Kernel regression for real-time building energy analysis

This study proposes a new technique for real-time building energy modelling and event detection using kernel regression. We show that this technique can exceed the performance of conventional neural network algorithms, and do so by a large margin when the available training dataset is small. Furthermore, unlike the synapse weights in a neural network, the parameters of our kernel regression models are amenable to human interpretation and can give useful information about the building being studied. We extensively test our proposed algorithms using a new dataset consisting of 1.5 years of power and environmental measurements for four buildings, in addition to benchmarking against the ASHRAE Predictor Shootout dataset. On the new dataset, our kernel regression algorithm gave the best prediction performance in three of four cases and significantly outperformed neural networks (the nearest competitor) with training sets of 1/2 a year or less.     

Uncertainty and sensitivity decomposition of building energy models

As building energy modelling becomes more sophisticated, the amount of user input and the number of parameters used to define the models continue to grow. There are numerous sources of uncertainty in these parameters, especially when the modelling process is being performed before construction and commissioning. Past efforts to perform sensitivity and uncertainty analysis have focused on tens of parameters, while in this work, we increase the size of analysis by two orders of magnitude (by studying the influence of about 1000 parameters). We extend traditional sensitivity analysis in order to decompose the pathway as uncertainty flows through the dynamics, which identifies which internal or intermediate processes transmit the most uncertainty to the final output. We present these results as a method that is applicable to many different modelling tools, and demonstrate its applicability on an example EnergyPlus model.     

Uncertainty quantification of microclimate variables in building energy models

The last decade has seen a surge in the need for uncertainty analysis (UA) for building energy assessment. The rigorous determination of uncertainty in model parameters is a vital but often overlooked part of UA. To undertake this, one has to turn one's attention to a thriving area in engineering statistics that focuses on uncertainty quantification (UQ) for short. This paper applies dedicated methods and theories that are emerging in this area of statistics to the field of building energy models, and specifically to the microclimate variables embedded in them. We argue that knowing the uncertainty in these variables is a vital prerequisite for ensuing UA of whole building behaviour. Indeed, significant discrepancies have been observed between the predicted and measured state variables of building microclimates. This paper uses a set of approaches from the growing UQ arsenal, mostly regression-based methods, to develop statistical models that quantify the uncertainties in the following most significant microclimate variables: local temperature, wind speed, wind pressure and solar irradiation. These are the microclimate variables used by building energy models to define boundary conditions that encapsulate the interaction of the building with the surrounding physical environment. Although our analysis is generically applicable to any of the current energy models, we will base our UQ examples on the energy model used in EnergyPlus.     

建筑全能耗分析软件EnergyPlus及其应用

介绍了新一代建筑全能耗分析软件EnergyPlus的基本原理、特点和新功能及其与DOE-2的比较,并将其应用于某一实际的建筑冷热电联产系统的模拟,根据模拟结果对整个系统进行了全年能耗和经济性分析。     

浅谈建筑节能设计与改造

结合西安地区节能建筑设计的现状与竣工验收中发现的节能施工方面的问题,简述了新建建筑物的节能设计与原有建筑物的改造措施,对节能建筑、绿色建筑及生态建筑设计与改造具有积极的促进作用。     

上海市某商用建筑能耗分析与节能评估

采用能耗模拟软件eQUEST对上海市某商用建筑建立模型,对模型进行校正之后计算出该建筑的能耗情况,在此基础上提出6项节能措施,并分析了其节能效果,验证了计算机模拟技术在建筑能耗分析和节能评估中的适用性。     

多功能商业建筑能耗系统优化与节能分析

以美国德州农工大学(Texas A&M University)Reed McDonld大楼为例,介绍了建筑能耗系统的优化方法及分区控制室内环境的技术手段.详细介绍了在其能耗系统优化过程中所发现的问题、相应的解决方案及节能效果.     

建筑节能对建筑设计发展的影响分析

随着人类社会的高度发展,人类生活的各个方面对能源都有着巨大的需求,然而由于常规能源的不可再生以及地理分布不均,导致全球能源竞争日趋加剧,这就要求我们在各个行业都要采取节能措施,减少能源消耗,在建筑行业尤其重要.近年来,由于建筑节能的现实需要以及迅速的发展,促进了建筑各个领域的发展,建筑设计也在节能发展的促进下表现出蓬勃生机,新技术层出不穷,新的产品也不断涌现.本文就此描述了建筑节能对建筑设计行业的深刻影响与促进.     

