臺灣博碩士論文加值系統

本研究以一般住宅建築為實驗對象，住宅內設置一暖通空調，設計控制器以控制暖通空調，使得房屋在室外環境溫度的影響下維持穩定的室內溫度，同時透過模擬其耗費之能量換算成耗電成本，結合建築資訊模型之技術，將建築地理位置設定於淡水，並匯入真實氣溫資訊，使模擬更貼近真實情境，進一步調整建築規格，觀察屋內暖通空調之能耗變化。
研究中之住宅建築模擬與暖通空調控制器皆於MATLAB/Simulink上進行，透過窗戶及牆壁面積推算出建築模型之等效熱阻，暖通空調則是透過計算其製造之熱流及通過之氣流率來進行模擬，最後將屋內空氣質量結合等效熱阻得出建築熱量散失之數學式，本研究將上述數學式作為架構完成建築模型，並於Revit平台為此建築建立3D模型，結合建築資訊模型之技術，並使用Insight分析其能源模型，獲得多種節能窗玻選擇與窗牆比，調整建築規格，使其成為最佳節能之配置，並比較模型在不同窗牆比與窗玻材質下之耗電成本的變化，計算其節能貢獻度，最後加入玻璃成本以計算每種窗玻配置之性價比，比較住宅建築模型於各窗牆比下最合適之配置，並且能在建築之節能能力與使用者之支出成本間達到平衡，同時改善住宅建築的能源使用效率。

In this study, a general residential building is used as an experimental object. A HVAC system is installed in the house, and a controller is designed to control the HVAC, so that the house maintains a stable indoor temperature under the influence of the outdoor environmental temperature, and at the same time simulates the energy consumption, converted into the cost of electricity consumption, combined with the technology of Building Information Modeling, sets the geographic location of the building to Tamsui and imports real temperature data to make the simulation closer to the real situation, further adjust the building specifications, and observe the energy consumption cost of HVAC in the house.
The residential building simulation and HVAC system in the research are carried out on MATLAB/Simulink, and a 3D model for the building is built on the Revit platform, combined with the technology of Building Information Modeling, and Insight is used to analyze its energy model to obtain a variety of energy-saving windows and window-to-wall ratios, adjust building specifications to make it the best energy-saving configuration, and compare the model''s energy consumption cost under different window-to-wall ratios and window glass materials to calculate its energy-saving contribution. Finally, add the glass cost to calculate the cost-performance ratio of each window glass configuration, compare the most suitable configuration of the residential building model under each window-to-wall ratio, and achieve a balance between the energy saving capacity of the building and the user''s expenditure cost, while improving the residential building energy efficiency.

Contents
Acknowledgement I
Abstract in Chinese II
Abstract in English III
Contents IV
List of Figures VI
List of Tables VIII
1 Introduction 1
1.1 Research Background 1
1.1.1 Global Warming & Energy Saving 1
1.1.2 HVAC 3
1.1.3 BIM & Revit 5
1.2 Motivation 7
1.3 Literature Review 9
1.4 Thesis Organization 11
2 Problem Statement 13
3 Methodology 18
3.1 Thermal Model & House Structure 20
3.2 Operating Environment 22
3.3 First Result & Energy Model in Revit 23
3.4 Window Glass Types and Prices & Window­to­Wall Setting 26
4 Numerical Experiment 29
4.1 Mathematical Models in MATLAB/Simulink 29
4.2 Results 32
5 Conclusions and Future Work 48
References 50

List of Figures
Figure 1.1 Global Warming 2
Figure 1.2 HVAC system 4
Figure 1.3 BIM 5
Figure 1.4 Revit 6
Figure 2.1 Energy Consumption Decomposition Analysis Structure for Residential Sector 14
Figure 2.2 Taiwan’s Power Consumption in 2015 15
Figure 2.3 Research Framework 17
Figure 3.1 Research Process Flow Chart 19
Figure 3.2 House Thermal Model 20
Figure 3.3 House Model Structure 21
Figure 3.4 Simulation Result 24
Figure 3.5 Waveform Details 25
Figure 3.6 House Model in Revit 25
Figure 3.7 Wall Appearance with 4 Window­to­wall Ratios 28
Figure 4.1 Glass A at WWR=0.01 33
Figure 4.2 Glass A at WWR=0.02 33
Figure 4.3 Glass A at WWR=0.04 34
Figure 4.4 Glass A at WWR=0.08 34
Figure 4.5 Glass B at WWR=0.01 35
Figure 4.6 Glass B at WWR=0.02 35
Figure 4.7 Glass B at WWR=0.04 36
Figure 4.8 Glass B at WWR=0.08 36
Figure 4.9 Glass C at WWR=0.01 37
Figure 4.10 Glass C at WWR=0.02 37
Figure 4.11 Glass C at WWR=0.04 38
Figure 4.12 Glass C at WWR=0.08 38
Figure 4.13 Glass D at WWR=0.01 39
Figure 4.14 Glass D at WWR=0.02 39
Figure 4.15 Glass D at WWR=0.04 40
Figure 4.16 Glass D at WWR=0.08 40
Figure 4.17 Glass E at WWR=0.01 41
Figure 4.18 Glass E at WWR=0.02 41
Figure 4.19 Glass E at WWR=0.04 42
Figure 4.20 Glass E at WWR=0.08 42
Figure 4.21 Simulation Result of Heating Cost 43
Figure 4.22 Cost–performance Ratio at WWR=0.01 44
Figure 4.23 Cost–performance Ratio at WWR=0.02 45
Figure 4.24 Cost–performance Ratio at WWR=0.04 46
Figure 4.25 Cost–performance Ratio at WWR=0.08 47

List of Tables
Table 1.1 Overall Results CCPI 2020 8
Table 3.1 Wall Structure 22
Table 3.2 Operating Environment 23
Table 3.3 Window Glass Types 27
Table 4.1 WWR=0.01 44
Table 4.2 WWR=0.02 45
Table 4.3 WWR=0.04 46
Table 4.4 WWR=0.08 47

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