Calibrating detailed building energy simulation programs with measured data—part I: General methodology (RP-1051)

HVAC and R Research

Volumn 13, Issue 2, 2007, Pages 221-241

  Reddy, T Agami ^a   Maor, Itzhak ^b   Panjapornpon, Chanin ^c  

^a Drexel University   (United States)

^b PWI Energy   (United States)

^c KASETSART UNIVERSITY   (Thailand)

Author keywords

[No Author keywords available]

Indexed keywords

CALIBRATION; COMPUTATIONAL EFFICIENCY; COMPUTER SIMULATION; ENERGY UTILIZATION; HEURISTIC METHODS; MONTE CARLO METHODS; PARAMETER ESTIMATION;

BUILDING ENERGY SIMULATION PROGRAMS;

CLIMATE CONTROL;

EID: 34247520494     PISSN: 10789669     EISSN: None     Source Type: Journal    
DOI: 10.1080/10789669.2007.10390952     Document Type: Article

References (51)

1. ASHRAE. 2001. ANSI/ASHRAE/IESNA Standard 90.1–2001, Energy Standard for Buildings Except Low-Rise Residential Buildings. Atlanta:American Society of Heating, Refrigerating and Air-Conditioning Engineers.
2. ASHRAE. 2002. ASHRAE Guideline 14–2002, Measurement of Energy and Demand Savings. Atlanta:American Society of Heating, Refrigerating and Air-Conditioning Engineers.
3. Box, G. E. P., Hunter, W. G., and Hunter, J. S., 1978. Statistics for Experimenters—An Introduction to Design, Data Analysis, and Model Building. New York:John Wiley & Sons.
4. Burns, E. M., 1990. Annual and monthly peak demand for electricity in commercial buildings. Proceedings of the ACEEE Summer Study on Energy Efficiency in Buildings, 3:47–55.
5. Caldas, L. G., and Norford, L. K., 2003. Genetic algorithms for optimization of building envelopes and the design and control of HVAC systems. ASME Journal of Solar Energy Eng., 125:343–51.
6. Carroll, W. L., and Hitchcock, R. J., 1993. Tuning simulated building description to match actual utility data:Methods and implementation. ASHRAE Transactions, 99 (2):928–34.
7. Chou, S. K., and Chang, W. L., 1993. Development of an energy-estimating equation for large commercial buildings. International Journal of Energy Research, 17:759–73.
8. Chou, S. K., Chang, W. L., and Wong, Y. W., 1993. Effects of multi-parameter changes on energy use in large buildings. International Journal of Energy Research, 17:885–903.
9. Christensen, C., Stoltenberg, B., and Barker, G., An optimization methodology for zero net energy buildings. ASME Solar Energy Conference Proceedings. June, Hawaii.
10. Corson, G. C., 1992. Input-output sensitivity of building energy simulations. ASHRAE Transactions, 98 (1):618–26.
11. Cumali, Z., 1988. Global optimization of HVAC system operations in real time. ASHRAE Transactions, 94 (1):1729–43.
12. De Wit, S., and Augenbroe, G., 2002. Analysis of uncertainty in building design evaluations and its implications. Energy and Buildings, 34:951–58.
13. Eisenberg, J. N., Seto, E. Y. W., Olivieri, A. W., and Spear, R. C., 1996. Quantifying water pathogen risk in an epidemiological framework. Risk Analysis, 16 (4):549–63.
14. Eto, J. H., An investigation of the use of prototypes for commercial sector EUI analysis. Proceedings of the ACEEE Summer Study on Energy Efficiency in Buildings. Vol. 10, pp. 29–37.
15. Frey, H. C., 2002. Introduction to special section on sensitivity analysis and summary of NCSU/USDA workshop on sensitivity analysis. Risk Analysis, 22 (3):539–45.
16. Frey, H. C., and Patil, S. R., 2002. Identification and review of sensitivity analysis methods. Risk Analysis, 22 (3):553–78.
17. Hammersley, J. M., and Handscomb, D. C., 1964. Monte Carlo Methods. London:Methuen and Co.
18. Helton, J. C., and Davis, F. J., 2003. Latin hypercube sampling and the propagation of uncertainty of complex systems. Reliability Engineering and System Safety, 81:23–69.
19. Hofer, E., 1999. Sensitivity analysis in the context of uncertainty analysis for computationally intensive models. Computer Physics Communication, 117:21–34.
20. Hornberger, G. M., and Spear, R. C., 1981. An approach to the preliminary analysis of environmental systems. Journal of Environmental Management, 12:7–18.
21. Hou, D., Jones, J. W., Hunn, B. D., and Banks, J. A., Development of HVAC system performance criteria using factorial design and DOE-2 simulations. Proceedings of the 10th Symposium on Improving Building Systems in Hot and Humid Climates. May13–14, Fort Worth, TX. pp. 184–92.
22. Huang, Y. J., Hanford, J. W., and Piraino, M., The impact of variations in building parameters and operating conditions on commercial building energy use and load shapes. IBPSA Conference. Aug.16–18, Adelaide, Australia. pp. 215–22.
23. Huang, Y. J., and Franconi, E., 1995. Commercial building heating and cooling loads component analysis, LBNL-37208 Berkeley, CA:Lawrence Berkeley National Laboratory.
