Calibration and uncertainty analysis for computer models – A meta-model based approach for integrated building energy simulation

Massimiliano Manfren, Niccolò Aste and Reza Moshksar

Applied Energy, 2013, vol. 103, issue C, 627-641

Abstract: In energy and environment field models are constructed, in general, based on well-defined physical phenomena and properties. Calibration and uncertainty analysis hold a particular interest because models represent a simplification of reality and, therefore, it is necessary to quantify to what degree they are imperfect before employing them in design, prediction and decision making processes. Integrated building energy models attempt to describe the effect of various internal and external actions (weather, occupancy, appliances, etc.) through physical relations (both algebraic and differential) and they are being widely used to design and operate high performance buildings, which are an essential component of a global energy strategy to reduce carbon emission and fossil sources depletion. An approach oriented to systems and able to integrate effectively field measured data and computer simulations for calibration in the modeling process has the potential to revolutionize the way buildings are designed and operated, and to stimulate also the development of new technologies and solutions in the field. The research presented in this paper aims to represent an initial step towards this integrated approach.

Keywords: Model calibration; Uncertainty and sensitivity analysis; Bayesian analysis; Kernel regression; Gaussian processes (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (63)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261912007374
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:103:y:2013:i:c:p:627-641

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2012.10.031

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().