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Modelling energy efficiency performance of residential building stocks based on Bayesian statistical inference

机译:基于贝叶斯统计推断的住宅建筑库存能效表现模型

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摘要

This paper provides a model based on Integrated Nested Laplace Approximation to predict the energy performance of existing residential building stocks. The energy demand and the discomfort hours for heating and cooling were taken as response variables and five parameters were considered as potentially significant to assess the building energy performance: urban block pattern, street height-width ratio, building class through the building shape factor, year of construction and solar orientation of the main façade. A total of 240 dynamic energy simulations were run varying these parameters, by using the EnergyPlus software with the Design Builder interface, which allowed the response variables to be determined for a set of sample buildings. Simulation results revealed the most and least significant parameters in the energy performance of the buildings. The model developed is a useful decision-making tool in assisting local authorities during energy refurbishment interventions at the urban scale.
机译:本文提供了一个基于集成嵌套拉普拉斯逼近的模型来预测现有住宅建筑存量的能源绩效。能源需求和供暖和制冷的不舒适时间被用作响应变量,五个参数被认为对评估建筑物的能源性能具有潜在的重要意义:城市街区格局,街道高宽比,通过建筑物形状因子的建筑物等级,年份主立面的结构和太阳能定向通过使用带有Design Builder界面的EnergyPlus软件,总共运行了240个动态能源模拟,以改变这些参数,从而可以确定一组样本建筑物的响应变量。仿真结果显示了建筑物能源性能中最重要和最不重要的参数。开发的模型是在城市规模的能源翻新干预过程中协助地方当局的有用决策工具。

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