气候变化下的建筑能耗预测

该文梳理并讨论4种产生未来逐时气象数据的方法:度日法、补偿法、随机气象模型法及全球气候模型法,并着重阐述补偿法中变形法的原理和计算过程;使用西安的历史观测数据及IPCC月尺度预测数据,产生2050年的逐时气象数据;应用Energy Plus对西安高层住宅及办公建筑进行气候变化下的建筑能耗动态模拟。建筑能耗模拟用未来逐时气象数据的精细化研究是进行建筑节能设计和可持续发展的基础工作。     

空调能耗分析用简明气象参数的构成研究

本文分析了我国气候的特点,阐明了建立新的空调能耗计算用气象数据的必要性。以长沙地区为例,对标准年气象参数的构成进行了研究,给出了长沙地区空调能耗简易计算的温频统计图表。     

南京地区冬季窗节能研究

根据南京市的典型年逐时气象参数，对于该市的同一座建筑物，应用自编的逐时能耗模拟程序对围护结构冬季采暖期能耗（窗户，墙体和屋顶）进行逐时动态负荷模拟计算，通过逐时负荷计算累加得到不同窗户，墙体和屋顶的冬季采暖期间能耗，结果表明，塑窗比钢窗节能，双层窗比单层窗节能，对单层窗而言，双玻窗比单玻窗节能。     

建筑能耗模拟用典型年气象参数的选取方法

准确的典型气象年(TMY)数据是建筑能耗模拟不可或缺的基本条件。TMY的生成需要长期全面的气象数据,而中国大部分气象台站所能提供完整且符合TMY挑选要求的气象数据存在一定困难。该文以北京为例,应用多元统计中的聚类和主成分法,针对不同气象参数生成的TMY进行研究,并对典型建筑进行能耗模拟,得到不同气象参数下TMY的综合表达式并探寻北京地区气象参数的相关关系,提出建筑能耗模拟用TMY室外气象参数的选取方法。     

建筑能耗分析方法的研究与实例

建筑能耗分析是建筑节能和建筑能效管理的基础。在分析常用建筑能耗分析方法的基础上,对比了计算机模拟法、度日法、温频法三种方法的优缺点,并简要介绍一些改进措施,使计算结果更符合实际情况,为建筑能耗计算及节能措施研究提供有益的参考。     

基于改进的BIN法模拟分析建筑空调能耗

利用改进的BIN法对南京某空调建筑的能耗进行模拟,并应用正交试验设计、方差分析、回归分析等数理统计方法对能耗进行分析,得到建筑能耗显著影响因素和各因素影响程度大小关系,从而为建筑节能设计与空调运行管理提供依据。     

气候变化对中国典型气候区办公建筑能耗的影响研究

基于联合国政府间气候变化专门委员会IPCC报告SRES情景下中排放A1B场景及低排放B1情景的预测结果,针对中国5个建筑热工设计分区的代表城市,以历史30年气象观测数据挑选出的典型气象年为基准,采用"Morphing"方法生成未来2种排放场景下代表城市的建筑能耗模拟用逐时气象数据,并对直至21世纪末每隔10年作为一个时间节点,进行代表城市办公建筑的全年能耗模拟,预估气候变化下建筑能耗的变化趋势。结果表明,总体上5个代表城市办公建筑的采暖能耗呈降低趋势、制冷能耗呈增加趋势,但在不同的排放情景下,不同气候区代表城市的建筑能耗变化有明显区别。     

基于BIN法的空调建筑全年能耗影响因素分析

本文利用BIN法初步选定空调建筑能耗的影响因素后,采用正交试验、回归分析和方差分析等方法,得到全年能耗与各个主要因素的函数关系、显著影响因素及全年能耗影响因素排序图,从而为空调和建筑节能设计提供依据.     

