Developing a Data-driven school building stock energy and indoor environmental quality modelling method
Developing a Data-driven school building stock energy and indoor environmental quality modelling method
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开发数据驱动的校舍存量能源和室内环境质量建模方法
DOI：
10.1016/j.enbuild.2021.111249
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发表时间：
2021
影响因子：
6.7
通讯作者：
D. Mumovic
中科院分区：
文献类型：
--
作者：
Y. Schwartz;D. Godoy;I. Korolija;J. Dong;S. Hong;A. Mavrogianni;D. Mumovic
学校建筑部门在向低碳英国经济过渡中发挥着关键作用。学校建筑占该国公共部门碳排放量的15%，目前空间供暖在学校能源使用和相关成本中占最大比例。孩子们醒着的大部分时间都在学校里度过。有大量证据表明，室内空气质量差和热不适会对学生和学校工作人员的表现、福祉和健康产生不利影响。由于学校环境的独特运作特点，例如高和间歇性的占用密度或全年占用模式的变化，保持高室内环境质量同时减少学校的能源需求和碳排放是具有挑战性的。此外，现有数据显示，英格兰81%的学校建筑是在1976年之前建造的。在当前和未来气候变化的背景下，老化的学校建筑群面临的挑战可能会加剧，近几十年来，建筑群建模已被广泛用于量化和评估社区，城市，区域或国家一级大量建筑物的当前和未来的能源和室内环境质量性能。建筑存量模型通常使用建筑原型，其目的是通过频繁出现的建筑类型来表示建筑存量的多样性。本文的目的是介绍一种新颖的、数据驱动的、基于原型的学校建筑存量建模框架--学校原型模型数据驱动引擎（DREAMS）。DREAMS通过对英国政府提供的两个大规模和高度详细的数据库进行统计分析，详细描述了英国的学校建筑存量：（i）教育部（DfE）的财产数据调查计划（PDSP），和（ii）显示能源证书（DEC）。本文介绍了代表英国9,551所小学的168个建筑原型的发展情况。使用经过广泛测试和应用的建筑性能软件EnergyPlus，对当前气候下典型年份的英国小学建筑物的能耗进行了建模。为了建模验证的目的，梦想空间供暖需求预测进行了比较，对平均测量的能源消耗的学校，由每个原型。结果表明，英国一所典型小学的模拟化石热能消耗仅比实测能耗高7%（模拟为139 kWh/m2/y，实测为130 kWh/m2/y）。建筑存量模型在预测自然通风建筑（占存量的97%）的能源性能方面优于机械通风建筑。该框架还显示出在更局部规模上预测能源消耗的能力。伦敦小学建筑存量作为一个案例研究进行了审查。学校建筑存量建模框架，如梦想，可以是强大的工具，帮助决策者量化和评估的影响范围广泛的建筑存量水平的政策，能源效率的干预措施和气候变化的情况下，学校的能源和室内环境性能。
The school building sector has a pivotal role to play in the transition to a low carbon UK economy. School buildings are responsible for 15% of the country’s public sector carbon emissions, with space heating currently making up the largest proportion of energy use and associated costs in schools. Children spend a large part of their waking life in school buildings. There is substantial evidence that poor indoor air quality and thermal discomfort can have detrimental impacts on the performance, wellbeing and health of schoolchildren and school staff. Maintaining high indoor environmental quality whilst reducing energy demand and carbon emissions in schools is challenging due to the unique operational characteristics of school environments, e.g. high and intermittent occupancy densities or changes in occupancy patterns throughout the year. Furthermore, existing data show that 81% of the school building stock in England was constructed before 1976. Challenges facing the ageing school building stock may be exacerbated in the context of ongoing and future climate change.In recent decades, building stock modelling has been widely used to quantify and evaluate the current and future energy and indoor environmental quality performance of large numbers of buildings at the neighbourhood, city, regional or national level. Building stock models commonly use building archetypes, which aim to represent the diversity of building stocks through frequently occurring building typologies.The aim of this paper is to introduce the Data dRiven Engine for Archetype Models of Schools (DREAMS), a novel, data-driven, archetype-based school building stock modelling framework. DREAMS enables the detailed representation of the school building stock in England through the statistical analysis of two large scale and highly detailed databases provided by the UK Government: (i) the Property Data Survey Programme (PDSP) from the Department for Education (DfE), and (ii) Display Energy Certificates (DEC). In this paper, the development of 168 building archetypes representing 9,551 primary schools in England is presented. The energy consumption of the English primary school building stock was modelled for a typical year under the current climate using the widely tested and applied building performance software EnergyPlus. For the purposes of modelling validation, the DREAMS space heating demand predictions were compared against average measured energy consumption of the schools that were represented by each archetype. It was demonstrated that the simulated fossil-thermal energy consumption of a typical primary school in England was only 7% higher than measured energy consumption (139 kWh/m2/y simulated, compared to 130 kWh/m2/y measured). The building stock model performs better at predicting the energy performance of naturally ventilated buildings, which constitute 97% of the stock, than that of mechanically ventilated ones. The framework has also shown capabilities in predicting energy consumption on a more localised scale. The London primary school building stock was examined as a case study.School building stock modelling frameworks such as DREAMS can be powerful tools that aid decision-makers to quantify and evaluate the impact of a wide range of building stock-level policies, energy efficiency interventions and climate change scenarios on school energy and indoor environmental performance.
模拟伦敦城市热岛和住宅热质量对过热的相对重要性
影响因子：
7.4
作者：
Oikonomou E
通讯作者：
Oikonomou E
影响因子：
3.9
作者：
Hong S
通讯作者：
Hong S