城市节能的关键性能指标

根据中国城市能耗特点,提出将城市能耗分为生产性能耗和消费性能耗两大类型。指出生产性能耗主要用效率指标来评价;消费性能耗应尽量用实物量指标来评价,也就是用量化的强度性指标EUI(energy use intensity)评价,实现评价指标的可测量、可核查、可报告。即使采用相对性指标(如百分比指标),也一定要有明确的基准线。提出了城市生产性能耗、消费性能耗以及城市能源系统的关键性能指标。     

区域建筑能源需求预测基准模型的构建——以深圳市公共建筑为例

根据深圳市公共建筑能耗敏感因子分析结果,采用统计分析法、情景分析法和模拟分析法建立了区域建筑能源规划中酒店类、办公类及商业类典型建筑模型。以商业类建筑为例,详细叙述了典型建筑模型的建立过程,并以实测逐月能耗数据对典型建筑模型进行了校准,用校准后的建筑能耗基准模型进行了区域建筑能源需求预测。结果表明,办公、商业、酒店类建筑能耗基准模型的能耗预测值与实测值的月误差、年误差和均方差变异系数均满足误差标准要求,该方法可用于在区域层面进行办公、商业、酒店类公共建筑能源需求预测。     

基于聚类分析的酒店建筑分类与用能评价

根据建筑能耗影响因素的特性来进行类别划分是客观、科学地评价建筑用能水平的前提。以酒店建筑为例,从多个建筑能耗影响因素中选取23个参数引入评价指标体系中,应用主成分分析方法对指标体系进行降维处理,并采用聚类分析法将酒店建筑样本群划分为三类,最后对各类建筑的用能水平进行综合分析和评价。按照新的分类方法,每一类酒店都代表了各自的特点,与传统按星级分类相比,该方法反映酒店总体特性的参数更趋近一致,按照此分类进行的能耗基准评价将更具代表性,能够更好地引导酒店建筑节能诊断和用能管理,也为其他类型建筑的类型细化和用能评价提供方法指导。     

西安酒店建筑能耗调查与节能潜力分析

课题组对西安市数十栋酒店建筑进行能耗调查,获得2009年—2011年全年耗电量、耗气量、耗水量统计数据。引用能质系数计算方法,将所有的终端能源按一定折算系数转化为电。以总耗电量表示建筑能耗量,以单位面积建筑能耗作为标准。针对室内环境参数测试值分析室内环境质量。分析总结酒店建筑能耗现状:普遍存在的问题,亟待改善的问题,并分析节能潜力。     

建筑能耗模拟在能源审计中的应用

以某大厦为例,阐述了建筑能耗模拟时的模型校验方法,并利用经过校验的模型进行了能耗预测和节能量计算.指出在进行能源审计时,必须用实际的建筑资料和历史能耗数据对所建模型进行校验,只有经过实测能耗数据校验的模型才能对建筑能耗进行准确预测;通过能耗模拟进行能耗预测和节能量计算,可以节省大量的时间,且更加准确、直观,具有很好的应用前景.     

基于建筑能源需求的光伏供能配置研究——以延庆山区某酒店建筑为例

以延庆山区某酒店建筑为例,研究了基于建筑能源需求的光伏系统供能配置.针对案例建筑的用能特点,建立了能耗模型,分析了用能强度及峰谷分布.综合考虑了建设用地、山地环境及建筑用能特点,采用光伏系统作为可再生能源产能系统,分别以建筑用能淡季峰值负荷、淡季谷值负荷、旺季峰值负荷、旺季谷值负荷作为基准选配光伏系统装机容量,根据投资...     

西安市大型酒店建筑能耗调查

对西安市多家大型酒店进行了调研,获得酒店建筑实际运行中的建筑能耗值,并通过对比多家酒店能耗信息,分析了西安市大型酒店建筑的能源构成、能耗状况及用能特点,提出了酒店建筑能源管理和设备运行中的问题,以及相应的节能措施。     

基于某房地产公司的建筑能耗分析

以某大型房地产公司所建的酒店和住宅作为研究对象,研究了建筑能耗的影响因素及各影响因素之间的多重共线性问题。采用偏最小二乘回归法拟合了各能耗影响因素与能耗密度EUI之间的线性关系,并给出建筑累积概率相对于能耗比率的分布情况,作为评价建筑能耗的有力参考依据,对以后建筑固有特性参数设计、固有耗能参数设计、能耗管理系统设计提供量化依据。     

