Quantitative risk management for energy retrofit projects

Yeonsook Heo, Godfried Augenbroe, Ruchi Choudhary

Research output: Contribution to journalArticlepeer-review

36 Citations (Scopus)


This article presents a risk analysis method based on Bayesian calibration of building energy models. The Bayesian approach enables probabilistic outputs from the energy model, which are used to quantify risks associated with investing in energy conservation measures in existing buildings. This article demonstrates the applicability of the proposed methodology to support energy saving contracts in the context of the energy service company industry. A case study illustrates the importance of quantifying relative risks by comparing the probabilistic outputs derived from the Bayesian approach with standard practices endorsed by International Performance Measurement and Verification Protocol and ASHRAE guideline 14.

Original languageEnglish
Pages (from-to)257-268
Number of pages12
JournalJournal of Building Performance Simulation
Issue number4
Publication statusPublished - 2013
Externally publishedYes

Bibliographical note

Funding Information:
This study was partly funded by grants from the Energy Efficient Cities Initiative (EECi) at the University of Cambridge and the NSF-EFRI SEED grant ‘Risk-conscious Design and Retrofit of Buildings for Low Energy’ awarded to the Georgia Institute of Technology.


  • Bayesian calibration
  • Building energy models
  • Energy efficiency projects
  • Energy service companies
  • Risk analysis

ASJC Scopus subject areas

  • Architecture
  • Building and Construction
  • Modelling and Simulation
  • Computer Science Applications


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