辦公建築日常使用階段碳排評價系統之研究

Research on the carbon emission benchmarking system of office building during usage phase

陳世禎(Shih-Chen Chen)

指導教授 ： 黃國倉

國立臺灣大學/生物資源暨農學院/生物環境系統工程學研究所/碩士(2019年)

https://doi.org/10.6342/NTU201903162

摘要

辦公建築之生命週期中，有超過80%的耗能集中於日常使用之階段，為建築生命週期中碳排放佔比最大的階段。本研究期望建立一建築碳排評價之系統，期望建立一計算流程來評估其日常使用階段之碳排量。本研究主要分成兩個部分:(1)辦公建築之全年耗能推估、(2)建築碳排評價系統之建置。
在辦公建築全年耗能推估中，本研究收集台灣建築之組成因子，並利用這些因子結合建立之耗能計算流程，來推估建築全年耗能量，耗能項目包含空調、換氣設備、照明、電梯設備、辦公事務機器等六項，將統合這些項目個別之耗能量總和，以作為評判建築耗能表現之指標。另外，為了使用者方便評估使用，在空調耗能之推估上，利用類神經網路預測模型，結合空調耗能與建築組成因子，提供使用者預測其全年建築空調耗能。
建築碳排評價系統之建置上，利用建立建築基線模型之概念，來評估建築碳排之表現。本研究利用建築組成因子與台灣之法規，建立欲評估建築之對照基線案例，並根據設計案例與基線案例之比值(設計與基線碳排比)來做為碳排評比之依據，建立一評分查詢之系統。
研究結果顯示，台灣之辦公建築耗能大約以照明、空調、事務機器之碳排各佔30%，其他碳排約佔10-13%，建築耗電強度(EUI)則根據辦公建築使用時程不同以及設計情況不同，大約落在50(kWh/m2)至180(kWh/m2)之間。碳排評價系統之建置上，則以Gamma分布擬合建築設計與基線碳排比之分布，建立評分查詢表。使用者可透過耗能計算之流程取得建築各項耗能之資訊，以及搭配類神經網路預測建築之空調耗能，來計算建築之全年空調耗能，並由經濟部所公布的電力排放係數，取得耗能予碳排之間的關係。並藉由與欲評估模型對比之基線模型之建立，根據碳排評分表來了解建築耗能之表現。

關鍵字

建築碳排 ； 建築生命週期 ； 日常使用階段 ； 建築耗能 ； 碳排評價系統

並列摘要

More than 80% of energy consumption in building life cycle is during daily usage phase, which is the main phase of carbon emissions of building life cycle. In this study, a building carbon emission benchmarking system was built to evaluate the carbon emissions during daily usage phase of office building. In this study, we try to achieve two main goal, the first is to estimate the energy consumption in a year by the design factors of office building, the second is to build a carbon emission benchmarking system to let the users easily know their building energy performance.
To estimate the energy consumption of office building, we try to collect the design factors of office building in Taiwan and combine with the calculation process in this study to estimate the building energy consumption of a whole year. The energy consumption in a typical office building includes: HVAC system, ventilation system, lighting, water pump, elevator equipment, and office equipment, these energy consumption items would be calculated and sum up to identify the energy performance. On the other hand, to provide a convenient benchmarking system, Neuron network prediction model was introduced in this study to let the users to get the HVAC system energy consumption in a whole year because of the complexity of estimating HVAC energy consumption compare to other energy demands.
To build up a benchmarking system, a baseline model was introduced in this study to evaluate the carbon emission performance of office building. Combining the building design factors and building regulations in Taiwan, we can build up a baseline building for every proposed building. And by the Ministry of Economic Affairs in Taiwan, we can get the coefficient of carbon emission to transfer the energy consumption to the amount of carbon emission. The ratio of the proposed building`s carbon emission and baseline building`s carbon emission is called Design and Baseline Carbon Emission Ratio (DBCER), and DBCER is used to evaluate the performance of the office building.
The results indicate that the lighting, office equipment and HVAC system each shares about 30% of total carbon emission in a whole year, and the other energy consumption items share about 10%-13% of the total carbon emission. The Energy Usage Intensity(EUI) value is between 50(kWh/m2) to 180(kWh/m2) generally in Taiwan. In the benchmarking system, Gamma distribution was used to fit the DBCER value, and the fitted curve was used to make a lookup table for the users to estimate their building energy performance by calculating the DBCER value and get the building score of the proposed building.

並列關鍵字

building carbon emission ； building life cycle ； building daily usage phase ； building energy consumption ； carbon emission benchmark system

參考文獻

參考資料

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