24. Hui, S. C. M., A randomized approach to multiple regression analysis of building energy simulation. IBPSA Conference. Sept.13–15, Prague, Czech Republic. Vol. 1, pp. 103–10.
25. Iman, R. L., and Helton, J. C., 1985. A comparison of uncertainty and sensitivity analysis techniques for computer models Alberqu-erque, NM:Sandia National Laboratories. Report NUREG/CR-3904, SAND 84–1461
26. Judkoff, R., Wortman, D., O'Doherty, B., and Burch, J., 1983. A methodology for validating building energy analysis simulations, SERI/TR-254–1508 Golden, CO:Solar Energy Research Institute (now National Renewable Energy Laboratory).
27. Kaplan, M. B., McFerran, J., Jansen, J., and Pratt, R., 1990. Reconciliation of a DOE2.1C model with monitored end-use data for a small office building. ASHRAE Transactions, 96 (1):981–93.
28. Kreider, J. F., and Haberl, J., 1994. Predicting hourly building energy usage:The great predictor shootout—Overview and discussion of results. ASHRAE Transactions, 100 (2):1104–18.
29. Lam, J. C., and Hui, S. C. M., 1996. Sensitivity analysis of energy performance of office buildings. Building and Environment, 31 (1):27–39.
30. Lomas, K. J., and Eppel, H., 1992. Sensitivity analysis techniques for building thermal simulation programs. Energy and Buildings, 19:21–44.
31. Macdonald, I., and Strachan, P., 2001. Practical application of uncertainty analysis. Energy and Buildings, 33:219–27.
32. Mottillo, M., 2001. Sensitivity analysis of energy simulation by building type. ASHRAE Transactions, 107 (2):722–32.
33. Oliva, R., 2003. Model calibration as a testing strategy for system dynamics models. European Journal of Operational Research, 151:552–68.
34. Reddy, T. A., 2006. Literature review on calibration of building energy simulation programs:Uses, problems, procedures, uncertainty, and tools. ASHRAE Transactions, 12 (1):177–96.
35. Reddy, T. A., and Claridge, D. E., 2000. Uncertainty of "measured" energy savings from statistical baseline models. HVAC&R Research, 6 (1):3–20.
36. Reddy, T. A., Maor, I., Panjapornpon, C., and Sun, J., Procedures for reconciling computer-calculated results with measured energy data, ASHRAE RP-1051, final report. January. Atlanta:American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc.
37. Reddy, T. A., Maor, I., and Panjapornpon, C., 2007. Calibrating detailed building energy simulation programs with measured data—Part II:Application to three case study office buildings. HVAC&R Research, 13 (2)
38. Reinhard, M., and Duffy, J., Optimization methods for alternative energy system design. Proceedings of the ASES Annual Conference. Boulder, CO:American Solar Energy Society.
39. Saltelli, A., 2002. Sensitivity analysis for importance assessment. Risk Analysis, 22 (2):579–90.
40. Saltelli, A., and Marivoet, J., 1990. Non-parametric statistics in sensitivity analysis for model output:A comparison of selected techniques. Reliability Engineering and System Safety, 28:229–53.
41. Saltelli, A., Chan, K., and Scott, E. M., eds. 2000. Sensitivity Analysis. Chichester:John Wiley and Sons.
42. Saporito, A., Day, A. R., Karayiannis, T. G., and Parand, F., 2001. Multi-parameter building thermal analysis using the lattice method for global optimization. Energy and Buildings, 33:267–74.
43. Sharp, T. R., Energy benchmarking in commercial office buildings. Proceedings of the ACEEE Summer Study on Energy Efficiency in Buildings. pp. 321–29. paper 4
44. Sonderegger, R., Avina, J., Kennedy, J., and Bailey, P., Deriving loadshapes from utility bills through scaled simulation. Seminar presentation, ASHRAE Annual Meeting. Kansas City, MO.
45. Spears, R., Grieb, T., and Shiang, N., 1994. Parameter uncertainty and interaction in complex environmental models. Water Resources Research, 30 (11):3159–69.
46. Sullivan, R., Nozari, S., Johnson, R., and Selkowitz, S., 1985. Commercial building energy performance analysis using multiple regression. ASHRAE Trans actions, 91 (2):337–53.
47. Sun, J., and Reddy, T. A., 2006. Calibration of building energy simulation programs using the analytic optimization approach. HVAC&R Research, 12 (1):177–96.
48. Trane. 1992. TRACE 600 Program LaCrosse, WI:Trane Company.
49. USEIA. 1995. Commercial buildings energy consumption and expenditures 1992 Washington, DC:US Energy Information Agency. US Energy Information Administration, DOE/EIA-0318(92)
50. Wetter, M., GenOpt:Generic Optimization Program. Seventh International IBPSA Conference. Rio de Janeiro, Brazil. pp. 601–608.
51. Winkelmann, F. C., Birdsall, B. E., Buhl, W. F., Ellington, K. L., Erdem, A. E., Hirsch, J. J., and Gates, S., 1993. DOE-2 Supplement, Version 2.1E Berkeley, CA:Lawrence Berkeley National Laboratory. November