本文選題：公共建筑 + 冷負(fù)荷��； 參考：《湖南大學(xué)》2015年碩士論文

【摘要】：能源是制約人類社會(huì)的快速發(fā)展的瓶頸,節(jié)約能源是每一個(gè)公民應(yīng)盡的義務(wù)。在我國,由于經(jīng)濟(jì)快速生長,能源需求量逐年增加。作為社會(huì)總能耗的主要組成部分,建筑能耗的上升速度較快,所以在建筑領(lǐng)域,其節(jié)能潛力很大,對(duì)進(jìn)一步實(shí)現(xiàn)我國的能源戰(zhàn)略目標(biāo)以及可持續(xù)發(fā)展有重要意義�？照{(diào)系統(tǒng)作為影響建筑能耗最重要的因素,實(shí)現(xiàn)建筑節(jié)能應(yīng)從準(zhǔn)確計(jì)算建筑冷熱負(fù)荷開始,尤其是冷負(fù)荷。本文首先分析了影響建筑冷負(fù)荷的影響因素以及現(xiàn)有的負(fù)荷預(yù)測(cè)方法,得知設(shè)計(jì)人員在計(jì)算冷負(fù)荷值時(shí)傾向使用計(jì)算機(jī)模擬法和估算法。然而由于計(jì)算機(jī)模擬方法需要輸入的參數(shù)過多且耗時(shí)長,人們不易掌握,估算法由于估算指標(biāo)值在現(xiàn)有規(guī)范和設(shè)計(jì)中僅僅只根據(jù)建筑功能粗略的進(jìn)行分類,往往易使計(jì)算的冷負(fù)荷偏大,造成能源的浪費(fèi)。因此在不失計(jì)算精度的基礎(chǔ)上簡(jiǎn)化計(jì)算方法,分析負(fù)荷影響因素,是現(xiàn)階段預(yù)測(cè)建筑冷負(fù)荷的主要研究?jī)?nèi)容。通過對(duì)冷負(fù)荷影響因素定性分析,選出影響建筑冷負(fù)荷比較顯著的因素：建筑物所在地理位置、建筑功能、體形系數(shù)、窗墻比、綜合傳熱系數(shù)、室內(nèi)人均密度等作為分類指標(biāo),對(duì)現(xiàn)有公共建筑進(jìn)行分類,建立一系列基準(zhǔn)建筑模型,同時(shí)借用能耗模擬軟件DesignBuilder對(duì)每一類模型進(jìn)行全年冷負(fù)荷特性分析,最終選取全年第51大單位面積冷負(fù)荷值作為冷負(fù)荷指標(biāo)計(jì)算值,建立公共建筑單位面積冷負(fù)荷指標(biāo)值數(shù)據(jù)庫。最后,以長沙市所調(diào)研的公共建筑為實(shí)例驗(yàn)證本文所建數(shù)據(jù)庫的適用性。通過分析辦公建筑、商業(yè)建筑、賓館類建筑以及教育類建筑實(shí)際運(yùn)行值、數(shù)據(jù)庫選取值以及設(shè)計(jì)階段通過估算法計(jì)算的設(shè)計(jì)值三者之間的大小關(guān)系得知,本文所建數(shù)據(jù)庫在預(yù)測(cè)公共建筑冷負(fù)荷時(shí),其預(yù)測(cè)精度能夠滿足要求,其誤差大小在工程允許范圍內(nèi)。而且,只要知道一定的建筑參數(shù),本文所建數(shù)據(jù)庫同樣適用于城市規(guī)劃階段冷負(fù)荷的預(yù)測(cè)。由實(shí)例驗(yàn)證可得知,數(shù)據(jù)庫選取值和實(shí)際運(yùn)行值之間的誤差較小,表明本文所建的公共建筑單位面積冷負(fù)荷指標(biāo)數(shù)據(jù)庫具有較好的有效性和較高的預(yù)測(cè)精確度。可以認(rèn)為,本文所建數(shù)據(jù)庫對(duì)公共建筑冷負(fù)荷的預(yù)測(cè)能夠提供一定的理論依據(jù)和工程應(yīng)用價(jià)值。
[Abstract]:Energy is the bottleneck restricting the rapid development of human society. Saving energy is the duty of every citizen. In China, due to the rapid growth of the economy, energy demand is increasing year by year. As the main component of the total energy consumption of the society, the building energy consumption is rising rapidly, so in the field of construction, its energy saving potential is very large, which is of great significance to the further realization of our country's energy strategic goal and sustainable development. As the most important factor affecting building energy consumption, air conditioning system should begin with accurate calculation of building cooling and heat load, especially cold load. In this paper, the factors affecting the cooling load of buildings and the existing load forecasting methods are analyzed. It is found that the designers tend to use computer simulation and estimation methods in the calculation of the cooling load. However, because the computer simulation method needs to input too many parameters and takes a long time, it is difficult for people to grasp the estimation method, because the estimation index value is only roughly classified according to the building function in the existing specification and design. Often easy to make the calculation of the cooling load is too large, resulting in a waste of energy. Therefore, simplifying the calculation method and analyzing the factors affecting the load on the basis of not losing the calculation precision are the main research contents of forecasting the building cooling load at the present stage. Through the qualitative analysis of the factors affecting the cooling load, the factors that influence the building cooling load are selected as the classification indexes: the location of the building, the function of the building, the coefficient of shape, the ratio of window to wall, the comprehensive heat transfer coefficient, the per capita density of the room, etc. The existing public buildings are classified and a series of benchmark building models are established. At the same time, energy consumption simulation software DesignBuilder is used to analyze the annual cooling load characteristics of each model. Finally, the 51st unit area cold load value is selected as the calculated value of the cooling load index, and the database of the common building unit area cold load index value is established. Finally, taking the public buildings investigated in Changsha as an example, the applicability of the database is verified. By analyzing the actual operation values of office buildings, commercial buildings, hotel buildings and educational buildings, the value of database selection and the design value calculated by the method of estimation in the design stage, the size relationship among them is obtained. The prediction accuracy of the database in this paper can meet the requirements when forecasting the cooling load of public buildings, and the error is within the allowable range of the project. Moreover, as long as certain building parameters are known, the database can also be used to predict the cooling load in urban planning stage. It can be seen that the error between the selected value and the actual operating value of the database is small, which indicates that the database of unit area cooling load index built in this paper is effective and accurate. It can be concluded that the database built in this paper can provide certain theoretical basis and engineering application value for forecasting the cooling load of public buildings.
【學(xué)位授予單位】：湖南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TU242;TU831.2

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本文編號(hào)：1937273