應用建築能源分析軟體模擬不同參數下 室溫以協助能源使用與節能分析;Room Temperature Prediction Using Data Generated by Building Performance Analysis Software for Efficient Energy Use and Conservation

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题名:	應用建築能源分析軟體模擬不同參數下室溫以協助能源使用與節能分析;Room Temperature Prediction Using Data Generated by Building Performance Analysis Software for Efficient Energy Use and Conservation
作者:	李富傑;Lee,Fu-Jie
贡献者:	土木工程學系
关键词:	建築資訊模型;建築節能;室溫預測;Building information modeling;Building energy usage and conservation;Room temperature prediction
日期:	2015-07-17
上传时间:	2015-09-23 10:05:16 (UTC+8)
出版者:	國立中央大學
摘要:	資訊科技與建築工程結合，改變了僅有圖面資料的電腦輔助設計(Computer-Aided Design, CAD)技術，結合了工程圖說與建築過程資料於一個建築模型內，並有進階三維幾何功能與視覺化能力，此新技術稱為建築資訊模型(Building Information Modeling, BIM)。然而永續綠建築中提倡建築生命週期之概念，但是建築物節能這部份的課題卻是存在的，建築物應需避免錯誤的使用方式或建造方式而造成能源消耗之負擔，所以建築物的規劃與設計階段需考量建造當地的氣候環境。並列入設計中的一部份考量其適用性及外部環境之影響性，讓建築物延長生命週期並達到節能減碳之目的。本研究利用建築熱環境模擬Ecotect進行地區之熱模擬分析，並載入相對應之影響條件求得建物溫度。此行為可以幫使用者調整出適合方位及位置之比較方案，以符合生態永續建築規劃設計的要求。限於版權或詴用版之因素，本研究測詴Autodesk-Revit、Autodesk-Ecotect與Microsoft EXCEL VBA來執行，並從文獻分析出七項重要外部與內部參數最主要影響室溫來進行進一步分析。首先透過Ecotect以敏感度分析的方式產生各參數變動下室溫，接著以簡單外推法或內插法的方式讓使用者指定參數，最後以VBA程式推估室溫。;Energy usage pertaining to air conditioning is a critical factor in designing energy conservation policies. In addition to the performance of an air conditioning system, it is well recognized that the temperature inside a room without the air conditioning system can be used to estimate how much energy is required to maintain a comfortable indoor environment. Currently, several building performance analysis software packages such as Ecotect can provide designer with satisfactory building performance simulations, including room temperature, under various conditions. Hence, this research aims at using Ecotect to generate enough data sets for prediction of room temperature. Seven factors have been identified from the literature as the input parameters for this prediction, including, day of the year, time of the day, site location, site orientation, room size, room level, and nearby buildings. A simple model was proposed to utilize such data sets to build a linear relationship between variables. 50 testing cases, with the randomized input parameters, were entered into Ecotect to obtain the base prediction results and were compared with the results from using the proposed approach. Less than 5% difference was observed, which means the proposed approach may help designers quickly estimate room temperature for energy usage and conservation analysis.
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