Monte Carlo housing stock model to predict the energy performance indicators

This study presents a new physics-based model of housing stock energy using Monte Carlo, where inputs are probability distribution functions originated from Energy Performance Certification (EPC) Portuguese database. The overall performance of the model in predicting the energy indicators used in EP...

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Veröffentlicht in:Energy and buildings 2017-10, Vol.152, p.503-515
Hauptverfasser: Fonseca, J.N.B., Oliveira Panão, Marta J.N.
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Oliveira Panão, Marta J.N.
description This study presents a new physics-based model of housing stock energy using Monte Carlo, where inputs are probability distribution functions originated from Energy Performance Certification (EPC) Portuguese database. The overall performance of the model in predicting the energy indicators used in EPC is extremely satisfactory, considering that the inputs required to run the calculations are not always available. The model outputs are validated against EPC data with residual sum of squares (RSS) below 2×10−3, except for cooling energy benchmark with RSS below 4×10−2. The main output of EPC, the distribution among classes, is successfully reproduced by the model, with differences in the number of occurrences below 3.1%. The developed model constitutes a tool that helps on further research on energy policies, namely, studying the impact evaluation of more restrictive thermal quality requirements; evaluating other methodological approaches to calculate energy indicators; analysing policies of building elements retrofitting and bottom-up estimations of housing stock energy consumption.
doi_str_mv 10.1016/j.enbuild.2017.07.059
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subjects Bottom-up model
Business metrics
Computer simulation
Distribution functions
Energy consumption
Energy distribution
Energy indicators
Energy policy
Housing
Housing stock
Indicators
Mathematical models
Monte Carlo
Monte Carlo simulation
Physics
Physics-based model
Probability distribution
Probability distribution functions
Retrofitting
Studies
title Monte Carlo housing stock model to predict the energy performance indicators
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