Standard (black-box) regression models may not necessarily suffice for accurate identification and prediction of thermal dynamics in buildings. This is particularly apparent when either the flow rate or the inlet temperature of the thermal medium varies significantly with time. To this end, this paper analytically derives, using physical insight, and investigates linear regression models (LRMs) with nonlinear regressors (NRMs) for system identification and prediction of thermal dynamics in buildings. Comparison is performed with standard linear regression models with respect to both (a) identification error and (b) prediction performance within a model-predictive-control implementation for climate control in a residential building. The implementation is performed through the EnergyPlus building simulator and demonstrates that a careful consideration of the nonlinear effects may provide significant benefits with respect to the power consumption.

References

1.
Nghiem
,
T.
, and
Pappas
,
G.
,
2011
, “
Receding-Horizon Supervisory Control of Green Buildings
,”
2011 American Control Conference
, June 29–July 1, pp.
4416
4421
.http://ieeexplore.ieee.org/document/5990995/
2.
Oldewurtel
,
F.
,
Parisio
,
A.
,
Jones
,
C.
,
Morari
,
M.
,
Gyalistras
,
D.
,
Gwerder
,
M.
,
Stauch
,
V.
,
Lehmann
,
B.
, and
Morari
,
M.
,
2012
, “
Use of Model Predictive Control and Weather Forecasts for Energy Efficient Building Climate Control
,”
Energy Build.
,
45
, pp.
15
27
.
3.
Nghiem
,
T.
,
Pappas
,
G.
, and
Mangharam
,
R.
,
2013
, “
Event-Based Green Scheduling of Radiant Systems in Buildings
,”
2013 American Control Conference
(
ACC
), June 17–19, pp.
455
460
.
4.
Touretzky
,
C. R.
, and
Baldea
,
M.
,
2014
, “
Nonlinear Model Reduction and Model Predictive Control of Residential Buildings With Energy Recovery
,”
J. Process Control
,
24
(
6
), pp.
723
739
.
5.
Coogan
,
S.
,
Ratliff
,
L.
,
Calderone
,
D.
,
Tomlin
,
C.
, and
Sastry
,
S.
,
2013
, “
Energy Management Via Pricing in LQ Dynamic Games
,”
2013 American Control Conference
(
ACC
), June 17–19, pp.
443
448
.
6.
Rasmussen
,
B.
,
Alleyne
,
A.
, and
Musser
,
A.
,
2005
, “
Model-Driven System Identification of Transcritical Vapor Compression Systems
,”
IEEE Trans. Control Syst. Technol.
,
13
(
3
), pp.
444
451
.
7.
Maasoumy
,
M.
,
Razmara
,
M.
,
Shahbakhti
,
M.
, and
Vincentelli
,
A. S.
,
2014
, “
Handling Model Uncertainty in Model Predictive Control for Energy Efficient Buildings
,”
Energy Build.
,
77
, pp.
377
392
.
8.
Ljung
,
L.
,
1999
,
System Identification: Theory for the User
, 2nd ed.,
Prentice Hall PTR
,
Upper Saddle River, NJ
.
9.
Yiu
,
J.-M.
, and
Wang
,
S.
,
2007
, “
Multiple ARMAX Modeling Scheme for Forecasting Air Conditioning System Performance
,”
Energy Convers. Manage.
,
48
(
8
), pp.
2276
2285
.
10.
Scotton
,
F.
,
Huang
,
L.
,
Ahmadi
,
S.
, and
Wahlberg
,
B.
,
2013
, “
Physics-Based Modeling and Identification for HVAC Systems
,”
2013 European Control Conference
(
ECC
), Zurich, Switzerland, July 17–19, pp.
1404
1409
.http://www.nt.ntnu.no/users/skoge/prost/proceedings/ecc-2013/data/papers/0074.pdf
11.
Malisani
,
P.
,
Chaplais
,
F.
,
Petit
,
N.
, and
Feldmann
,
D.
,
2010
, “
Thermal Building Model Identification Using Time-Scaled Identification Models
,” 49th
IEEE
Conference on Decision and Control
, Dec. 15–17, pp.
308
315
.
12.
EnergyPlus
, 2015, “
EnergyPlus Energy Simulation Software Version: 7-2-0
,” U.S. Department of Energy, Golden, CO.
13.
Chasparis
,
G.
, and
Natschläger
,
T.
,
2014
, “
Nonlinear System Identification of Thermal Dynamics in Buildings
,”
2014 European Control Conference
(
ECC
), June 24–27, pp.
1649
1654
.
14.
Karnopp
,
D.
,
Margolis
,
D.
, and
Rosenberg
,
R.
,
2012
,
System Dynamics: Modeling, Simulation and Control of Mechatronic Systems
, 5th ed.,
Wiley
,
Hoboken, NJ
.
15.
Thirumaleshwar
,
M.
,
2009
,
Fundamentals of Heat and Mass Transfer
,
Dorling Kindersley (India) Pvt. Ltd.
,
New Delhi, India
.
16.
Karnopp
,
D.
,
1978
, “
Pseudo Bond Graphs for Thermal Energy Transport
,”
ASME J. Dyn. Syst., Meas., Control
,
100
(
3
), pp.
165
169
.
17.
Chasparis
,
G.
, and
Natschläger
,
T.
,
2016
, “
Regression Models for Output Prediction of Thermal Dynamics in Buildings
,” e-print arXiv:1608.03090.
18.
Sayed
,
A.
,
2003
,
Fundamentals of Adaptive Filtering
,
Wiley
, Hoboken,
NJ
.
You do not currently have access to this content.