have had a significant impact on global climate change. Thus, this paper aims to estimate the energy use intensity (EUI) of hotel buildings using MLR models. Large dataset of building, energy usage and energy consumption had been collected from 32 different hotels by survey. The survey data includes: heating, ventilation, and air-conditioning, lighting, plug equipment, lift, location, and floor area, which can be considered relatively big data. The KNN algorithm is used to cluster the hotels according to the EUI results. Finally, a three-cluster management strategy accompanied by smart monitoring to reduce CO2 using EUI was suggested to meet local emission goals. Some suggestions are put forward to improve energy performance of hotels and their environmental impact to adapt climate change. This work was supported by Korea Ministry of Environment (MOE) as Graduate School specialized in Climate Change. |
| 저자 |
Hoang TuanViet1, Joseph J. Deringer2, Usman Safder1, 남기전1, Tran NgocQuang3, Van-Dat Mac3, 유창규1
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| 소속 |
1경희대, 2American Institute of Architects, 3National Univ. of Civil Engineering |
| 키워드 |
공정모델링; 공정모사; 이상진단
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| E-Mail |
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| 원문파일 |
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