In order to avoid high utility demand charges from cooling during the summer and to level a building’s electrical demand profile, precooling of the building’s massive structure can be applied to shift cooling-related thermal loads in response to utility pricing signals. Several previous simulation and experimental studies have shown that proper precooling can attain considerable reduction of operating cost in buildings. This paper systematically evaluates the merits of the passive building thermal capacitance to minimize energy cost for a design day using optimal control. The evaluation is conducted by means of a sensitivity analysis utilizing a dynamic building energy simulation program coupled to a popular technical computing environment. The optimal controller predicts the required extent of precooling (zone temperature set-point depression), depending on the utility rate structure, occupancy and on-peak period duration and onset, internal gains, building mass, occupancy period temperature set-point range, and weather as characterized by diurnal temperature and relative humidity swings. In addition to quantifying the building response, energy consumption, and utility cost, this paper extracts the dominant features of the optimal precooling strategies for each of the investigated cases so that guidelines for near-optimal building thermal mass savings may be developed in the future.

1.
Braun
,
J. E.
, 1990, “
Reducing Energy Costs and Peak Electrical Demand Through Optimal Control of Building Thermal Mass
,”
ASHRAE Trans.
0001-2505,
96
(
2
), pp.
876
888
.
2.
Golneshan
,
A. A.
, and
Yaghoubi
,
M. A.
, 1990, “
Simulation of Ventilation Strategies of a Residential Building in Hot Arid Regions of Iran
,”
Energy Build.
0378-7788,
14
, pp.
201
205
.
3.
Snyder
,
M. E.
, and
Newell
,
T. A.
, 1990, “
Cooling Cost Minimization Using Building Thermal Mass for Thermal Storage
,”
ASHRAE Trans.
0001-2505,
96
(
2
), pp.
830
838
.
4.
Rabl
,
A.
, and
Norford
,
L. K
, 1991, “
Peak Load Reduction by Preconditioning Buildings at Night
,”
Int. J. Energy Res.
0363-907X,
15
, pp.
781
798
.
5.
Andresen
,
I.
, and
Brandemuehl
,
M. J.
, 1992, “
Heat Storage in Building Thermal Mass: A Parametric Study
,”
ASHRAE Trans.
0001-2505,
98
(
1
), pp.
910
918
.
6.
Keeney
,
K. R.
, and
Braun
,
J. E.
, 1996, “
A Simplified Method for Determining Optimal Cooling Control Strategies for Thermal Storage in Building Mass
,”
HVAC&R Res.
1078-9669,
2
(
1
), pp.
59
78
.
7.
Conniff
,
J. P.
, 1991, “
Strategies for Reducing Peak Air-Conditioning Loads by Using Heat Storage in the Building Structure
,”
ASHRAE Trans.
0001-2505,
97
(
1
), pp.
704
709
.
8.
Morris
,
F. B.
,
Braun
,
J. E.
, and
Treado
,
S. J.
, 1994, “
Experimental and Simulated Performance of Optimal Control of Building Thermal Storage
,”
ASHRAE Trans.
0001-2505,
100
(
1
), pp.
402
414
.
9.
Ruud
,
M. E.
,
Mitchell
,
J. W.
, and
Klein
,
S. A.
, 1990, “
Use of Building Thermal Mass to Offset Cooling Loads
,”
ASHRAE Trans.
0001-2505,
96
(
2
), pp.
820
828
.
10.
Keeney
,
K. R.
, and
Braun
,
J. E.
, 1997, “
Application of Building Precooling to Reduce Peak Cooling Requirements
,”
ASHRAE Trans.
0001-2505,
103
(
1
), pp.
463
469
.
11.
Braun
,
J. E.
,
Lawrence
,
T. M.
,
Klaassen
,
C. J.
, and
House
,
J. M.
, 2002, “
Demonstration of Load Shifting and Peak Load Reduction with Control of Building Thermal Mass
,”
Proc. of 2002 ACEEE Summer Study on Energy Efficiency in Buildings
, American Council for an Energy Efficient Economy, Washington, D.C., pp.
3.55
3.67
.
12.
Henze
,
G. P.
,
Kalz
,
D.
,
Liu
,
S.
, and
Felsmann
,
C.
, 2005, “
Experimental Analysis of Model-Based Predictive Optimal Control for Active and Passive Building Thermal Storage Inventory
,”
HVAC&R Res.
1078-9669,
11
(
2
), pp.
189
214
.
13.
Henze
,
G. P.
,
Dodier
,
R. H.
, and
Krarti
,
M.
, 1997, “
Development of a Predictive Optimal Controller for Thermal Energy Storage Systems
,”
HVAC&R Res.
1078-9669,
3
(
3
), pp.
233
264
.
14.
Henze
,
G. P.
, and
Krarti
,
M.
, 1999, “
The Impact of Forecasting Uncertainty on the Performance of a Predictive Optimal Controller for Thermal Energy Storage Systems
,”
ASHRAE Trans.
0001-2505,
105
(
1
), pp.
553
561
.
15.
Liu
,
S.
, and
Henze
,
G. P.
, 2004, “
Impact of Modeling Accuracy on Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory
,”
ASHRAE Trans.
0001-2505,
110
(
1
), pp.
151
163
.
16.
Braun
,
J. E.
, 2003, “
Load Control Using Building Thermal Mass
,”
ASME J. Sol. Energy Eng.
0199-6231,
125
(
3
), pp.
292
301
.
17.
Carrier Corporation, 2003, “
30GTN Air-Cooled Reciprocating Liquid Chillers With ComfortLink Controls
,” available at http://www.xpedio.carrier.com/idc/groups//public/documents/techlit/30gtn-5pd.pdfhttp://www.xpedio.carrier.com/idc/groups//public/documents/techlit/30gtn-5pd.pdf
18.
U. S. Department of Energy, 1980, “
Doe-2 Reference Manual, Part 1
,” Ver. 2.1. Lawrence Berkeley Laboratory, Berkeley, CA.
19.
Nelder
,
J. A.
, and
Mead
,
R.
, 1965, “
A Simplex Method for Function Minimization
,”
Comput. J.
0010-4620,
7
, pp.
308
313
.
20.
Matlab, 1996,
Optimization Toolbox User’S Guide
,
The MathWorks
,
Natick, MA
.
21.
AASHRAE, 1997,
ASHRAE Handbook of Fundamentals
,
ASHRAE
Atlanta, GA
, Chap., 28,
Nonresidential Heating and Cooling Calculations
, Table 2, pg.
286
.
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