一种用于建筑负荷预测的动态修正方法及其在综合能源规划中的应用

通过对典型建筑特性的研究,提出一种适用于综合能源方案规划阶段的冷热电负荷预测方法。该方法通过动态参数化建模的典型建筑模型,以EnergyPlus(一款建筑能耗模拟软件)为计算基础,根据项目地点、建筑外形、室内设计参数、围护结构等关键参数进行动态修正后,实现建筑负荷的预测,该方法具有更好的准确性和普适性。根据此方法开发出的计算软件,在某实际工程的规划中进行了验证,应用结果证实了该方法的实用性和准确性。     

基于情景分析法的昆明市能源消费需求研究

本文以预测昆明市2020年的能源消费总量为精确化问题,以昆明市能源状况为中心,从能源生产和能源消费两个视角为切入点,指出能源产品对外依存度较高;工业部门仍是我市能源消费的主要部门,高速的经济增长是以相应的能源消费增速支撑实现的。通过拟合以经济总量、产业结构和人口总量为自变量,能源消费总量为因变量的回归方程;采用情景分析法,设定基准、中等和高等三种情景,预测昆明市2020年的能源消费总量。在能满足昆明市发展低碳经济的前提下,得出结论,建议昆明市"十三五"期间,GDP能耗目标降低率为8%~12%。     

A decision tree method for building energy demand modeling

This paper reports the development of a building energy demand predictive model based on the decision tree method. This method is able to classify and predict categorical variables: its competitive advantage over other widely used modeling techniques, such as regression method and ANN method, lies in the ability to generate accurate predictive models with interpretable flowchart-like tree structures that enable users to quickly extract useful information. To demonstrate its applicability, the method is applied to estimate residential building energy performance indexes by modeling building energy use intensity (EUI) levels. The results demonstrate that the use of decision tree method can classify and predict building energy demand levels accurately (93% for training data and 92% for test data), identify and rank significant factors of building EUI automatically. The method can provide the combination of significant factors as well as the threshold values that will lead to high building energy performance. Moreover, the average EUI value of data records in each classified data subsets can be used for reference when performing prediction. One crucial benefit is improving building energy performance and reducing energy consumption. Another advantage of this methodology is that it can be utilized by users without requiring much computation knowledge.     

A study on energy performance of hotel buildings in Singapore

This paper presents a study on energy performance of Singapore's hotel buildings. Energy consumption data and other pertinent information were collected from 29 quality hotels through a national survey. Building features and operational characteristics contributing to the variations in hotel energy performance were discussed. The annual average total energy use intensity (EUI) in these hotels is 427 kWh/m². Electricity and gas are used in all sampled hotels, and some hotels also use diesel to power standby generator or hot water boiler. We also investigated relationships between electricity consumption and number of occupied rooms in individual hotels; the weak correlations found indicate it is necessary to improve energy management when occupancy rate is low. Besides, Pearson correlations between hotel energy use intensity and possible explanatory indicators revealed that three-star hotels differ from high class establishments in energy use. Worker density and years after the last major energy retrofit were also found to be highly correlated to hotel building energy use intensity. Also discussed in this paper is the effect of weather conditions on electricity consumption of the hotels.     

Analysis of a simplified calibration procedure for 18 design-phase building energy models

This paper evaluates the accuracy of 18 design-phase building energy models, built according to LEED Canada protocol, and investigates the effectiveness of model calibration steps to improve simulation predictions with respect to measured energy data. These calibration steps, applied in professional practice, included inputting actual weather data, adding unregulated loads, revising plug loads (often with submetered data), and other simple updates. In sum, the design-phase energy models underpredicted the total measured energy consumption by 36%. Following the calibration steps, this error was reduced to a net 7% underprediction. For the monthly energy use intensity (EUI), the coefficient of variation of the root mean square error improved from 45% to 24%. Revising plug loads made the largest impact in these cases. This step increased the EUI by 15% median (32% mean) in the models. This impact far exceeded that of calibrating the weather data, even in a sensitivity test using extreme weather years.     

Determinants and benchmarking of resource consumption in hotels—Case study of Hilton International and Scandic in Europe

This paper reports on a study of resource consumption in 184 Hilton International and Scandic hotels in Europe. An overview of the characteristics of these two brands (upscale and mid-market, respectively), as well as the collective resource consumption in these hotels is presented (2004 data). This is followed by a more detailed analysis of a number of physical and operational factors that may potentially influence the energy and water use in these hotels. A multiple variable regression analysis indicated that, in the absence of climate data, hotel standard, total hotel floor area, number of guest-nights sold and number of food covers sold all affect the energy and water use in these facilities. The survey results further document significant differences in the energy- and water-utilisation in Hilton and Scandic hotels. This indicates that establishing realistic resource consumption benchmarks or models requires classifying hotels (especially those belonging to the upscale brand) into sufficiently specialised sub-groups representing facilities with comparable properties. It is further suggested that benchmarking of facility components may be necessary. The paper concludes with some recommendations on the procedure and criteria for establishing a useful reporting system and benchmarking model.     

