Calibration of an energy simulation with actual data has generally been considered too difficult to be part of the energy audit procedure. The purpose of this paper is to develop a systematic method using a “base load analysis approach” to calibrate a building energy performance model with a combination of monthly utility billing data and sub-metered data such as is commonly available in large buildings in Korea. The calibration procedure was specifically developed to be suitable for use in both the audit and savings determination procedure within a retrofit process. The procedure has been visualized using a logical flow chart and demonstrated using the simulation of a 26-story commercial building located in Seoul as a case study. The results indicate that the approach developed provided a reliable and accurate simulation of the monthly and annual building energy requirements of the case study building.

Issue Section:
Technical Papers
Keywords:
power consumption, energy conservation, calibration, load (electric)
Topics:
Calibration, Simulation, Stress, Commercial construction
1.
Diamond
,
S.
, and
Hunn
,
B.
,
1981
, “
Comparison of DOE-2 Computer Program Simulations to Metered Data from Seven Commercial Buildings
,”
ASHRAE Trans.
,
87
(
1
), pp.
1222
–
1231
.
2.
Holtz, M. 1990, “Electrical Energy Savings in Office Buildings,” Technical Report of Swedish Council for Building Research, ISBN 91-540-5213-0.
3.
Kaplan
,
M.
,
Mcferran
,
J.
,
Jansen
,
J.
, and
Pratt
,
R.
,
1990
, “
Reconciliation of a DOE2.1c Model with Monitored End-Use Data from a Small Office Building
,”
ASHRAE Trans.
,
96
(
1
), pp.
981
–
993
.
4.
Pratt
,
R. G.
,
1990
, “
Errors in Audit Predictions of Commercial Lighting and Equipment Loads and Their Impacts on Heating and Cooling Estimates
,”
ASHRAE Trans.
,
96
(
1
), pp.
994
–
1000
.
5.
McCray, J. A., Bailey, P. L., and Parker, J. L. 1995, “Using Data Visualization Tools for the Calibration of Hourly DOE-2.1 Simulation,” Building Simulation ’95, Int. Building Performance Simulation Assoc., 4th Int. Conf., pp. 461–466.
6.
Bou-Saada, T. E., and Haberl, J. S. 1995, “An Improved Procedure for Developing Calibrated Hourly Simulation Models” Building Simulation ’95, Int. Building Perform. Simul. Assoc. 4th Int. Conf., pp. 475–484.
7.
Bronson
,
D. J.
,
Hinchey
,
S. B.
,
Haberl
,
J. S.
, and
O’Neal
,
D. L.
,
1992
, “
A Procedure for Calibrating the DOE-2 Simulation Program to Non-Weather-Dependent Measured Loads
,”
ASHRAE Trans.
,
98
(
1
),
636
–
652
.
8.
Haberl
,
J. S.
,
Bronson
,
J. D.
, and
O’Neal
,
D. L.
,
1995
, “
An Evaluation of the Impact of Using Measured Weather Data Versus TMY Weather Data in a DOE-2 Simulation of an Existing Building in Central Texas
,”
ASHRAE Trans.
,
101
(
1
), pp.
558
–
576
.
9.
Haberl
,
J.
, and
Bou-Saada
,
T.
,
1998
, “
Procedures for Calibrating Hourly Simulation Models to Measured Building Energy and Environmental Data
,”
ASME J. Sol. Energy Eng.
,
120
(
3
), pp.
193
–
204
.
10.
Liu
,
M.
, and
Claridge
,
D. E.
,
1998
, “
Use of Calibrated HVAC System Models to Optimize System Operation
,”
ASME J. Sol. Energy Eng.
,
120
, pp.
131
–
138
.
11.
Liu, M., Wei, G., and Claridge, D. E. 1998, “Calibrating AHU Models Using Whole Building Cooling and Heating Energy Consumption Data,” Proc. of ACEEE 1998 Summer Study on Energy Efficiency in Buildings, 3, American Council for an Energy Efficient Economy, Washington, D.C., pp. 229–241.
12.
Reddy, S. N., Hunn, B. D., and Hood, D. B. 1994, “Determination of Retrofit Savings Using a Calibrated Building Energy Simulation Model,” Proc. of 9th Symp. on Improving Building Systems in Hot and Humid Climates, Arlington, TX, pp. 153–165.
13.
LBNL, 1982, “DOE-2 Reference Manual,” Lawrence Berkeley Laboratory and Los Alamos National Laboratory, Report No. LBL-8706 Rev. 2.
14.
Lyberg, M. D. 1987, Source Book for Energy Auditors, IEA Energy Conservation, Swedish Council for Building Research, Stockholm, Sweden, (ISBN: 91-540-4763-3).
15.
Huang, J. 1993, DrawBDL User’s Guide, Joe Huang and Associates, DrawBDL Version 1.03.
16.
Fels
,
M.
,
1986
, “
Special Issue Devoted to Measuring Energy Savings, The Scorekeeping Approach
,”
Energy Build.
,
9
(
1,2
), pp.
1
–
180
.
17.
Kissock
,
K.
,
Reddy
,
T. A.
, and
Claridge
,
D. E.
,
1998
, “
Ambient-Temperature Regression Analysis for Estimating Retrofit Savings in Commercial Buildings
,”
ASME J. Sol. Energy Eng.
,
120
(
3
), pp.
168
–
176
.
18.
Kreider
,
J. F.
, and
Haberl
,
J. S.
,
1994
, “
Predicting Hourly Building Energy Use
,”
ASHRAE Trans.
,
100
(
2
), pp.
1104
–
1118
.
19.
Haberl
,
J. S.
, and
Abbas
,
M.
,
1998
, “
Development of Graphical Indices for Viewing Building Energy Data: Part I
,”
ASME J. Sol. Energy Eng.
,
120
(
3
), pp.
156
–
161
.
20.
Kim, K. S., Yoon, J. H., and Lee, E. J. 1998, “A Study on Seoul Weather Data for Building Energy Audit,” 13th Workshop on Energy Conservation Technology, Yusong, Korea.
21.
Kim, K. S., Yoon, J. H., and Lee, E. J. 1997, “Development and Application of Advanced Energy Performance Assessment Technology for Building Energy Management,” KIER Tech. Report, 1997. 11.
22.
IPMVP, 1997, International Performance Measurement and Verification Protocol, U.S. Department of Energy, DOE/EE-0157, Washington, DC.
Copyright © 2003
 by ASME
You do not currently have access to this content.