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Predictive capability testing and sensitivity analysis of a model for building energy efficiency.

Authors :
Kalogeras, G.
Rastegarpour, S.
Koulamas, C.
Kalogeras, A. P.
Casillas, J.
Ferrarini, L.
Source :
Building Simulation; Feb2020, Vol. 13 Issue 1, p33-50, 18p
Publication Year :
2020

Abstract

Building energy modelling presents a good tool for estimating building energy consumption. Different modelling approaches exist in literature comprising white-box/physical/calculation-based models, black-box/statistical/measurement-based models or hybrid models combining the former two. Our work presented in this paper deals with a calculation-based quasi-steady-state model for building energy consumption based on the ISO 13790 standard and its implementation in MATLAB/Octave. The model is also well compared to the ISO 52016 standard updating ISO 13790. The model predictive capability is confirmed against both EnergyPlus dynamic simulator results and calculation results of a commercially available relevant tool used as benchmarks. Machine learning techniques are applied to a large dataset of simulated data and a sensitivity analysis is presented narrowing down to the most influential model parameters. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19963599
Volume :
13
Issue :
1
Database :
Complementary Index
Journal :
Building Simulation
Publication Type :
Academic Journal
Accession number :
140970630
Full Text :
https://doi.org/10.1007/s12273-019-0559-8