| 研究生: |
黃國倉 Huang, Kuo-Tsang |
|---|---|
| 論文名稱: |
空調設備量簡易預測法之研究
---由ENVLOAD推估冷凍主機容量--- A Study on the Simplified Method of Evaluating the Air-conditioning Capacity ---Evaluating the Capacity of Chiller base on ENVLOAD--- |
| 指導教授: |
林憲德
Lin, Shien-Te |
| 學位類別: |
碩士 Master |
| 系所名稱: |
規劃與設計學院 - 建築學系 Department of Architecture |
| 論文出版年: | 2002 |
| 畢業學年度: | 90 |
| 語文別: | 中文 |
| 論文頁數: | 102 |
| 中文關鍵詞: | 建築外殼耗能 、空調型建築 、空調設備量預測 |
| 外文關鍵詞: | energy consumption of building's encelope, DOE, prediction of chiller's capacity, ENVLOAD, air-conditioning building |
| 相關次數: | 點閱:108 下載:13 |
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以往對於決定建築空調設備量時,不是多以具經驗之空調技師依照建築之特性以及簡略之建築外殼條件約略加以判斷之外,就是使用建築空調計算機程式做熱負荷的動態運算,非經訓練有素的專業人員,一般人難以勝任。基於未來空調型建築物依法皆需計算其ENVLOAD值,本研究之主要目的在配合已行之多年並已成法規的外殼耗能評估指標ENVLOAD,進一步能夠推估其冷凍主機的容量,並試圖建立簡易空調設備量的預測公式。所選用的變數其一為ENVLOAD(X1),其二為空調外周區所佔空調面積之比重(X2)經本文定義為外周區係數γ。經由這二項變數以大略概估一棟建築物之空調設備量(m2/USRT),亦即每單位冷凍頓所能供應的空調面積。主要的研究內容如下:
1. 本研究將原有ENVLOAD規範內四個空調時區(六、十、十二、二十四小時空調時區)以及四種不同類型的建築類別(辦公類、百貨類、醫院類、旅館類),依照室內發散熱以及室內人員、照明的使用時間分佈,加以歸納成七大類空調預測類型。
2. 使用空調設計用的氣象資料,依台灣地理位置所涵蓋的緯度範圍,以北緯25度、北緯24度、北緯23度分別代表台灣北、中、南三地區進行電腦模擬。
3. 運用實驗計畫法,選用三個等級的直交表,配合三種緯度別以及七種空調預測類型,建立一共567種模擬樣本,用以代表理論上每一預測類型每一緯度所需逐一求之的157464種實際所有可能組合之樣本,以及七大類型三種緯度全部共3306744種之樣本。
4. 以DOE-2.2大型動態空調負荷計算程式進行模擬定風量空調箱空調系統(AHU)與風管機併用外氣引入空調系統(FCU+OA)的空調主機設備量部分,再配合BEEPII程式計算每一建築樣本的ENVLOAD值。
5. 研究成果經由將變因ENVLOAD、外周區係數γ與由電腦所模擬計算出來之空調設備量(m2/USRT),將模擬樣本分緯度別以及七大空調預測類型進行統計學上的複迴歸分析,一共建立AHU空調系統之空調預測公式二十一條,其重判定係數範圍落在0.732至0.903之間,並同時建立FCU+OA空調系統之修正係數α。
本研究之成果將以往需依經驗判斷或專業軟體計算之空調設備量預估,藉由簡易預測公式的建立,判斷出空調的設備量,除簡化預估之難度外更能避免超量設計的情形發生,此外更建立了由ENVLOAD推估冷凍主機容量的預測模式。
▃ Research Purpose:
1. Regarding the process of determining the chiller capacity(m2/USRT) in air-conditioning systems of a building, in spite of some professionals have the ability to do such complicated works, few can evaluate the capacity of the chiller accurately without the help of sophisticated software such as DOE which are not made for the ordinaries.
2. Furthermore, on account of ENVLOAD(kwh/m2-year)(the evaluating index of a building’s envelope loads through out one year in Taiwan)which by law has become an indispensable requirement of the air-conditioning buildings. Additionally, the research is focus on developing a simplified method in predicting the capacity of the chiller base on ENVLOAD with the convenient of the ENVLOAD index that has been calculated previously.
▃ Research Methods:
1. To establish the predicting models, two variables have been introduced, one is ENVLOAD that has been mentioned above and the other is the coefficient of perimeter zone within air-conditioning area(which is defined as γ in the paper).
2. In order to co-ordinate the predicting models with ENVLOAD, seven sets of predicting patterns have been generalized from the norm of ENVLOAD evaluating system.
3. Establish the predicting models by simulation. We use DOE-2.2 software which is widely used in calculating the dynamic building loads worldwide to simulate the capacity of the chiller from heat loads in a building.
4. The experimental design method is introduced to generate the simulative building models finitely, in order to represent the whole possibly samples and thus reduces the amount of the simulations.
5. During computer simulation, we adopt air-conditioning design based meteorological data to collocate with DOE-2.2 to prevent from resulting insufficient capacity.
▃ Conclusion:
1. Using multiple-regression method to establish the predicting models. While the dependent variable is the chiller capacity the two independent variables are ENVLOAD and γ.
2. Totally, 21 formulas have been set up within 7 predicting categories. The R-square value lies between 0.732 and 0.903 which is convincible.
3. Moreover, to broaden the application of the predicting models, FCU+OA air-conditioning system factor(α) is built simultaneously in the paper.
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