Automated dynamic thermal simulation of houses and housing stocks using readily available reduced data
Automated dynamic thermal simulation of houses and housing stocks using readily available reduced data
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使用现成的简化数据对房屋和住房进行自动动态热模拟
DOI：
10.1016/j.enbuild.2019.109431
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发表时间：
2019
影响因子：
6.7
通讯作者：
Badiei A
中科院分区：
文献类型：
--
作者：
Badiei A
本文描述了一种快速建模房屋和住宅库存供暖能量需求和室内空气温度动态的新方法。简化数据能量模型(RdDEM)通过增强简化数据标准评估程序(RdSAP)的输入数据集，为稳态建模提供了一种经济高效的替代方案。RdSAP是英国用于计算能源性能证书(EPC)的方法。这消除了与房屋库存的动态热模拟(DTS)相关的主要缺点，即所需的大量输入数据和为每栋房屋建模所需的大量时间。RdDEM算法在Energy Plus DTS软件中创建RdSAP等价的几何、结构、热质量和边界条件。新的推论和方法改进首先进行了测试，然后使用83个半独立房屋的样本进行了大规模实施。RdDEM的大部分能量结果都在RdSAP的10%以内。RdDEM方法提供了一种动态替代RdSAP的方法，用于了解家庭能源需求和室内空气温度的动态变化。这可能包括评估社区能源计划的高峰需求或评估个别住宅的夏季过热风险。最终，它可以使用已经从数百万套房屋收集的数据来提供一个动态的住房存量模型，以生成EPC。
This paper describes a new method to swiftly model the dynamics of heating energy demand and indoor air temperatures of houses and housing stocks. The Reduced data Energy Model (RdDEM) provides a cost-effective alternative to steady-state modelling by enhancing the input dataset from the Reduced data Standard Assessment Procedure (RdSAP) – the method used to calculate Energy Performance Certificates (EPC) in the UK. This eliminates the main drawbacks associated with dynamic thermal simulation (DTS) of housing stocks, namely the large amount of required input data and the significant time required to model each house.The RdDEM algorithms create RdSAP-equivalent geometry, construction, thermal mass and boundary conditions in Energy Plus DTS software. The new inferences and methodological enhancements were first tested and then implemented at scale using a sample of 83 semi-detached houses. Most energy results from RdDEM were within 10% of those from RdSAP. The differences are explained by the different ways that indoor air temperature is calculated.The RdDEM method provides a dynamic alternative to RdSAP for understanding the dynamics of energy demand and indoor air temperatures in homes. This could include assessing the peak demand of a community energy scheme or assessing the summertime overheating risk in individual dwellings. Ultimately, it could provide a dynamic housing stock model using the data already collected from millions of houses to generate EPCs.
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影响因子：
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作者：
Amit Mhalas;M. Kassem;T. Crosbie;N. Dawood
通讯作者：
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英国住房的动态能量建模：替代方法的评估
DOI：
10.26868/25222708.2013.2507
发表时间：
2013
期刊：
Building Simulation Conference Proceedings
影响因子：
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作者：
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通讯作者：
K. Lomas
DOI：
10.1016/s0301-4215(97)00130-4
发表时间：
1997-10
期刊：
Fuel and Energy Abstracts
影响因子：
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影响因子：
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