Probabilistic Reliability Assessment and Case Studies for Predicted Energy Savings in Residential Buildings

Roderick Jackson, Piljae Im, Yeonjin Bae, Jin Don, Borui Cui

Research output: Contribution to journalArticlepeer-review

8 Scopus Citations


This study aims to (1) investigate the key influential parameters (KIPs) in estimating the uncertainty of energy savings using a residential building energy simulation model and (2) perform uncertainty quantification for energy savings for several different scenarios. The proposed methodology was successfully applied to the calculation of uncertainties associated with residential energy retrofits using two test houses designed for pre- and post-retrofit cases. Uncertainties were determined using basic parameters that might be supplied to an energy model and then reevaluated based on an audit of the KIPs identified, resulting in substantially reduced uncertainty. Of four different scenarios, the most uncertain scenario estimated the annual energy savings from the retrofit would be between 18% and 51% at a 95% confidence level, and the least uncertain scenario estimated the annual savings would be between 26% and 40% at a 95% confidence level. The actual measured annual savings from the two test houses was 28%, which shows an agreement with the uncertainty analysis.

Original languageAmerican English
Article number109658
Number of pages15
JournalEnergy and Buildings
StatePublished - 2020

Bibliographical note

Publisher Copyright:
© 2019

NREL Publication Number

  • NREL/JA-4A00-75831


  • Building energy modeling
  • Retrofit
  • Sensitivity analysis
  • Uncertainty quantification


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