建筑能耗分析逐时气象资料的开发研究

逐时气象资料对建筑能耗动态模拟是不可缺少的。在编制《夏热冬冷地区居住建筑节能设计标准》时 ,应用了动态模拟计算软件。为了开发逐时气象资料 ,通过与美国劳伦斯·伯克利国家实验室的技术合作 ,研究建立了我国城市的逐时资料。介绍了由我国气象台站报道的气象参数建立太阳辐射量的数学模型 ,阐述了典型气象月的选取原则 ,以及逐时数值插补方法。     

典型气象年和典型代表年的选择及其对建筑能耗的影响

介绍了典型气象年和典型代表年的选择原理和几种常见的选择方法。不同的方法考虑了不同气象参数的加权因子和气象数据的连续性。介绍了将太阳辐射总量分为太阳直射辐射量与太阳散射辐射量的应用模型,并依据香港的气象数据,分别计算选出了香港的典型气象年与典型代表年。为了验证不同方法计算出的典型气象年与典型代表年对研究对象、系统的影响,作了一个实例建筑物能耗动态模拟。结果表明,不同典型气象年对模拟结果的影响偏差较小,而典型代表年的影响较大;选择合适方法计算的典型气象年对保证模拟评估结果的正确性具有重要意义。     

气候变化下建筑能耗模拟气象数据研究

气象参数是建筑能耗模拟的基础,随着全球气候异常变暖,必将对建筑采暖和空调能耗产生重要影响.进行未来气候条件下的建筑能耗模拟,必须首先开展未来模拟气象参数的研究.根据TMY2模拟气象参数模式提出了节能分析气象年(AEEMY)模拟气象参数模式.使用了3个气候模型预测了中国建筑热工分区代表城市未来2021-2050的30 a气象参数.使用AEEMY模式得到了1971-2000年和2021-2050年代表城市的建筑能耗模拟气象参数.应用DOE2模拟软件对中国各气候区的居住建筑在2种气候条件下进行了建筑能耗模拟.验证了该模拟气象数据模式的有效性和可行性.     

建筑能耗模拟典型年中气象参数权重的确定

在建筑能耗模拟用典型年的生成中,传统的Finkelstein-Schafer统计方法对气象参数赋予了固定的权重因子,但有关研究表明,由于地域间气象资源不同,气象参数权重因子的固化有待商榷。针对挑选典型年时气象参数权重因子统一与否对典型年挑选结果和建筑能耗模拟准确性的影响问题,选同一建筑热工分区中寒冷地区的代表城市北京和拉萨,分别使用FS方法和主成分法进行了典型年的挑选,并对典型公共建筑建模进行了能耗模拟分析。结果表明:FS统计方法适于表征单独气象参数的长期相似性,但存在对太阳辐射参数权重赋予过大的问题,适用于太阳能丰富地区;而主成分法适合寻求当地气象资源的本质特征,使用主成分法时对气象参数的选择尤为重要。     

建筑能耗分析用逐日气象数学模型的建立

为给建筑能耗分析工作提供可靠依据。选取长春市１０年（１９７８￣１９８７）的６项逐日气象参数,建立了东北地区的６维疏系数混合回归模型。经检验,由该模型模拟得出的气象参数反映了实测值所具有的规律和特性。     

广州地区典型年气象资料计算方法

针对广州地区气象站典型年数据的特点,给出了空调能耗分析用室外标准年气象参数的生成方法,为编制能耗估算软件打下了一定的理论基础。     

不同统计时长对典型气象年选取结果的影响

为建立我国建筑节能用基础气象数据库,针对我国气象数据实际记录状况,需分析不同统计时长对典型气象年挑选结果的影响。分别在5个建筑热工设计分区的11个二级区划中各选取一个典型城市,采用美国Sandia国家实验室法,对比缩短后的统计时长(3～15 a)和长期30 a挑选出的不同典型年结果的差异。结果表明:为了控制辐射标准差的平均波动幅度在1 MJ/m2以内,同时温度标准差的平均波动幅度也在1℃以内,最少要用8 a统计时长的数据,但根据城市位置和气候的不同,仍然会有部分城市的温度或辐射标准差的波动幅度较大。     

建筑能耗分析用室外气象数学模型的建立

建立徐州地区的逐日和逐时气象数学模型。经检验,由该模型模拟得出的气象参数反映了实测值所具有的规律性和数字特征,给建筑能耗分析工作提供了可靠的依据。     

An evaluation of the effects of various parameter weights on typical meteorological years used for building energy simulation

