本文選題：工業(yè)建筑 + 基準(zhǔn)建筑�。� 參考：《蘇州科技學(xué)院》2015年碩士論文

【摘要】：工業(yè)是國(guó)民經(jīng)濟(jì)的支柱,而蘇州市地處長(zhǎng)三角發(fā)達(dá)地區(qū),工業(yè)產(chǎn)業(yè)結(jié)構(gòu)復(fù)雜,能源消耗量很大。在建筑總能耗中工業(yè)建筑的能耗所占比重逐年上升,工業(yè)建筑節(jié)能研究變得十分重要。與其他地區(qū)相比,蘇州市工業(yè)建筑節(jié)能潛力大。因此,探討蘇州市的工業(yè)建筑能耗水平,評(píng)價(jià)分析工業(yè)建筑能耗意義重大。本文首先通過調(diào)研蘇州市25個(gè)現(xiàn)有典型工業(yè)建筑,獲得近3年來典型工業(yè)建筑能耗數(shù)據(jù),進(jìn)而對(duì)其中16個(gè)典型電子類工業(yè)建筑做出能耗評(píng)價(jià),找出電子類工業(yè)建筑節(jié)能方面存在的問題,從圍護(hù)結(jié)構(gòu)熱工性能、暖通、給排水、管理與管理控制方面,總結(jié)典型典型工業(yè)建筑的能耗特點(diǎn),挖掘工業(yè)建筑的節(jié)能潛力,并提出節(jié)能建議。能耗計(jì)算主要分為簡(jiǎn)易計(jì)算方法與計(jì)算機(jī)模擬方法。計(jì)算機(jī)模擬的方法在綠色建筑評(píng)價(jià)及LEED評(píng)估均有廣泛的應(yīng)用,由清華大學(xué)開發(fā)的建筑環(huán)境設(shè)計(jì)模擬分析軟件DeST(Designer's Simulation Toolkits),適用于分析工業(yè)建筑的能耗。以蘇州某電子工業(yè)廠房為例,首先對(duì)該工業(yè)廠房進(jìn)行節(jié)能審查,分析其各項(xiàng)指標(biāo)是否滿足規(guī)范要求。利用DeST對(duì)工業(yè)廠房進(jìn)行能耗模擬。分析了工業(yè)廠房?jī)?nèi)的空調(diào)季自然室溫特點(diǎn),工業(yè)廠房的冷負(fù)荷特征、能耗結(jié)構(gòu)。根據(jù)調(diào)研所得的各家電子類工業(yè)建筑的能耗賬單,對(duì)影響建筑能耗的7個(gè)因數(shù)用數(shù)值統(tǒng)計(jì)軟件SPSS進(jìn)行偏相關(guān)分析,建筑能耗與建筑面積、空調(diào)能耗、空調(diào)類型、照明總功率相關(guān)性較大且顯著,進(jìn)而對(duì)能耗數(shù)據(jù)進(jìn)行多元回歸分析,從而獲得建筑能耗多元線性回歸方程。通過箱線圖法及能耗誤差分析,選出6號(hào)建筑為基準(zhǔn)建筑,通過對(duì)基準(zhǔn)建筑的模擬,獲得全年8760h逐時(shí)能耗數(shù)據(jù)。采用歸一化能耗系數(shù)預(yù)測(cè)建筑每小時(shí)的能耗數(shù)據(jù),誤差在[-10%,10%]范圍內(nèi),工業(yè)建筑基本電力消耗ECBe的誤差頻率在83%,工業(yè)建筑變化的電力消耗ECVe的誤差頻率在75%,采用歸一化能耗系數(shù)結(jié)合實(shí)際的能耗賬單快速預(yù)測(cè)企業(yè)每小時(shí)的能耗數(shù)據(jù)的方法比較可靠。
[Abstract]:Industry is the mainstay of the national economy, and the industrial structure of the Suzhou city is very complicated and the energy consumption is very large. The proportion of energy consumption of industrial buildings is increasing year by year in the total energy consumption of buildings. The energy saving research of industrial buildings is very important. Compared with other areas, the energy saving potential of Suzhou is great. Therefore, the exploration of the energy saving potential of the industrial buildings is great. Therefore, the exploration of the energy saving potential of the industrial buildings is great. Therefore, the exploration of the energy saving potential of the industrial buildings is great. It is of great significance to evaluate the energy consumption level of industrial buildings in Suzhou and to evaluate and analyze the energy consumption of industrial buildings. First, through the investigation of 25 typical industrial buildings in Suzhou, the energy consumption data of the typical industrial buildings in the last 3 years are obtained, and then the energy consumption of 16 typical electronic industrial buildings is evaluated, and the energy saving aspects of the electronic industrial buildings are found out. The existing problems, from the thermal performance of the enclosure structure, HVAC, water supply and drainage, management and management control, summarize the characteristics of typical typical industrial buildings, excavate the energy saving potential of industrial buildings, and put forward energy saving suggestions. The calculation method of energy consumption is mainly divided into simple calculation method and computer simulation method. The computer simulation method is in green building. The evaluation and LEED evaluation are widely used. The software DeST (Designer's Simulation Toolkits), which is developed by Tsinghua University, is suitable for the analysis of energy consumption of industrial buildings. Taking an electronic industrial plant in Suzhou as an example, it is first to review the industrial building, and to analyze whether the indexes meet the standard. Use DeST to simulate the energy consumption of industrial buildings, analyze the characteristics of the air conditioning season natural room temperature in industrial buildings, the cold load characteristics and energy consumption structure of industrial buildings. According to the energy consumption bill of various electronic industrial buildings, the 7 factors affecting the building energy consumption are analyzed by the partial correlation analysis of the numerical statistics software SPSS. The correlation between energy consumption and building area, air conditioning energy consumption, air conditioning type and total lighting power is significant and significant. Then multiple regression analysis of energy consumption data is carried out to obtain multiple linear regression equation of building energy consumption. Through box line graph method and energy consumption error analysis, 6 building is selected as datum building, and 8 of the datum building is simulated to obtain 8 of the year. 760h hourly energy consumption data. The normalized energy consumption coefficient is used to predict the energy consumption data per hour of the building. The error frequency is in the range of [-10% and 10%]. The error frequency of the basic power consumption of industrial buildings is 83%, and the error frequency of the ECVe is 75% for the change of industrial buildings. The normalized energy consumption coefficient combined with the actual energy consumption bill is quickly predicted. The method of hourly energy data is reliable.

【學(xué)位授予單位】：蘇州科技學(xué)院
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TU111.195

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