Analysis of a simplified calibration procedure for 18 design-phase building energy models.

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Bibliographic Details
Title: Analysis of a simplified calibration procedure for 18 design-phase building energy models.
Authors: Samuelson, Holly W.1, Ghorayshi, Arash2, Reinhart, Christoph F.3
Source: Journal of Building Performance Simulation. Jan2016, Vol. 9 Issue 1, p17-29. 13p.
Subjects: Calibration, Leadership in Energy & Environmental Design, Energy consumption, Standard deviations, Weather, Heating & ventilation industry
Abstract: This paper evaluates the accuracy of 18 design-phase building energy models, built according to LEED Canada protocol, and investigates the effectiveness of model calibration steps to improve simulation predictions with respect to measured energy data. These calibration steps, applied in professional practice, included inputting actual weather data, adding unregulated loads, revising plug loads (often with submetered data), and other simple updates. In sum, the design-phase energy models underpredicted the total measured energy consumption by 36%. Following the calibration steps, this error was reduced to a net 7% underprediction. For the monthly energy use intensity (EUI), the coefficient of variation of the root mean square error improved from 45% to 24%. Revising plug loads made the largest impact in these cases. This step increased the EUI by 15% median (32% mean) in the models. This impact far exceeded that of calibrating the weather data, even in a sensitivity test using extreme weather years. [ABSTRACT FROM PUBLISHER]
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Database: Engineering Source
Description
Abstract:This paper evaluates the accuracy of 18 design-phase building energy models, built according to LEED Canada protocol, and investigates the effectiveness of model calibration steps to improve simulation predictions with respect to measured energy data. These calibration steps, applied in professional practice, included inputting actual weather data, adding unregulated loads, revising plug loads (often with submetered data), and other simple updates. In sum, the design-phase energy models underpredicted the total measured energy consumption by 36%. Following the calibration steps, this error was reduced to a net 7% underprediction. For the monthly energy use intensity (EUI), the coefficient of variation of the root mean square error improved from 45% to 24%. Revising plug loads made the largest impact in these cases. This step increased the EUI by 15% median (32% mean) in the models. This impact far exceeded that of calibrating the weather data, even in a sensitivity test using extreme weather years. [ABSTRACT FROM PUBLISHER]
ISSN:19401493
DOI:10.1080/19401493.2014.988752