| 논문명 | Python을 이용한 냉동기 에너지소비량 예측 모델의 성능 개선 및 비교 평가/Performance Improvement and Comparative Evaluation of the Chiller Energy Consumption Forecasting Model Using Python |
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| 저자명 | 이철원(Lee, Cheol-Won) ; 성남철(Seong, Nam-Chul) ; 최원창(Choi, Won-Chang) |
| 발행사 | 한국건축친환경설비학회 |
| 수록사항 | 한국건축친환경설비학회 논문집 , Vol.15 No.3 |
| 페이지 | 시작페이지(252) 총페이지(13) |
| ISSN | 1976-6483 |
| 주제분류 | 환경및설비 |
| 주제어 | 파이썬; 랜덤포레스트; 인공신경망; 예측 모델; 냉동기 에너지소비량 Python; Random Forest; Artificial Neural Network; Forecasting Model; Chiller Energy Consumption |
| 요약2 | In this study, a drain back system to prevent summer season overheating and winter season freezing of facade installed solar hot water system for school building was suggested and evaluated by long-term experiments. The drain back system proposed in this study was configured as a system with a control valve to modulate the amount of drained water when drain-back is called. The controller of the drain-back system allows the user to set the set point temperature and control whether to remain or discharge the working fluid inside the piping of the solar hot water system. In addition, the piping system was constructed so that a part of the working fluid pump power recovered by installing a micro hydro turbine with a capacity of 10 W at the end of the return pipe of the solar hot water system. In order to experimentally evaluate the reliability and usefulness of the drain back system to prevent overheating and freezing, long-term demonstration experiments were carried out to use tap water that is vulnerable to freezing and overheating as a working fluid. As a result of long-term experiments, the temperature inside the heat storage tank could be kept below the setting temperature of 68℃ in the summer season. Also, the freezing problem of the solar hot water system did not occur at all even when the outside temperature was continuously below -10℃ in the winter season. |
| 소장처 | 한국건축친환경설비학회 |