苏州地区电子类工业建筑能耗评价分析

发布时间：2018-05-01 20:37

本文选题：工业建筑 + 基准建筑　；参考：《苏州科技学院》2015年硕士论文

【摘要】：工业是国民经济的支柱,而苏州市地处长三角发达地区,工业产业结构复杂,能源消耗量很大。在建筑总能耗中工业建筑的能耗所占比重逐年上升,工业建筑节能研究变得十分重要。与其他地区相比,苏州市工业建筑节能潜力大。因此,探讨苏州市的工业建筑能耗水平,评价分析工业建筑能耗意义重大。本文首先通过调研苏州市25个现有典型工业建筑,获得近3年来典型工业建筑能耗数据,进而对其中16个典型电子类工业建筑做出能耗评价,找出电子类工业建筑节能方面存在的问题,从围护结构热工性能、暖通、给排水、管理与管理控制方面,总结典型典型工业建筑的能耗特点,挖掘工业建筑的节能潜力,并提出节能建议。能耗计算主要分为简易计算方法与计算机模拟方法。计算机模拟的方法在绿色建筑评价及LEED评估均有广泛的应用,由清华大学开发的建筑环境设计模拟分析软件DeST(Designer's Simulation Toolkits),适用于分析工业建筑的能耗。以苏州某电子工业厂房为例,首先对该工业厂房进行节能审查,分析其各项指标是否满足规范要求。利用DeST对工业厂房进行能耗模拟。分析了工业厂房内的空调季自然室温特点,工业厂房的冷负荷特征、能耗结构。根据调研所得的各家电子类工业建筑的能耗账单,对影响建筑能耗的7个因数用数值统计软件SPSS进行偏相关分析,建筑能耗与建筑面积、空调能耗、空调类型、照明总功率相关性较大且显著,进而对能耗数据进行多元回归分析,从而获得建筑能耗多元线性回归方程。通过箱线图法及能耗误差分析,选出6号建筑为基准建筑,通过对基准建筑的模拟,获得全年8760h逐时能耗数据。采用归一化能耗系数预测建筑每小时的能耗数据,误差在[-10%,10%]范围内,工业建筑基本电力消耗ECBe的误差频率在83%,工业建筑变化的电力消耗ECVe的误差频率在75%,采用归一化能耗系数结合实际的能耗账单快速预测企业每小时的能耗数据的方法比较可靠。
[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.

【学位授予单位】：苏州科技学院
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TU111.195

【参考文献】