CALIBRO: an R package for the automatic calibration of building energy simulation models

Filippo Monari, Paul Strachan

Research output: Contribution to conferencePaper

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Abstract

Bayesian probability theory offers a powerful framework for the calibration of building energy models (Bayesian calibration). The major issues impeding
its routine adoption are its steep learning curve, and the complicated setting up of the required calculation. This paper introduces CALIBRO, an R package
which has the objective of facilitating the undertaking of Bayesian calibration of building energy models. An overview of the techniques and procedures involved in CALIBRO is given, as well as demonstrations of its capability and reliability through two examples.
Original languageEnglish
Publication statusPublished - 7 Aug 2017
EventBuilding Simulation 2017: The 15th Biennial Conference of the International Building Performance Simulation Association (IBPSA) - Hyatt Regency Embarcadero, San Fransisco, United States
Duration: 7 Aug 20179 Aug 2017
Conference number: 15
http://www.buildingsimulation2017.org/

Conference

ConferenceBuilding Simulation 2017
Abbreviated titleBS17
CountryUnited States
CitySan Fransisco
Period7/08/179/08/17
Internet address

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Keywords

  • CALIBRO
  • building energy models
  • building energy simulation (BES)
  • Bayesian probability theory
  • Bayesian calibration

Cite this

Monari, F., & Strachan, P. (2017). CALIBRO: an R package for the automatic calibration of building energy simulation models. Paper presented at Building Simulation 2017, San Fransisco, United States.