江水源热泵机组年运行能耗预测方法研究

在建筑工程的可行性研究阶段,空调系统冷热源的年运行能耗预测是静态投资回收期分析、全寿命周期成本分析中的核心组成部分,是冷热源选型的重要依据之一.然而,在实际项目中通常选用IPLV/NPLV、设计工况COP进行年运行能耗估算,计算结果与实际能耗有较大的误差.在已知建筑设计冷、热负荷的前提下,引入平衡温度概念,采用BIN方法预测不同温度下的建筑负荷,通过参数修正的方式预测江水源热泵机组在部分负荷率情况下功率,将热泵机组功率修正系数的变化函数拟合为水源侧进水温度和负荷侧回水温度的多项式.对长江上游地区江水温度及气象参数进行监测,并建立了江水温度与空气于球温度的数学关系.提出江水源热泵机组年运行能耗预测方法.该方法反映了系统运行的实际特征,且计算过程较为简单,可以在实际工程中应用.     

空调动态负荷计算与预测参数的数据处理

根据西安参考年 (TRY)逐时气象参数 ,采用动态模拟程序计算了某办公楼 4-9月逐时冷负荷。对计算数据和结果的统计处理与分析 ,表明冷负荷与当前时刻的室外干球温度呈一定的线性关系 ,与太阳辐射呈强烈的非线性关系     

某商住楼两种不同空调方案的能耗分析

采用BIN能耗分析的方法,对天津市某一商住楼空调系统的两种不同方案进行能耗分析,比较两种系统在能源消耗上的差别,并提出了系统节能改造建议。     

Mixed-mode ventilation and air conditioning as alternative for energy savings: a case study in Beirut current and future climate

The aim of this work is to assess the use of mixed-mode ventilation for a typical office building in Lebanon and consequently reduce Heating Ventilation and Air Conditioning (HVAC) energy consumption in the observed current and under the future projected climatic conditions. Mixed-mode cooling is considered a compromise between the insufficient natural ventilation and the expensive year round-operated HVAC. A control algorithm is set for windows and HVAC system to ensure mixed-mode operation. Dynamic simulations are performed on a typical office building in Beirut City under the mixed-mode operation in the present and the future using commercial IES-VE software. The results of the software were validated against measured HVAC and total energy consumption of the typical office base case with conventional mechanical system. The results of the simulations are evaluated in terms of potential reduction in energy consumption under the present and the future weather data. Finally, a lifecycle cost analysis is performed for the proposed system, and its payback period is computed. Under present construction practices and weather data, 31% annual energy savings were achieved using mixed-mode system. Under future 2050s projected weather data, annual energy savings of 21% was attained with a payback period of 3.8 years.     

Use of different methodologies for thermal load and energy estimations in buildings including meteorological and sociological input parameters

This review paper provides first an overview of the background for meteorological and sociological influences on thermal load and energy estimations. The different yearly representations of weather parameters (test reference year (TRY), design reference year (DRY), typical meteorological year (TMY) and weather year for energy calculations (WYEC)) are discussed, and compared to simplified representations of weather characteristics. Sociological influences on energy demand are discussed in relation to attitude and culture.Many methods exist for estimating thermal load and energy consumption in buildings, and they are primarily based on three different methodologies; regression analyses, energy simulation programs and intelligent computer systems. Regression analyses are mainly based on large amounts of metered load data, long-term weather characteristics and some information about the buildings. Energy simulation programs require detailed information about the buildings and sociological parameters, as well as thorough representation of weather data. Intelligent computer systems require metered load data, weather parameters and building information. The advantages and disadvantages of the alternative methodologies are discussed, as well as when and where to use them. Finally, the more specific usages of the methodologies are exemplified through three specific methods: conditional demand analysis (CDA), engineering method (EM) and neural networks (NN).     

山东省采暖空调度日数及其分布特征

在分析山东地区气象变化规律的基础上。应用近10年的实测气象数据，选出了平均月。研究了山东地区标准年气象参数的构成方法，求出了全省各地的采暖度日数和空调度日数，探讨了采暖度日数和空调度日数的分布特征。该研究为计算采暖能耗、空调能耗和推行建筑节能技术，奠定了坚实的基础。     

Some perceptions on typical weather year—from the observations of Hong Kong and Macau

Accurate prediction of building energy performance requires precise information of the local climate. Typical weather year files like test reference year (TRY) and typical meteorological year (TMY) are commonly used in building simulation. They are also essential for numerical analysis of the sustainable and renewable energy systems. The weather year file of one city is often employed by the nearby cities for such purposes. In this paper, the developments of customized weather year formulation are reviewed. The key issues are discussed making reference to two neighboring cities, Hong Kong and Macau, using their weather data records over a century, and the typical weather year files developed. The findings support the preference of TMY over TRY. It is also suggested that the TMY selection process should include the most recent meteorological observations, and should be periodically reviewed to well reflect the long-term climate change.     

