合川文化艺术中心剧场负荷分析与气流组织设计

通过对合川文化艺术中心剧场冷负荷的计算及分析,笔者认为在剧场等间歇性使用且人员密集场所的大空间公共建筑中,构成空调冷负荷的主要部分是人体发热及新风负荷;因此在空调系统的使用过程中,应根据人员密度的变化来调节系统的运行,达到节能的目的。在气流组织设计时,宜选用倾角可调的喷口来满足冬、夏工况的使用要求。     

办公建筑内部负荷扰量特性与计算方法

随着建筑围护结构保温性能的逐步提高,以室内人员为代表的内部因素已成为影响建筑负荷的重要不确定性因素,内部负荷扰量(简称内扰)在空调负荷设计中的重要性需要被强调。通过对两栋办公建筑的实地测试发现,办公建筑中人员在室率普遍只有设计人数的40%～60%,设备的实际功率也远低于20 W/m~2的概算指标,过大的经验值是造成机组选型偏大的重要原因。重新思考标准中的人员密度系数和设备使用密度系数,以人为核心将建筑内扰负荷结合起来,提出"代表人"的内扰负荷计算方法,并对案例建筑的负荷设计进行修正。相比最大实测冷负荷,修正后的设计冷负荷富余率均在10%以内。     

Computational intelligence techniques for HVAC systems: A review

Buildings are responsible for 40% of global energy use and contribute towards 30% of the total CO2 emissions. The drive to reduce energy use and associated greenhouse gas emissions from buildings has acted as a catalyst in the development of advanced computational methods for energy efficient design, management and control of buildings and systems. Heating, ventilation and air-conditioning (HVAC) systems are the major source of energy consumption in buildings and ideal candidates for substantial reductions in energy demand. Significant advances have been made in the past decades on the application of computational intelligence (CI) techniques for HVAC design, control, management, optimization, and fault detection and diagnosis. This article presents a comprehensive and critical review on the theory and applications of CI techniques for prediction, optimization, control and diagnosis of HVAC systems. The analysis of trends reveals that the minimisation of energy consumption was the key optimization objective in the reviewed research, closely followed by the optimization of thermal comfort, indoor air quality and occupant preferences. Hardcoded Matlab program was the most widely used simulation tool, followed by TRNSYS, EnergyPlus, DOE-2, HVACSim+ and ESP-r. Metaheuristic algorithms were the preferred CI method for solving HVAC related problems and in particular genetic algorithms were applied in most of the studies. Despite the low number of studies focussing on multi-agent systems (MAS), as compared to the other CI techniques, interest in the technique is increasing due to their ability of dividing and conquering an HVAC optimization problem with enhanced overall performance. The paper also identifies prospective future advancements and research directions.     

高层建筑暖通空调设计和建筑优化及故障检测与室内空气品质、节能和全球环境问题的协调

高层建筑内包容了众多的人员和发热设备，因此不合理的设计和运行将对室内人员的健康和舒适、经济性和能耗、全球环境等产生重大的影响。从工程实际和基本原理上探讨了暖通空调广泛领域内将遇到的一些重要课题，以实现协调这些方面要求的最优的暖通空调系统。     

Building signatures: A holistic approach to the evaluation of heating and cooling concepts

A sustainable and environmentally responsible building concept aims at a high workplace comfort, a significantly reduced heating and cooling demand, a high-efficient plant system, and the use of renewable energy sources to condition the built environment. This paper presents a comprehensive analysis of the heating and cooling concepts of 11 low-energy buildings in terms of energy use, efficiency and occupant thermal comfort. All buildings investigated employ environmental energy sources and sinks – such as the ground, ground water, rainwater and the ambient air – in combination with thermo-active building systems. A limited primary energy use of about 100 kWh_prim/(m²_neta) as a target for the complete building service technology (HVAC and lighting) was postulated for all buildings presented. With respect to this premise, a comprehensive long-term monitoring in high time resolution was carried out for two to five years, with an accompanying commissioning of the building performance. Measurements include the useful heating and cooling energy use, auxiliary energy use for the hydraulic system, as well as end and primary energy use, occupant thermal comfort and local meteorological conditions. A new methodology is proposed for a holistic approach to the evaluation of heating and cooling concepts, which not only considers the occupants thermal comfort, but also the useful energy consumption and the efficiency of the generation, distribution and delivery of heating and cooling energy.     