居住建筑节能计算分析

阐述了建筑节能的发展现状,分析了节能计算中几个重要的节能控制参数,并结合工程实例进行了节能计算,验证了节能控制参数对建筑节能的影响,从而达到以最经济的手段提高建筑物节能效率的目的。     

建筑节能技术的发展

本文介绍了外墙保温技术、节能窗技术、屋顶节能技术和采暖计量与控制技术     

Whole building energy simulation and energy saving potential analysis of a large public building

This article explores how to use EnergyPlus to construct models to accurately simulate complex building systems as well as the inter-relationships among sub-systems such as heating, ventilation and air conditioning (HVAC), lighting and service hot water systems. The energy consumption and cost of a large public building are simulated and calculated for Leadership in Energy and Environmental Design (LEED) certification using EnergyPlus. American Society of Heating, Refrigerating and Air Conditioning Engineers (ASHRAE) baseline model is constructed according to ASHRAE 90.1 standard and the comparison of annual energy consumption between ASHRAE baseline model and proposed model is carried out. Moreover, an energy efficiency (EE) model is built based on the design model. Meanwhile, other energy conservation measures (ECMs) such as daylighting dimming and occupant sensors are considered. The simulation results show 4.7% electricity consumption decrease but 6.9% gas consumption increase of the EE model compared to ASHRAE baseline model. In summary, the annual energy cost of the EE model is reduced by 7.75%.     

Global sensitivity analysis of England's housing energy model

Housing energy models support informed decision-making for energy efficiency and CO₂ reduction strategies. However, they are subject to multiple sources of uncertainty. Previous studies have analysed uncertainties using a local one-at-a-time approach, but this suffers from significant limitations. Here two global sensitivity analysis techniques, elementary effects and a variance-based method, have been employed to overcome these limitations. Correct understanding of model sensitivities matters, for interpreting findings and directing research to reduce uncertainties. Analysis of the Cambridge Housing Model, a Standard Assessment Procedure (SAP)-based housing energy model for England, finds good agreement between the global analyses but there are major differences compared with the local analysis. We identify SAP wall U-values and demand temperature as by far the most significant uncertain parameters; along with SAP roof, window and floor U-values these account for 96% of the observed variation in outputs. This could have major implications for national-level estimates of savings based on such models.     

陕南地区居住建筑节能潜力分析

本文在对汉中市的居住建筑能耗现状调研的基础上,对当地的建筑居住建筑节能潜力进行分析和展望,对该地今后的建筑节能设计有较大参考作用.     

A review of bottom-up building stock models for energy consumption in the residential sector

Efficient and rational implementation of building stock CO₂ emission reduction strategies and policies requires the application of comprehensive building stock models that have the ability to: (a) estimate the baseline energy demand of the existing building stock, (b) explore the technical and economic effects of different CO₂ emission reduction strategies over time, including the impact of new technologies, and (c) to identify the effect of emission reduction strategies on indoor environmental quality.     

建筑热工设计对建筑节能的要求

影响建筑节能设计的因素很多,如用地因素、墙体因素、窗户因素、屋顶因素等。通过对其影响因素的分析．指出了建筑热工设计对建筑节能的要求。     

湘潭某公共建筑能耗现状及节能分析

通过对湘潭市某公共建筑能耗状况、空调系统运行管理状况和室内空气品质的调查研究,分析了该建筑室内空气品质较差和运行不节能的原因,并提出了相应的改进措施,为公共建筑的节能工作提供了参考借鉴。     

节能建筑室内热环境分析——以新疆首座超低能耗建筑为例

通过对新疆首座超低能耗示范建筑的实地测试与分析,得出该节能示范建筑的室内热环境和建筑能耗状况。并根据室内热舒适度及能耗状况,对该建筑中所使用的相关节能技术在新疆地区的适宜性作出分析,为节能建筑在新疆的发展提出建议。     

大卖场建筑节能浅析

分析了做好大卖场节能工作的重要性,结合大卖场的耗能方式,就大卖场如何节能进行了分析,阐述了具体的节能措施,重点提出了空调设置应做好的几项工作,以搞好大卖场的节能工作。     

建立适应建筑节能的暖通空调设计机制

列举了我国设计机制不适应建筑节能需求的现象。提出了在规划设计中应用综合资源规划(IRP)方法、建立各专业参与的会商制度、将建筑模拟技术用于设计阶段的能耗权衡、建立全程优化调整机制,以及采用基于性能的设计合同等方法,以进一步提高我国暖通空调节能设计水平。     

建筑节能中能耗节约份额的分析

指出建筑节能的目标是减少采暖耗煤量,节煤量应由建筑物和供热系统共同承担,通过对耗热量指标进行的分析,得出建筑物和供热系统在节能50%中承担的节能比例,并指出第三步节能的重点是对建筑的节能。