Modelling domestic energy consumption at district scale: A tool to support national and local energy policies
Modelling domestic energy consumption at district scale: A tool to support national and local energy policies
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DOI：
10.1016/j.envsoft.2011.04.005
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发表时间：
2011-10
期刊：
影响因子：
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通讯作者：
V. Cheng;K. Steemers
中科院分区：
文献类型：
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作者：
V. Cheng;K. Steemers
本文介绍了国内能源和碳模型（DECM）的发展，评估和应用，以预测现有的英国住房的能源消耗和二氧化碳排放量。DECM的一个新特点是采用了从住户就业状况数据得出的占用模式模型。我们相信，这一修改大大提高了空间加热能源使用估计的准确性。在国家层面，模型估算的碳排放量、天然气和电力消费量分别比国家统计数据高出4.5%、3.4%和1.0%。在国家以下一级（地方当局），使用两种方法进行估算：一种是基于住宅类型，另一种是基于社会经济阶层。对于这两种方法，模型估计值和政府记录之间的相关性在统计上是显著的和实质性的（所有rs> 0.9和ps <0.01）。根据研究结果，可以推断，超过85%的住宅能源消耗和碳排放的变化可以通过住宅类型和家庭的社会经济阶层来解释。本文提出了一个本地的敏感性分析，探讨了各种建筑结构和服务系统参数的影响，每个住宅的模拟平均碳排放量。基于研究结果，开发了一套预测图表，可以快速估计各种节能措施对住宅能源消耗和碳排放的影响，并考虑到潜在的反弹效应。总之，本文表明，DECM模型可以是一个有用的工具，以协助在国家和地方层面的能源效率政策的形成。
This paper presents the development, evaluation and application of the Domestic Energy and Carbon Model (DECM) for predicting the energy consumptions and carbon dioxide emissions of the existing English housing stock. A novel feature of DECM is the adoption of an occupancy pattern model which is derived from the household employment status data. We believe this modification has significantly improved the accuracy of the estimation in space heating energy use. At national level, the model estimation of carbon emissions and gas and electricity consumptions are respectively 4.5%, 3.4% and 1.0% higher than the national statistics. At the sub-national level (Local Authority), two methods are used to produce estimations: one based on dwelling type and the other based on socio-economic class. For both methods, the correlations between the model estimations and the government records are statistically significant and substantial (allrs> 0.9 andps<0.01). According to the results, it can be inferred that over 85% of the variance in dwelling energy consumptions and carbon emissions can be accounted for by dwelling type and the socio-economic class of households. The paper presents a local sensitivity analysis which examines the effects of various building fabric and service system parameters on the modelled average carbon emissions per dwelling. Based on the findings, a set of predictive charts are developed which can provide rapid estimations of the effect of various energy efficiency measures on dwelling energy consumptions and carbon emissions taking into account the potential rebound effect. In summary, this paper shows that the DECM model can be a useful tool to assist the formation of energy efficiency policies at both national and local levels.