某大型空调系统能耗分析

能源问题是决定我国能否可持续发展的关键因素之一。对某大型空调系统能耗进行了测试和分析，表明冷机实际COP低于其额定COP，并且空调箱能耗占到30％-50％；另外，对系统的负荷分析表明，造成系统的供需比下降的主要原因是该系统设计本身所造成。因此，对空调系统优化运行是节能改造必不可少的一个环节；同时，如何优化空调系统各级的设定参数以及系统的划分，将会从根本上提高系统冷负荷的供需比，从而大大减少系统能耗，可为大型空调系统的运行人员、设计人员提供参考。     

An analysis of stochastic properties of room temperature, cooling load and air-conditioning systems

Exact prediction of the heating and cooling load, proper sizing of the HVAC systems and the optimal control of the HVAC systems are essential to minimize energy consumption. Since external climates which are the main factors affecting cooling loads fluctuate randomly, calculation of the cooling load must take account of the stochastic nature of these processes.

This paper proposes methods of thermal calculation which give the density function of the HVAC system load considering the stochastic properties of the external climates. Simple HVAC systems are analysed for illustration of the applicability of these methods to many practical problems.     

基于人行为影响的住区建筑多主体集成能耗模型

在城市建筑节能研究中,政府常常依赖城市能源与碳排放模型工具制定并评估节能策略。而当前的城市建筑能耗模型受限于开发技术等因素,尚存在诸多不足,例如,考虑人行为对建筑能耗的影响,建立行为、日常活动及与环境相关的综合能耗模型。关于此类模型合理的数学形式、参数选择的方法以及不同行为的模拟方式等问题还尚待进一步研究。采用多主体(Multi-Agent)建模技术,设计集成建筑能耗模型,以住区中的居民作为模型中活动的主体,模拟使用者行为习惯、活动对建筑能耗的影响;采用ISO 13790标准模拟建筑的供热和降温需求,并在集成环境中设计统一的描述框架,以相对独立的环境模拟、行为模拟模块形式进行交互,实现热环境模拟和基于主体活动的设备能耗模拟的有机结合。研究表明,住区居民的用能行为是影响城市建筑能耗密度变化的重要因素,实现对住区主体行为特征的引导是实现城市建筑节能目标的有效途径。     

The power of qualitative data in post-occupancy evaluations of residential high-rise buildings

Using a mixed-method, case study research design, the present study explores four Toronto high-rise residential buildings in order to produce feedback about how occupants experience and behave in these buildings. The primary dataset is 700 comments received on 165 questionnaires. Content analysis was performed on the data, identifying envelope, heating, cooling and ventilation (HVAC), hot water, indoor environmental quality, and layout and design as the primary themes. The comments revealed important feedback for the designers and managers of these buildings; including important insights into the HVAC system, envelope, balcony, hot water delivery system, and noise control strategies. Though subjective in nature, the comments received from occupants are revelatory and have implications for the amount of energy consumed by the buildings, as well as the level of occupant satisfaction. Though not a substitute for quantitative problem solving, they are a complimentary strategy in the pursuit to improve the satisfaction and sustainability of the built environment.     

基于建筑全年动态冷负荷的冷水机组优化配置方案

提出一种在设计阶段对冷水机组方案进行优化配置的方法.首先,冷水机组的能耗计算简化为制冷机的实际制冷量和冷却水进口温度两个独立变量的函数.进一步,通过建筑动态负荷计算获得全年冷负荷频率特性以及相应的室外湿球温度分布,其中湿球温度决定了冷却水最低进口温度.最终,计算出各种冷水机组配置方案的全年以及不同冷负荷需求工况下的运行电耗,并得出最优化的节能方案.     

