An overview of commonly used methodologies based on the artificial intelligence approach is provided with a special emphasis on neural networks, fuzzy logic, and genetic algorithms. A description of selected applications to building energy systems of AI approaches is outlined. In particular, methods using the artificial intelligence approach for the following applications are discussed: Prediction energy use for one building or a set of buildings (served by one utility), Modeling of building envelope heat transfer, Controlling central plants in buildings, and Fault detection and diagnostics for building energy systems.

1.
Kreider
,
J. F.
, and
Wang
,
X. A.
,
1992
, “
Improved Artificial Neural Networks for Commercial Building Energy Use Prediction
,”
ASME J. Sol. Energy Eng.
,
114
(
4
), pp.
361
366
.
2.
Anstett
,
M.
, and
Kreider
,
J. F.
,
1993
, “
Application of Artificial Neural Networks to Commercial Energy Use Prediction
,”
ASHRAE Trans.
,
99
(
1
), pp.
505
517
.
3.
Gibson
,
F. J.
, and
Kraft
,
T. T.
,
1993
, “
Electric Demand Prediction Using Artificial Neural Network Technology
,”
ASHRAE J.
,
35
(
3
), pp.
60
68
.
4.
Curtiss
,
P. S.
,
1997
, “
Examples of Neural Networks Used for Building System Control and Energy Management
,”
ASHRAE Trans.
,
103
(
2
), pp.
909
913
.
5.
Dodier, R., and Henze, G., 1996, “Statistical Analysis of Neural Networks as Applied to Building Energy Prediction,” Proc. of the ASME ISEC, San Antonio, TX, pp. 495–506.
6.
Kreider
,
J. F.
,
Blanc
,
S. L.
,
Kammerud
,
R. C.
, and
Curtiss
,
P. S.
,
1997
, “
Operational Data as the Basis for Neural Network Prediction of Hourly Electrical Demand
,”
ASHRAE Trans.
,
103
(
2
), pp.
926
934
.
7.
Kreider
,
J. F.
,
Claridge
,
D.
,
Curtiss
,
P.
,
Dodier
,
R.
,
Haberl
,
J.
, and
Krarti
,
M.
,
1995
, “
Recurrent Neural Networks for Building Energy Use Prediction and System Identification: A Progress Report
,”
ASME J. Sol. Energy Eng.
,
117
, pp.
161
166
.
8.
Hornik
,
K.
,
Stinchcombe
,
M.
, and
White
,
H.
,
1989
, “
Multilayer Feedforward Networks are Universal Approximations
,”
Neural Networks
,
2
, pp.
359
366
.
9.
Bailey, M. B., 1998, “The Design and Viability of a Probabilistic Fault Detection and Diagnosis Method for Vapor Compression Cycle Equipment,” Ph.D. Thesis, Univ. of Colorado, Boulder, CO.
10.
Massie, D., 1998, “Optimal Neural Network-Based Controller for Ice Storage Systems,” Ph.D. Thesis, Univ. of Colorado, Boulder, CO.
11.
Curtiss
,
P. S.
,
Kreider
,
J. F.
, and
Brandemuehl
,
M. J.
,
1994
, “
Energy management in central HVAC plants using neural network
,”
ASHRAE Trans.
,
100
(
1
), pp.
476
493
.
12.
McClelland, J. L., and Rumelhart, D. E., 1988, Exploration in Parallel Distributed Processing, MIT Press, Cambridge.
13.
Falhman, S. E., 1988, An Empirical Study of Learning Speed in Back-Propagation Networks American Institute of Aeronautics and Astronautics.
14.
Wald
,
A.
,
1943
, “
Test of Statistical Hypotheses Concerning Several Parameters When the Number of Observations is Large
,”
Trans. Am. Math. Soc.
,
54
, pp.
426
482
.
15.
Dodier
,
R. H.
, and
Kreider
,
J. F.
,
1999
, “
Whole Building Energy Diagnostics
,”
ASHRAE Trans.
,
105
(
1
), pp.
579
589
.
16.
Kreider
,
J. F.
, and
Haberl
,
J.
,
1994
, “
Predicting Hourly Building Energy Usage: The Great Predictor Shootout—Overview and Discussion of Results
,”
ASHRAE Trans.
,
100
(
2
), pp.
1104
1118
.
17.
Kohonen
,
T.
,
1982
, “
Self-Organizing Formation of Topologically Correct Feature Maps
,”
Biol. Cybern.
,
43
, pp.
59
69
.
18.
Kohonen, T., 1987, Self-Organizing and Associative Memory, Springer-Verlag, New York, NY.
19.
Hecht-Hielsen
,
R.
,
1987
, “
Nearest Matched Filter Classification of Spatiotemporal Patterns
,”
Appl. Opt.
,
26
, pp.
1892
1899
.
20.
Torella G., and Lombardo, G., 1996, “Neural Networks for the Diagnostics of Gas Turbine Engines,” Proc. ASME Turbo Asia Conf.
21.
Ganguli, R., 2001 “Data Rectification and Detection of Trend Shifts in Jet Engine Gas Path Measurements using Median Filter and Fuzzy Logic,” Proc. of ASME Turbo Expo 2001, New Orleans, LA.
22.
Siu, C., Shen, Q., and Milne, R., 1997, “TMDOCTOR: A fuzzy rule- and case-based expert system for turbomachinery diagnosis,” Proc. of IFAC Fault Detection, Supervision and Safety for Technical Processes, 2, Kingston Upon Hull, UK.
23.
Zurada, J. M., 1992, Introduction to Artificial Neural Networks, West, St Paul, MN.
