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研究生: 蘇于翔
Yu-Xiang Su
論文名稱: 預測能源轉型趨勢下電動車在建築能耗比例: 以台北市為例
Forecast Energy Transition Ratio of Electric Vehicle at Building Energy Consumption:A Case of Taipei City
指導教授: 周建成
Chien-Cheng Chou
口試委員:
學位類別: 碩士
Master
系所名稱: 工學院 - 土木工程學系
Department of Civil Engineering
論文出版年: 2022
畢業學年度: 110
語文別: 中文
論文頁數: 115
中文關鍵詞: 電動車深度學習EUI建築資訊模型淨零碳排
外文關鍵詞: Electric vehicle, Deep learning, EUI, BIM, Net-Zero Carbon
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  • 在2050年的淨零碳排政策,從全球的觀點探討碳排放量(Carbon Footprint),人們主要以建築物為居住場所,根據國際能源總署( International Energy Agency, IEA ),提及在碳排部分建築部門占40 %、交通運輸部門占23% ,其餘的碳排產生由工業部門及製造部門等。
    若電動車的趨勢不斷成長,每棟建築物在未來都將承擔充電樁所產生的電能,而燃油車會逐漸減少,即可以預測交通運輸部門的碳排會大幅度的減少,在國內公路運輸使用能耗高達96.8 %,其中小客車使用能耗約52.18 %,大貨車約16.62 %。換句話說,若未來每棟建築物都設立電動車的充電樁,使用能源的比例與交通及建築都保持不變的狀態,則我國會有將近50 %的能源使用在建築場域中,但根據各國所規定的新建建築需達到建築淨零耗能標準,此現象不但使城市的能源面臨巨大的挑戰也增加了淨零碳排的困難度。
    本論文以台北市為例在老屋修繕、改建、及新建築設計階段以Revit Insight 基於BIM與BEM之間以EUI評估建築耗能並經過調整達到最佳效果且以深度學習預測未來電動車成長,從大格局的城市等級評析建築物的耗能或電力運輸的影響,隨著淨零碳排趨勢與進步,希望能夠藉此分析以提升人類的生活品質且達到永續節能的效果。


    According to the Net-Zero Carbon Emissions by 2050, from the global aspect of carbon footprint, the main use of construction is for residence. The International Energy Agency indicates that Construction section produces 40% ,Transportation section produces 23% ,Industry and Production section produce the rest of the carbon footprint.
    With the development of electric vehicles, fossil fuel vehicles will eventually be replaced. It can be predicted that the carbon footprint from Transportation section will substantially decrease. Thus, Construction section will cover most of the energy consumption it. Domestic highway accounts for 96.8%, passenger car accounts for 52.18% and truck accounts for 16.62 percent of the energy consumption. In other words, if there are charging piles in every single building and the percentage of energy consumption from transportation and construction keep the same, almost 50% of the energy consumption in our country will be from Construction section. However, since many countries have regulated policy of Zero-energy buildings, cities are facing significant challenges of energy consumption and it increases the difficulties of zero carbon footprint.
    This theses is using Taipei City as an example of predicting future growth of electric vehicles, the design, repair and renewal of construction. Using city-level energy consumption of construction and electrical transportation to evaluate, with the foundation of BIM and BEM such as Revit Insight, The method must be further verified and analyzed. With the progression of Zero Carbon Footprint, we hope that we can improve human beings’ living conditions to reach energy sustainability.

    目 錄 摘要 i Abstract ii 誌 謝 iv 目 錄 v 圖目錄 viii 表目錄 x 第一章 緒論 1 1-1 研究背景與動機 1 1-2 研究問題與目的 3 1-3 研究範圍與限制 4 1-4 研究流程 5 1-5 論文架構 7 第二章 文獻回顧 8 2-1 全球能源分析及我國能源轉型目標與願景 8 2-1-1 燃油車相關法規 11 2-1-2 國內加油站市場競爭與現況 12 2-1-3 國內加油站產業面臨的挑戰 13 2-2 電動車相關介紹種類 14 2-2-1 電動車的興起及充電設施的建置 15 2-2-2 電動車製造商 16 2-2-3 先進國家電動車成長與政策 18 2-3 人工智慧之相關文獻 20 2-3-1 機器學習 20 2-3-2 深度學習 21 2-4 建築能耗模型與建築資訊模型相關文獻 23 2-4-1 Building Information Modeling 24 2-4-2 Building Energy Modeling 26 2-4-3 Energy plus 28 2-4-4 Energy Use Intensity 31 2-4-5 Autodesk Insight 33 2-5 文獻回顧總結 35 第三章 電動車轉換效率與成長量預測 36 3-1 能量轉換效率 36 3-1-1 燃油車推估 40 3-1-2 電動車推估 44 3-2 全球電動車預測成長量 47 3-2-1 台灣電動車與能源轉型成長預估 51 3-2-2 台北市能源轉型先行城市之電動車成長預估 52 3-2-3 電動車成長對城市各項能源基礎設施造成的影響 54 第四章 Revit建築能源評析 55 4-1 Revit能源分析設定 55 4-1-1 模型前置設定 56 4-1-2 模型能源分析設置 58 4-1-3 Insight 分析及視覺化 62 4-2 先行城市實際操作 67 4-2-1 住戶用電分析 69 4-2-2 住戶含公設用電分析 77 4-2-3 建築物與電動樁結果分析 80 第五章 結論與建議 81 5-1 結論 81 5-2 建議 82 5-3 貢獻 82 參考文獻 83 附錄 A 93 評審意見回覆表 99

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