商务办公楼的负荷计算与变压器配置

从商务办公楼的冷源、照明、电梯、景观照明等负荷的特点入手,结合用电量统计数据及变压器的特性．对商务办公楼的负荷计算、变压器损耗进行分析．得出变压器在不影响运行可靠性的情况下采用大容量少台数比小容量多台数节能的结论．同时给出商务办公楼负荷计算相关系数取值及变压器配置的一些建议。     

厦门农村住宅用能状况与建筑能耗模拟分析

以厦门农村住宅为调查研究的对象,采取实地调研和计算机模拟相结合的方法,根据农宅住户实际用电特征将厦门农村住宅分为6种基本类型,从中归纳出3种不同的空间原型作为计算机模拟的模型,通过De ST-h模拟软件进行能耗模拟,得出典型农村住宅基本能耗,分析其建筑能耗的特点。结果表明,农宅的用能方式导致不同的建筑形态其能耗也不同,通过典型气象年的运算发现,空调冷负荷在建筑总能耗中占比最大,3种计算模式的空调开启时间和运行时间均不同,3种计算模型的空调能耗占比分别是81.5%、84.6%、96.8%。     

基于DeST的夏热冬冷地区居住建筑人行为能耗模拟验证

为验证DeST人行为仿真建筑能耗模拟软件计算结果的准确性,在夏热冬冷地区开展了居民采暖及制冷的空调用能行为实测,将调研得到的居民用能行为参数及建筑围护结构信息代入到DeST人行为模拟软件中进行计算。将计算结果与实测空调能耗进行对比后,结果显示,原始软件制冷能耗平均绝对计算误差为37.9%;制热能耗平均绝对计算误差为128.2%。与原始软件相比,DeST人行为模拟软件制冷能耗计算误差减少了13.8%,采暖能耗计算误差减少了94.1%。人行为能耗模拟软件的计算结果更接近实测值,空调全年运行时长、启停概率与实测结果符合性也较好。嵌入人行为模块后的DeST将为模拟实际运行状况下建筑的能耗提供很好的计算平台。     

Probabilistic assessment of the occupant load density in retail buildings

The occupant load density is a crucial parameter for the design of the means of egress in buildings. In retail buildings the occupant load density is highly influenced by the individual׳s choice and the necessity of a person to visit the store. This causes a high variability of the occupant load density in time. An accurate representation of this variability will provide a basis for enhancing fire safety design. In this paper, a probabilistic approach is used to describe the variability of the occupant load density over a year, based on long-term data of customer frequencies in combination with methods from the queuing theory the distribution of the occupant load density is derived for four different types of retail chains. It is shown that the type of a retail chain has a large influence on the distribution of the occupant load density and that the exceedance probability of current design values in different standards is very small. A method is proposed to derive design values for a performance based design on the basis of probabilistic models for the occupant load density. In addition, the developed probabilistic models describing the number of occupants in a store, allow the assessment of the occupant load density for other types of retail chains, even with incomplete data.     

夏热冬冷地区办公建筑降低供暖空调能耗的技术路径

以上海地区某办公建筑为例,基于EnergyPlus能耗模拟,探讨了围护结构性能提升和暖通空调系统优化这2条节能技术路径对夏热冬冷地区办公建筑降低供暖空调全年能耗的有效性.结果 表明:围护结构性能提升的节能潜力较小,经济性较差;单纯提高围护结构保温隔热性能并不能保证降低建筑年耗冷量,应综合分析全年供热供冷能耗确定围护结构...     

居住建筑能耗预测分析方法的研究

本文通过正交实验设计、DeST建筑能耗软件模拟及多元线性回归方法,研究了影响居住建筑能耗的主要建筑设计因素,得到了重庆市居住建筑冷、热负荷及全年负荷的预测方程,并进行了误差分析。通过预测方程和模拟软件分别计算所得结果的对比分析,验证了该方程的可靠性,为重庆市居住建筑能耗预测分析提供了一种简便适用的方法。利用可靠的预测方程,可以快速而简单地评价分析不同设计方法和围护结构方式对建筑能耗的影响。     

Modeling occupancy and behavior for better building design and operation—A critical review