In this paper, we evaluate the influence of different parameter weights in creating “typical year” weather data following the typical meteorological year (TMY) methodology, by studying two sets of 3600 alternate weather files created using different parameter weights for Beijing (China) and New York City (USA). A “typical year” weather file consists of twelve distinctive months, each considered typical for that month of the year. Such a typical month, named “typical meteorological month (TMM),” is commonly identified by using a certain combination of parameter weights, such as 4:4:4:12, for dry bulb temperature, dew point temperature, wind speed, and solar radiation as in the TMY weather files developed by US National Climate Data Center (NCDC), or 4:4:2:10 in the newer TMY2 and TMY3 weather files developed by National Renewable Energy Laboratory (NREL). In this study, we investigate the influence of varying the parameter weights on the TMMs and the resultant new TMY weather files (nTMY). We found that the distribution of new 3600 TMMs tend to cluster within one or a few years for each month, and that the probabilities are very high for significant overlap between the new TMMs and the original TMMs chosen using the TMY/TMY2 weighting. Compared to the TMM data in TMY, the deviations of air temperatures and solar radiation values of the new TMMs and nTMYs derived from the 20-year weather data are less than 10% for both Beijing and New York. This confirms that the creation of “typical year” weather data is not very sensitive to the weighting of the different weather parameters, and that most nTMYs created and evaluated in this study are empirically close to the TMY data intended for use of simulating building energy consumption.     

一种新的典型气象年权重因子构建方法

典型气象年(TMY)是建筑能耗模拟用基础参数,其准确与否直接影响建筑能耗模拟和建筑节能设计.目前TMY的生成方法中,对挑选TMY的气象参数皆采用统一的权重因子,未能体现不同地域气象参数的影响差异.基于Sandia国家实验室法,采用随机赋权法验证了权重对TMY的挑选结果有明显影响;采用EnergyPlus软件对北京地区典...     

Developing a modified typical meteorological year weather file for Hong Kong taking into account the urban heat island effect

Building energy computer simulation software is a useful tool for achieving sophisticated design and evaluation of the thermal performance of buildings. For successful thermal and energy simulation of buildings, it requires hourly weather data such as dry bulb air temperature, relative humidity, solar radiation, wind speed, etc. Nowadays, an urban city faces a problem of an urban heat island which causes the urban area to have a higher air temperature than the rural region. Since the currently available weather dataset used in building simulation software mainly comes from weather stations located in remote and rural areas, the impact of the urban heat island on thermal and energy performance of buildings may not be effectively reflected. This paper reports an approach to construct a modified typical meteorological weather file, taking into account the urban heat island effect in the summer season. Field measurements have been carried out in the summer months and the corresponding urban heat island intensities were then determined. With a morphing algorithm, an existing typical meteorological year weather file was modified. An office building and a typical residential flat were modeled with a renowned building energy simulation program EnergyPlus. Computer simulations were conducted using the existing and modified typical meteorological year weather files. It was found that there was around a 10% increase in air-conditioning demand caused by the urban heat island effect in both cases. The implications of this and further work will also be discussed in this paper.     

建筑能耗分析用室外气象数学模型的建立

选用5个气象参数作为模拟量建立了逐日气象参数的模拟模型,通过平稳化变换将模拟量变换成平稳时间序列,采用混合回归模型进行了逐日量的模拟,根据模拟得出的逐日参数建立了逐时气象参数的模拟模型,用逐日、逐时模型对徐州地区的气象参数进行了模拟。     

上海建筑节能现状与对策

本研究首次用统计调查与模型推算相结合方法估算了上海的建筑能耗。１９９６年上海的建筑能耗为１１７６．６万ｔ标准煤，占上海总能耗的２５．４％。其中建筑使用能耗为６１９．９万ｔ标准煤，占上海总煤耗的１３．４％，建筑制造能耗（包括建材生产能耗）为５５６．７万ｔ标准煤，占上海总能耗的１２％。     

济南地区某办公楼能耗模拟与节能研究

如今,办公建筑已成为社会的主要建筑类型。办公建筑也随之成为了能耗大户,如何对办公建筑降低能耗成为如今的必要思考。本文选取济南地区某一办公建筑,利用DeST软件对其能耗进行模拟,并与参照建筑进行对比,得到济南地区办公建筑降低能耗的实用规律,为今后办公建筑降低能耗,节能减排提供参考。