Journal article
Calibration of Building Energy Simulation Programs Using the Analytic Optimization Approach (RP-1051)
HVAC&R research, v 12(1), pp 177-196
01 Jan 2006
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Reconciling results from detailed building energy simulation programs to measured data has always been recognized as essential in substantiating how well the simulation model represents the real building and its system. If the simulation results do not match actual monitored data, the programmer will typically 'adjust' inputs and operating parameters on a trial-and-error basis until the program output matches the known data. This 'ftidging' process often results in the manipulation of a large number of variables, which may significantly decrease the credibility of the entire simulation. A major drawback to the widesfiread acceptance and credibility of the calibrated simulation approach is that it is highly dependent on the personal judgment of the analyst doing the calibration. The lack of a proper mathematical foundation for the general calibration problem has greatly contributed to the current state 'of affairs. This paper proposes a general analytic framework for calibrating building energy system simulation software/programs that has a firm mathematical land statistical basis. The approach is based on the recognition that although calibration can be cast as an optimization problem, the basic issue is that the calibration problem is underdetermined or overparametrized, i.e., there are many more parameters to tune than can be supported by the monitored data. Further, detailed simulation programs are made up of nonlinear, implicit, and computationally demanding models. The proposed methodology involves several distinct concepts, namely, sensitivity analysis (to identify a subset of strong influential variables), identifiability analysis (to determine how many parameters of this subset can be tuned mathematically and which specific ones are the best candidates), numerical optimization (to determike the numerical values of this best subset of parameters), and uncertainty analysis (to deduce the range of variation of these parameters). A synthetic example involving an office buildin* is used to illustrate the methodology with the DOE-2 simulation program. The proposed methodology is recommended for use as the second step of a two-stage process with the first being a coarse-grid search that has reduced the number of simulation input parameters to a manageable few and also narrowed their individual range of variability.
Metrics
Details
- Title
- Calibration of Building Energy Simulation Programs Using the Analytic Optimization Approach (RP-1051)
- Creators
- Jian Sun - Air Products & ChemicalsAgami T Reddy - Drexel University
- Publication Details
- HVAC&R research, v 12(1), pp 177-196
- Publisher
- Taylor and Francis
- Number of pages
- 20
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- College of Engineering
- Web of Science ID
- WOS:000234731700011
- Scopus ID
- 2-s2.0-33644639915
- Other Identifier
- 991019168164704721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Construction & Building Technology
- Engineering, Mechanical
- Thermodynamics