People spend more than 90% of their life time in buildings, which makes occupant behavior one of the leading influences of energy consumption in buildings. Occupancy and occupant behavior, which refer to human presence inside buildings and their active interactions with various building system such as lighting, heating, cooling, ventilation, window blinds, and plugs, attract great attention of research with regard to better building design and operation. Due to the stochastic nature of occupant behavior, prior occupancy models vary dramatically in terms of data sampling, spatial and temporal resolution. This paper provides a comprehensive review of the current modeling efforts of occupant behavior, summarizes occupancy models for various applications including building energy performance analysis, building architectural and engineering design, intelligent building operations and building safety design, and presents challenges and areas where future research could be undertaken. In addition, modeling requirement for different applications is analyzed. Furthermore, a few commonly used statistical and data mining models are presented. The purpose of this paper is to provide a modeling reference for future researchers so that a proper method or model can be selected for a specific research purpose.     

Lighting energy consumption in ultra-low energy buildings: Using a simulation and measurement methodology to model occupant behavior and lighting controls

As building owners, designers, and operators aim to achieve significant reductions in overall energy consumption, understanding and evaluating the probable impacts of occupant behavior becomes a critical component of a holistic energy conservation strategy. This becomes significantly more pronounced in ultra-efficient buildings, where system loads such as heating, cooling, lighting, and ventilation are reduced or eliminated through high-performance building design and where occupant behavior-driven impacts reflect a large portion of end-use energy. Further, variation in behavior patterns can substantially impact the persistence of any performance gains. This paper describes a methodology of building occupant behavior modeling using simulation methods developed by the Building Energy Research Center (BERC) at Tsinghua University using measured energy consumption data collected by the University of Washington Integrated Design Lab (UW IDL). The Bullitt Center, a six-story 4831 m² (52,000 ft²) net-positive-energy urban office building in Seattle, WA, USA, is one of the most energy-efficient buildings in the world (2013 WAN Sustainable Building of the Year Winner). Its measured energy consumption in 2015 was approximately 34.8 kWh/(m²?yr) (11 kBtu/(ft²?yr)). Occupant behavior exerts an out-sized influence on the energy performance of the building. Nearly 33% of the end-use energy consumption at the Bullitt Center consists of unregulated miscellaneous electrical loads (plug-loads), which are directly attributable to occupant behavior and equipment procurement choices. Approximately 16% of end-use energy is attributable to electric lighting which is also largely determined by occupant behavior. Key to the building’s energy efficiency is employment of lighting controls and daylighting strategies to minimize the lighting load. This paper uses measured energy use in a 330 m² (3550 ft²) open office space in this building to inform occupant profiles that are then modified to create four scenarios to model the impact of behavior on lighting use. By using measured energy consumption and an energy model to simulate the energy performance of this space, this paper evaluates the potential energy savings based on different occupant behavior. This paper describes occupant behavior simulation methods and evaluates them using a robust dataset of 15 minute interval sub-metered energy consumption data. Lighting control strategies are compared via simulation results, in order to achieve the best match between occupant schedules, controls, and energy savings. Using these findings, we propose a simulation methodology that incorporates measured energy use data to generate occupant schedules and control schemes with the ultimate aim of using simulation results to evaluate energy saving measures that target occupant behavior.     

The effect of occupancy and building characteristics on energy use for space and water heating in Dutch residential stock

As a consequence of the improved quality of thermal properties of buildings due to energy regulations, overall energy use associated with building characteristics is decreasing, making the role of the occupant more important. Studies have shown that occupant behaviour might play a prominent role in the variation in energy consumption in different households but the extent of such influence is unknown. The impact of the building's thermal characteristics on space heating demand has been well studied. There is however, little work done that incorporates the impact of consumer behaviour. This study aims to gain greater insight into the effect of occupant behaviour on energy consumption for space heating by determining its effect on the variation of energy consumption in dwellings while controlling for building characteristics. The KWR database from the Ministry of Housing in the Netherlands was used. This study showed that occupant characteristics and behaviour significantly affect energy use (4.2%), but building characteristics still determine a large part of the energy use in a dwelling (42%). Further analysis showed that some occupant behaviour is determined by the type of dwelling or HVAC systems and, therefore, the effect of occupant characteristics might be larger than expected, since these determine the type of dwelling.