A comparison of the accuracy of building energy analysis in Bahrain using data from different weather periods

Weather data are important in building design and energy analysis. In Bahrain, the weather data currently used are based on far past climatic information. Climate variability during the last few decades has raised concern over the ability of these data to provide accurate results when analysing the energy performance of buildings. This study discusses issues related to climate variability and evaluates its impact on the performance of weather data used in building simulation. An evaluation was performed using two methods: firstly, a comparison of measured climatic elements and secondly, a comparison of the thermal performance of two statistically based weather data files. With respect to their impact on typical Bahraini building thermal systems, the comparison was carried out between simulation results and the actual energy consumption of two case studies. This paper shows a 14.5% difference between simulation results based on far past data and present electricity consumption and concludes that the prediction of present and future performance based on recent updated data gives better results.     

An analysis of climatic influences on chiller plant electricity consumption

Principal component analysis of dry-bulb temperature, wet-bulb temperature, global solar radiation, clearness index and wind speed was conducted, and a two-component solution obtained which could explain 80% of the variance in the original weather data. Clustering analysis of these two principal components resulted in a total of 18 typical day types being identified. A year long monitoring of the daily chiller plant electricity consumption in a fully air-conditioned office building was conducted. It was found that the typical day types exhibited daily and seasonal variations similar to the daily and monthly electricity consumption recorded. Three regression models were developed to correlate the daily chiller plant electricity consumption and the corresponding day types. The coefficient of determination (R²) was 0.86–0.99 showing strong correlation. It is proposed that the day type approach can be used as a tool for weather normalisation and inter-year comparisons in the analysis of energy savings due to building retrofits. It was also found that the typical day types identified appeared to show a slight increasing trend during the 28-year period (1979–2006) indicating a subtle, but gradual change of climatic conditions that might affect chiller plant electricity consumption in future years.     

Typical weather data of main Turkish cities for energy applications

Energy consumption and performance investigations of environment‐dependent systems such as building HVAC and refrigeration systems, solar collectors, cooling towers, usually require weather information. This introduces a problem because there may be significant variances between the recurrent days or years. In this work, typical hourly weather data for the selected 23 provinces that represent demographic and climatic conditions of Turkey are obtained by using actual recordings. The results are stored as computer files ready to be used by simulation programs. By using these typical meteorological years, heating and cooling degree‐days, dry‐bulb temperature bins and winter and summer design dry‐bulb temperatures are calculated. Sample typical‐year simulations show for example that energy savings of about 11 and 16 per cent could be expected in Ankara by 3 and 5 K night‐setback, respectively. Copyright © 2000 John Wiley & Sons, Ltd.     

A new method to develop typical weather years in different climates for building energy use studies

Principal component analysis of 30-year long-term meteorological variables was conducted. Typical principal component years (TPCYs) were determined for Harbin, Beijing, Shanghai, Kunming and Hong Kong representing the five major architectural climates across China: severe cold, cold, hot summer and cold winter, mild, and hot summer and warm winter. In each climate zone, the TPCY was compared with the 30 individual years and the widely used typical meteorological year (TMY). The monthly principal component and the predicted total building energy consumption based on the TPCY and TMY were very close to the 30-year long-term mean estimation. TPCY for the 21st century in each of the five cities was also identified using predictions from general climate models. The TPCY approach is a good alternative to the TMY method. Firstly, predicted building energy use from TPCY is closer to the long-term estimation than that from the TMY in different climates. Secondly, because only monthly data are considered, the development of TPCY is much simpler and less time-consuming. This would have important applications in the regular updating of typical weather years for building energy studies and in the assessment of the impact of climate change on energy use in the built environment.