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Title: A rigorous physics-based enhanced parameter estimation (EPE) methodology for calibration of building energy simulations

Journal Article · · Science and Technology for the Built Environment
 [1];  [2];  [3];  [2]
  1. Golden Analytics, Falls Church, VA (United States); Golden Analytics LLC
  2. M.S. Addison & Associates, Tempe, AZ (United States)
  3. Arizona State Univ., Tempe, AZ (United States)
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Buildings rarely perform as designed/simulated and there are numerous tangible benefits if this gap is reconciled. A new scientifically rigorous yet pragmatic methodology for calibrating building energy simulations - called Enhanced Parameter Estimation (EPE) - is proposed that allows physically relevant parameter estimation rather than a blind force-fit to energy use data. Starting with a rapidly created simulation model, calibration is performed in two stages: (a) building shell calibration with the HVAC system replaced by an ideal system that meets the loads (b) HVAC system calibration with the building shell and all internal loads replaced by a box with only process loads. In the first stage, EPE identifies a small number of high-level heat flows in the energy balance, calculates them with specifically tailored individual driving functions, introduces physically significant parameters to best accomplish energy balance, and, estimates the parameters and their uncertainty bounds. Calibration is thus done with corrective heat flows without any arbitrary tuning of input parameters. Calibration accuracy is enhanced by machine learning of the residual errors. The EPE methodology is demonstrated by means of: a synthetic building and an actual 75,000 sq. ft. building in Pennsylvania. Future work needed for widespread application is discussed.

Research Organization:
Golden Analytics LLC, Falls Church, VA (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office
Grant/Contract Number:
SC0018811
OSTI ID:
1839543
Journal Information:
Science and Technology for the Built Environment, Journal Name: Science and Technology for the Built Environment Journal Issue: 5 Vol. 28; ISSN 2374-4731
Publisher:
Taylor & FrancisCopyright Statement
Country of Publication:
United States
Language:
English

References (9)

Measuring industrial energy savings journal May 2008
Evaluation of “Autotune” calibration against manual calibration of building energy models journal November 2016
Improving infiltration modeling in commercial building energy models journal February 2015
A review of methods to match building energy simulation models to measured data journal September 2014
Calibration of Building Energy Simulation Programs Using the Analytic Optimization Approach (RP-1051) journal January 2006
Calibrating Detailed Building Energy Simulation Programs with Measured Data—Part I: General Methodology (RP-1051) journal March 2007
The building performance gap: Are modellers literate? journal January 2017
Machine learning for estimation of building energy consumption and performance: a review journal October 2018
Energy Audit of Building Systems: An Engineering Approach book December 2020

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32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
Calibration of building energy simulations
Commissioning
Energy efficiency
Optimization and modeling
Smart buildings