Calibrating building energy simulation models: A review of the basics to guide future work

2021 ◽  
pp. 111533
Author(s):  
Adrian Chong ◽  
Yaonan Gu ◽  
Hongyuan Jia
Keyword(s):  
Simulation Models ◽  
Building Energy ◽  
Energy Simulation ◽  
Building Energy Simulation ◽  
Future Work

scholarly journals Uncertainty Sources and Calculation Approaches for Building Energy Simulation Models

2015 ◽  
Vol 78 ◽  
pp. 2566-2571 ◽  
Author(s):  
Yinchun Ding ◽  
Yang Shen ◽  
Jianguo Wang ◽  
Xing Shi
Keyword(s):  
Simulation Models ◽  
Building Energy ◽  
Energy Simulation ◽  
Building Energy Simulation ◽  
Uncertainty Sources

A Procedure for Testing the Ability of Whole Building Energy Simulation Programs to Thermally Model the Building Fabric

1995 ◽  
Vol 117 (1) ◽  
pp. 7-15 ◽  
Author(s):  
R. D. Judkoff ◽  
J. S. Neymark
Keyword(s):  
International Energy Agency ◽  
Simulation Models ◽  
Building Energy ◽  
Energy Simulation ◽  
Building Energy Simulation ◽  
Thermal Mass ◽  
Reference Ranges ◽  
Energy Agency ◽  
Hourly Data ◽  
Whole Building Energy Simulation

A procedure was developed for systematically testing whole building energy simulation models and diagnosing the sources of predictive disagreement. Field trials of the method were conducted with a number of detailed state-of-the-art programs by researchers from nations participating in International Energy Agency (IEA) Task 12 and Annex 21. The technique consists of a series of carefully specified test case buildings that progress systematically from extremely simple to relatively realistic. Output values for the cases, such as annual loads, annual maximum and minimum temperatures, peak loads, and some hourly data are compared, and used in conjunction with diagnostic logic to determine the algorithms responsible for prediction differences. The more realistic cases, while geometrically simple, test the ability of the programs to model such combined effects as thermal mass, direct solar gain windows, window shading devices, internally generated heat, infiltration, sunspaces, earth coupling, and deadband and setback thermostat control. The more simplified cases facilitate diagnosis by allowing excitation of particular heat transfer mechanisms. The procedure was very effective at revealing bugs, faulty algorithms, and input errors in a group of building energy simulation programs that may be considered among the world’s best. The output data from the simulation programs can be used as reference ranges for comparing and diagnosing other detailed or simplified design tools.

Application of group screening to dynamic building energy simulation models

1997 ◽  
Vol 57 (1-4) ◽  
pp. 285-304 ◽  
Author(s):  
N. Rahni ◽  
N. Ramdani ◽  
Y. Candau ◽  
P. Dalicieux
Keyword(s):  
Simulation Models ◽  
Building Energy ◽  
Energy Simulation ◽  
Building Energy Simulation

Evaluation of a multi-stage guided search approach for the calibration of building energy simulation models

2015 ◽  
Vol 87 ◽  
pp. 370-385 ◽  
Author(s):  
J. Cipriano ◽  
G. Mor ◽  
D. Chemisana ◽  
D. Pérez ◽  
G. Gamboa ◽  
...  
Keyword(s):  
Simulation Models ◽  
Building Energy ◽  
Energy Simulation ◽  
Building Energy Simulation ◽  
Guided Search ◽  
Multi Stage ◽  
Search Approach
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