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。     

上海地区建筑能耗计算用典型年气象数据的研究

以同济大学某教学楼为研究对象,对比了用EnergyPlus模拟计算得到的全年耗电量和实测耗电量,研究了用于建筑能耗动态计算的5套典型年气象数据的可靠性,得出了CTYW气象数据最接近现实情况的结论。对其中影响较大的参数如室外气温、湿度和太阳辐射量进行分析和比较,指出所用5套典型年气象数据间的差异来自观测值的缺损和统计处理模型的不完善,特别是日射模型存在一定缺陷。     

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...     

广州西塔超高层玻璃幕墙选型的节能评价

以《公共建筑节能设计标准》为设计依据,根据西塔建筑特点对广州地区典型气象年数据中的室外气温和风速进行了修正。应用DeST软件,结合修正后的气象数据,分析了广州西塔传统单层玻璃幕墙和内呼吸双层通风幕墙的节能设计方案,根据能耗模拟结果对幕墙设计方案的静态投资回收期进行了估算。     

Developing future hourly weather files for studying the impact of climate change on building energy performance in Hong Kong

The concern on climate change leads to growing demand for minimization of energy use. As building is one of the largest energy consuming sectors, it is essential to study the impact of climate change on building energy performance. In this regard, building energy simulation software is a useful tool. A set of appropriate typical weather files is one of the key factors towards successful building energy simulation. This paper reports the work of developing a set of weather data files for subtropical Hong Kong, taking into the effect of future climate change. Projected monthly mean climate changes from a selected General Circulation Model for three future periods under two emission scenarios were integrated into an existing typical meteorological year weather file by a morphing method. Through this work, six sets of future weather files for subtropical Hong Kong were produced. A typical office building and a residential flat were modeled using building simulation program EnergyPlus. Hourly building energy simulations were carried out. The simulated results indicate that there will be substantial increase in A/C energy consumption under the impact of future climate change, ranging from 2.6% to 14.3% and from 3.7% to 24% for office building and residential flat, respectively.     

Quantifying the impact of building envelope condition on energy use

ABSTRACT

The gap between the architectural information and the as-is building condition has been known as one of the pivotal factors influencing deviations between actual and predicted building energy consumption. Despite such significance, quantifying the impact of deviated building information on energy use has not been fully investigated. This paper explores building information modelling (BIM)-driven experimental simulation to quantify the impact of building envelope condition on energy use, which can infer the impact of reflecting the as-is building conditions in as-designed BIMs on the reliability of energy analysis. First, BIM-driven energy simulations are conducted with varied thermo-physical properties of building envelope elements in gbXML-based BIMs under different climate conditions. Building upon the impacting factor for energy analysis (IFEA), the simulation results are then used to infer the impact of the deviated building condition on energy consumption. Through case studies, it is observed that the annual energy consumption of a residential building can deviate by 18–20%, whereas thermal resistances of exterior walls can deviate by 1?m²K/W. This paper validates quantitatively the potential benefits of reflecting the as-is building condition in BIM-based energy performance analysis. This provides practitioners with insights into how to improve the reliability of energy analysis of existing buildings.     

Quantification of model form uncertainty in the calculation of solar diffuse irradiation on inclined surfaces for building energy simulation

Traditional uncertainty quantification (UQ) in the prediction of building energy consumption has been limited to the propagation of uncertainties in model input parameters. Models by definition ignore, at least to some degree, and, in almost all cases, simplify the physical processes that govern the reality of interest, thereby introducing additional uncertainty in model predictions that cannot be captured as input parameter uncertainty. Quantification of this type of uncertainty (which we will refer to as model form uncertainty) is a necessary step towards the complete UQ of model predictions. This paper introduces a general framework for model form UQ and shows its application to the widely used sky irradiation model developed by Perez et al. [1990. “Modeling Daylight Availability and Irradiance Components from Direct and Global Irradiance.” Solar Energy 44 (5): 271–289], which computes solar diffuse irradiation on inclined surfaces. We collected a data set of one-year measurements of solar irradiation at one location in the USA. The measurements were done at surfaces with different tilt angles and orientations, for a wide spectrum of sky conditions. A statistical analysis using both this data set and published studies worldwide suggests that the Perez model performs non-uniformly across different locations and produces a certain bias in its predictions. Based on the same data, we then use a two-phase regression model to express model form uncertainty in the use of the Perez model at this particular location. Using a holdout validation test, we demonstrate that the two-phase regression model considerably reduces the model bias errors and root mean square errors for every tilted surface. Lastly, we discuss the significance of including model form uncertainty in the energy consumption predictions obtained with whole building simulation.     

An evaluation of the embedment of a Radio Frequency Integrated Circuit with a temperature detector in building envelopes for energy conservation

Concrete is the primary material for building envelopes in some parts of the world, and its ability to store heat as well as its dynamic temperature changes will not only affect the deterioration rate of the exterior wall but will also greatly influence the energy efficiency of interior air conditioning. There are many methods for measuring the inner temperature of concrete, but they often have limitations, such as indirect estimation, cable installation requirements, high cost, or heterogeneity of the sample structure. In order to measure the internal temperature of concrete, this study integrated a Radio Frequency Integrated Circuit (RFIC) with a temperature sensor chip and embedded the device in concrete structures. A Smart Temperature Information Material (STIM) was thus developed. This device overcomes the aforementioned constraints, allows direct measurement and wireless transmission, and is able to constantly monitor temperature changes from a distance. The experiment embedded STIM into 5 concrete specimens that simulated rooftop insulation (50 cm × 50 cm × 15 cm) to measure the thermal performance of each insulation material, and the effect of weather conditions and the heat release/absorption rates on the thermal performance. The results of the study can be used as a reference for selecting materials for building design or maintenance and analysis of the energy efficiency of building envelopes.     

Numerical evaluation of wind effects on a tall steel building by CFD

A comprehensive numerical study of wind effects on the Commonwealth Advisory Aeronautical Council (CAARC) standard tall building is presented in this paper. The techniques of Computational Fluid Dynamics (CFD), such as Large Eddy Simulation (LES), Reynolds Averaged Navier-Stokes Equations (RANS) Model etc., were adopted in this study to predict wind loads on and wind flows around the building. The main objective of this study is to explore an effective and reliable approach for evaluation of wind effects on tall buildings by CFD techniques. The computed results were compared with extensive experimental data which were obtained at seven wind tunnels. The reasons to cause the discrepancies of the numerical predictions and experimental results were identified and discussed. It was found through the comparison that the LES with a dynamic subgrid-scale (SGS) model can give satisfactory predictions for mean and dynamic wind loads on the tall building, while the RANS model with modifications can yield encouraging results in most cases and has the advantage of providing rapid solutions. Furthermore, it was observed that typical features of the flow fields around such a surface-mounted bluff body standing in atmospheric boundary layers can be captured numerically. It was found that the velocity profile of the approaching wind flow mainly influences the mean pressure coefficients on the building and the incident turbulence intensity profile has a significant effect on the fluctuating wind forces. Therefore, it is necessary to correctly simulate both the incident wind velocity profile and turbulence intensity profile in CFD computations to accurately predict wind effects on tall buildings. The recommended CFD techniques and associated numerical treatments provide an effective way for designers to assess wind effects on a tall building and the need for a detailed wind tunnel test.