臺灣博碩士論文加值系統

根據聯合國環境規劃署(United Nations Environment Programme)於2011年指出，全球有50%人口居住於城市，且城市使用之能源高達世界總能源消耗的60-80%，其中國際能源署(International Energy Agency)表示建築平均佔全球能源消耗32%。而我國經濟部能源局於2012年報告亦顯示住商部門的電力消耗量高達37.42%，建築物之能源使用效率評估與優化(optimization)已成為全球共同關注之能源策略研究議題。
經由文獻回顧之探討發現，空調與照明等日常使用占了整體建築能耗近50~80%，且建築的外殼、建材種類、窗戶種類、開窗率與遮陰設施等設計都與建築物能源效率有密切的影響。因此如何將此龐雜的建築設計進行優化，以達成高效率的節能效果，是相當值得探討的議題。
故本研究利用遺傳規劃法(Genetic Programming)結合能源模擬模式EnergyPlus求解建築節能設計之優化問題，並以位於台灣南部之辦公大樓的能源使用作為研究案例。研究結果顯示，優化後之參數設計可降低案例建築總能源達26.87%，並在各項能源使用上分別降低冷氣需求44.65%、風扇需求46.02%、照明需求16.23%及暖氣需求3.29%。

According to UNEP’s (United Nations Environment Programme) statement in 2011, 50% of the total population on earth lives in cities and consumed 60-80% of the total energy in the world. The IEA (International Energy Agency) also mentioned that the energy used by buildings make up 32% of the global energy consumption. On the other hand, the report of Bureau of Energy also indicates that Taiwan electricity consumption in residential and commercial sector was up to 37.42% in 2012. Therefore, evaluation and optimization of the building energy efficiency have become an important issue of global energy strategy research.
Literature review indicates that the energy use of air conditioning and lighting on general building accounts for nearly 50% to 80% of the total energy consumption. Moreover, energy efficiency of building are also affected by the design of the building shells, building types, window types, shading rates, etc.. Therefore, developing optimization tools to improve the energy efficiency of buildings it is a very valuable topic to work on.
This study employed genetic programming, integrated with the energy simulator EnergyPlus, to optimize efficient energy designs of building. An office building in southern Taiwan is used as case study. The results showed that the optimized building design can reduce 26.87% of total energy consumption, including 44.65% energy reduction of air conditioning system, 46.02% reduction of electric fan, 16.32% reduction of lighting system, and 3.29% of heating system.

摘要 ii
Abstract iii
目錄 iv
圖目錄 vii
表目錄 ix
第一章 前言 1
1.1 研究背景 1
1.2 研究動機與目的 4
1.3 研究流程與架構 8
第二章 文獻回顧 10
2.1 建築節能潛力評估 10
2.2 節能設計策略相關研究 12
2.2.1 建築外殼節能評估 12
2.2.2 空調系統 17
2.2.3 照明系統 21
2.3 建築節能優化相關研究 24
2.4 文獻小結 28
第三章 研究方法 29
3.1 EnergyPlus建築全能耗模擬模式 29
3.1.1 EnergyPlus之模擬架構 30
3.1.2 EnergyPlus資料輸入與輸出 34
3.2 遺傳規劃法 36
3.2.1 遺傳規劃法之結構與特性 39
3.2.2 遺傳規劃法之交配(Crossover)機制 41
3.2.3 遺傳規劃法之突變(Mutation)機制 42
3.2.4 遺傳規劃法設計參數配置 43
3.3 研究案例 44
3.3.1 研究案例基本資料 44
3.3.2 氣象資料輸入 45
3.3.3 建築配置與參數設定 46
3.3.4 案例外殼建材設置 47
3.3.5 空調系統與設備 48
3.4 優選模式設計 49
3.4.1 GenOpt通用優選模式 49
3.4.2 本案例設計之優化模式 50
3.4.3 建築外牆與屋頂優化設置 52
3.4.4 建築外觀窗戶與種類優化設置 53
3.4.5 照明控制系統優化設置 56
第四章 結果與討論 57
4.1 原始案例能耗與優化結果 57
4.1.1 原始案例建築能耗結果 57
4.1.2 建築能耗整合優化模擬結果 58
4.2 各項優化表現與分析 61
4.2.1 外牆增設隔熱層之優化 61
4.2.2 屋頂增設隔熱層之優化 64
4.2.3 各向窗戶寬度之優化 68
4.2.4 窗戶種類之優化 74
4.2.5 照明系統 78
4.2.6 各項優化與整合優化之能耗結果 80
第五章 結論與建議 83
5.1 研究結論 83
5.2 研究建議 84
參考文獻 85

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