- 會議論文
應用BEMS、TMY3與氣候資料庫預測建築熱負荷-以臺灣大學人工氣候室為例
Applications BEMS,TMY3 and Climate datebase to predict the Air- Conditioning heat load - A Case Study of National Taiwan University phytotron
摘要
人工氣候室為生技產業重要之研究建築設施，因其建築型態在國際間相當稀少，相關建築資訊具有研究的價值；本研究應用營運中的臺大人工氣候室冰水主機2012-2014年空調熱負荷之觀測與分析，試圖建立植物工廠空調電力能耗更簡易的預測方法。以臺灣大學人工氣候室的BEMS數據，與政府公開氣候資料庫接近68萬筆的資料，共同進行統計學的迴歸分析，先建立人工氣候室熱負荷迴歸預測模型；進一步推導出人工氣候室實務上用以估計電力能耗的最大空調負荷需量方程式，以3組連續方程式建置植物工廠建築空調能耗的完整預測系統，最終應用在人工氣候室的年度電力能源規劃報告。本研究的數據為人工氣候室內建的BEMS（建築能源管理）系統海量資料庫中加以解析與探勘而成，此研究方式適合計算建築能源時實務的運用，利用大樓的BEMS資訊，建立各類型大樓的建築熱負荷模型，可由本研究實驗數據之迴歸模型中發現新的耗能參數、研究方向與趨勢，更冀望BEMS海量資訊可導出與BIM系統中AutodeskRevit等綠能電腦模擬軟體，進行更精確的物業能源規劃與管制。
並列摘要
The study is proposing a simplified methodology to predict the electricity consumption for the air conditioning in a plant factory using the air conditioning heat load records, from the 2012 to 2014, of the chiller group at the Phytotron of National Taiwan University. The predictive modelling for Phytotron air conditioning heat load was developed based on the regression analysis of the Phytotron's BEMS data and the 677,880 records from government's open climate database. Three equations were derived to estimate the demand of the electricity consumption for the maximum air conditioning load. The study adopted the three equations to build a comprehensive system that can predict the maximum electricity consumption of the plant factory building, which was applied to the annual planning of the electricity demand for the Phytotron. The massive real time data which collected from the NTU Phytotron's BEMS (Building Energy Management) system was mine and analyzed to accomplish the heat load model in order to apply for property management on plant factory. This research not only approach to heat load model creation by using BEMS but also towards the parameters in building energy consumption. In the further research, the model can be applied to BIM Autodesk Revit simulation which facilitates precise control of the property and energy planning.
延伸閱讀
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