A study of energy efficiency of private office buildings in Hong Kong

A benchmark study of the energy efficiency of private office buildings in Hong Kong was conducted in 2002 because energy efficiency was declining. In the study, private office buildings were divided into five user groups. For each group, a multiple regression model was developed to find the relationship between Energy Use Intensities (EUIs) and other factors, such as operating hours, for normalization and benchmarking purposes. In this paper we make use of the regression results to study the energy efficiency of private office buildings by different grades. In Hong Kong, office buildings are divided into three grades (A, B, and C) based on the quality of the facility, which is reflected in rental values; a Grade A office building denotes expensive luxury. We found that the EUI of Grade A office buildings is the highest, consuming over 50% of the total energy used in office buildings. Recently, the annual EUI of office buildings has improved even though Grade A floor space is increasing. This may be due to the promotion of the energy efficiency program launched in the last decade.     

Decoupling of building energy use and climate

Energy use intensity (EUI) and climate have a well documented correlation, which is generally applied in building energy management. Green buildings have sought to greatly reduce energy consumption and a number of examples are documented in the literature. A sample of high performance buildings constructed in a variety of global locations is analyzed here, and provides evidence that measures to reduce energy consumption have reduced EUI to the point where its correlation with heating degree days is no longer apparent. This result suggests that end-user behaviour is the next major hurdle in lowering the energy consumption of greener buildings.     

Energy efficiency benchmarks and the performance of LEED rated buildings for Information Technology facilities in Bangalore, India

This paper provides a summary of an energy benchmarking study that uses performance data of a sample of Information Technology facilities in Bangalore. Information provided by the sample of occupiers was used to develop an Energy Performance Index (EPI) and an Annual Average hourly Energy Performance Index (AAhEPI), which takes into account the variations in operation hours and days for these facilities. The EPI and AAhEPI were modelled to identify the factors that influence energy efficiency. Employment density, size of facility, operating hours per week, type of chiller and age of facility were found to be significant factors in regression models with EPI and AAhEPI as dependent variables. Employment density, size of facility and operating hours per week were standardised and used in a separate regression analysis. Parameter estimates from this regression were used to normalize the EPI and AAhEPI for variance in the independent variables. Three benchmark ranges - the bottom third, middle third and top third - were developed for the two normalised indices. The normalised EPI and AAhEPI of LEED rated building, which were also part of the sample, indicate that, on average, LEED rated buildings outperform the other buildings.     

重庆某酒店中央空调系统运行管理现状及能耗分析

通过对重庆某酒店中央空调系统最近几年能耗数据的调查和其运行管理现状分析，采用单位建筑面积平均一次能耗量对其进行能耗计算，并与国内、国外同类建筑的穹调耗能水平进行比较，获得该酒店的运行能耗水平。通过对该建筑的能耗水平评价并分析其能耗特点，指出了该酒店中央空调系统设计和运行管理的不合理因素，提出了相应的节能降耗措施。     

酒店软件产品服务清洁生产效绩评估体系研究

本文依据循环经济发展模式的绿色酒店评估体系框架原理,建立起绿色酒店数学表达式,其中将酒店环境质量作为硬件产品服务质量的获得,将酒店清洁生产效绩作为软件产品服务质量的获得,将能源消耗和对环境的影响破坏作为酒店的付出,将酒店的获得与付出的比值作为收益来反映酒店的绿色化程度。而后利用层次分析法建立起酒店软件产品服务清洁生产效绩评估指标体系、指标赋权,通过对酒店经济—能源—环境系统投入产出的分析和能耗寿命周期的分析,确定评估指标标准,并对国内有代表性的8家酒店软件产品服务清洁生产效绩进行试评估,评估方法可行。评估结果显示酒店之间效绩差距很大、整体落后,急需改进。     

探究夏热冬冷地区办公建筑面积对单位建筑面积能耗(EUI)的影响

以上海地区的气象参数作为夏热冬冷气候区的典型代表,提出"H/S——建筑形状系数"并作为建筑形状分类指标,对办公建筑分类建模,采用能耗模拟软件e QUEST进行能耗估算,并用SPSS软件做逐步线性回归分析,探究建筑总面积、建筑形态与单位建筑面积年能耗(EUI)之间的数学关系。研究表明:1单位建筑面积能耗(EUI)随建筑总面积的增加而减少。2总面积越小的单体建筑,面积变化对能耗影响越大。3越"瘦高"的建筑,建筑能耗越大。