Understanding the Reasons behind the Energy Performance Gap of an Energy-Efficient Building, through a Probabilistic Approach and On-Site Measurements

The performance gap, defined as the difference between the measured and the calculated performance of energy-efficient buildings, has long been identified as a major issue in the building domain. The present study aims to better understand the performance gap in high-energy performance buildings in...

Full description

Saved in:
Bibliographic Details
Published in:Energies (Basel) 2021-10, Vol.14 (19), p.6178
Main Authors: Padey, Pierryves, Goulouti, Kyriaki, Wagner, Guy, Périsset, Blaise, Lasvaux, Sébastien
Format: Article
Language:English
Subjects:
Air flow
Buildings
Case studies
Demand
Electricity
Energy
Energy consumption
Energy efficiency
Energy modeling
energy-efficient building
global sensitivity analysis
Heating
Monitoring systems
on-site measurements
Parameter uncertainty
performance gap
probabilistic heating demand
Sensitivity analysis
Ventilation
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The performance gap, defined as the difference between the measured and the calculated performance of energy-efficient buildings, has long been identified as a major issue in the building domain. The present study aims to better understand the performance gap in high-energy performance buildings in Switzerland, in an ex-post evaluation. For an energy-efficient building, the measured heating demand, collected through a four-year measurement campaign was compared to the calculated one and the results showed that the latter underestimates the real heating demand by a factor of two. As a way to reduce the performance gap, a probabilistic framework was proposed so that the different uncertainties of the model could be considered. By comparing the mean of the probabilistic heating demand to the measured one, it was shown that the performance gap was between 20–30% for the examined period. Through a sensitivity analysis, the active air flow and the shading factor were identified as the most influential parameters on the uncertainty of the heating demand, meaning that their wrong adjustment, in reality, or in the simulations, would increase the performance gap.
ISSN:1996-1073
1996-1073
DOI:10.3390/en14196178