24.
Holland, J. H., 1975, Adaptation in Natural and Artificial Systems, Univ. of Michigan Press, Ann Arbor, MI.
25.
Goldsberg, D., 1989, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, MA.
26.
Wen
,
F.
, and
Chang
,
C. S.
,
1998
, “
A New Approach to Fault Diagnosis in Electrical Distribution Networks Using a Genetic Algorithm
,”
Artif. Intell. Eng.
,
12
, pp.
69
80
.
27.
Min
,
L.
, and
Cheng
,
W.
,
1999
, “
A Genetic Algorithm for Minimizing the Make-span in the Case of Scheduling Identical Parallel Machines
,”
Artif. Intell. Eng.
,
13
, pp.
399
403
.
28.
Lazzerini
,
B.
, and
Marcelloni
,
F.
,
2000
, “
A Genetic Algorithm for Generating Optimal Assembly Plans
,”
Artif. Intell. Eng.
,
14
, pp.
319
329
.
29.
Lin
,
F. J.
, and
Chou
,
W. D.
,
2003
, “
An Induction Motor Servo Drive using Sliding-Mode Controller with Genetic Algorithm
,”
Electric Power Systems Research
,
64
, pp.
93
108
.
30.
Pham
,
D. T.
, and
Karaboga
,
D.
,
1999
, “
Self-Tuning Fuzzy Controller Design Using Genetic Optimization and Neural Network Modelling
,”
Artif. Intell. Eng.
,
13
, pp.
119
130
.
31.
Chen
,
W. C.
,
Chang
,
N. B.
, and
Chen
,
J. C.
,
2003
, “
Rough Set-Based Hybrid Fuzzy-Neural Controller Design for Industrial Wastewater Treatment
,”
Water Res.
,
37
, pp.
95
107
.
32.
Huang
,
W.
, and
Lam
,
H. N.
,
1997
, “
Using Genetic Algorithms to Optimize Controlle Parameters for HVAC Systems
,”
Energy Build.
,
26
, pp.
277
282
.
33.
Guillemin
,
A.
, and
Morel
,
N.
,
2001
, “
An Innovative Lighting Controller Integrated in Self-Adaptive Building Control System
,”
Energy Build.
,
33
, pp.
477
487
.
34.
Wright
,
J. A.
,
Loosemore
,
H. A.
, and
Farmami
,
R.
,
2002
, “
Optimization of Building Thermal Design and Control by Multi-Criterion Genetic Algorithm
,”
Energy Build.
,
34
, pp.
959
972
.
35.
ASHRAE, 2001, ASHRAE Handbook of Fundamentals, American Society for Heating, Refrigerating, and Air Conditioning, Atlanta, GA.
36.
Kaciauskas
,
A. P.
,
Brody
,
L. R.
,
Hadjimichael
,
M.
,
Bankert
,
R. I.
, and
Tag
,
P. M.
, 1998, “A Fuzzy Expert System to Assist in the Prediction of Hazardous Wind Conditions within the Mediterranean Basin,” Meteor. Appl., 5, pp. 307–320.
37.
Jagadesh
,
A.
,
2000
, “
Comparison of ANN and Empirical Approaches for Predicting Watershed Runoff
,”
Journal of Water Resources Planning and Management
,
126
(
3
), pp.
156
166
.
38.
Salehi, M., and Krarti, M., 2003, “
A NN-based Model to Predict 24-ahead Weather Conditions,” Meteo. Appl., (submitted
).
39.
Krarti
,
M.
,
Kreider
,
J. F.
,
Cohen
,
D.
, and
Curtiss
,
P.
,
1998
, “
Estimation of Energy Savings for Building Retrofits Using Neural Networks
,”
ASME J. Sol. Energy. Eng.
,
120
(
3
), pp.
211
216
.
40.
Taylor
,
J. W.
, and
Buizza
,
R.
, 2002, “Neural Network Load Forecasting With Weather Ensemble Predictions,” IEEE Transactions on Power Systems, 17(3), pp. 626–632.
41.
Senjyu
,
T.
,
Takara
,
H.
,
Uezato
,
K.
, and
Funabashi
,
T.
, 2002, “One-Hour-Ahead Load Forecasting Using Neural Network,” IEEE Transactions on Power Systems, 17(1), pp. 113–118.
42.
Zhang
,
G.
,
Patuwo
,
B. E.
, and
Hu
,
M. Y.
, 1998, “Forecasting With Neural Networks: The State-of-the-Art,” Int. J. Forecast., 14, pp. 35–62.
43.
Hippert
,
H. S.
,
Pedreira
,
C. E.
, and
Souza
,
R. C.
, 2001, “Neural Networks for Short-Term Load Forecasting: A Review and Evaluation,” IEEE Transactions on Power Systems, 16, pp. 44–55.
44.
Cohen, D., and Krarti, M., 1996, “Prediction of Short-Term Utility Loads using Neural Networks,” JCEM Report 96-17, Univ. of Colorado, Boulder, CO.
45.
Claridge, D. E., 1988, “Design Methods for Earth-Contact Heat Transfer,” Progress in Solar Energy, K. Boer (ed.), American Solar Energy Society, Boulder, CO.
46.
Krarti, M., 1999, “Foundation Heat Transfer,” Advances in Solar Energy, Y. Goswami and K. Boer (eds.), American Solar Energy Society, Boulder, CO.
47.
Krarti, M., 1995, “Comparison of a Neural Network Model With a Regression Model for Foundation Heat Loss Calculation,” Proc. of Thermal Performance of the Exterior Envelopes of Buildings VI, pp. 235–243.
48.
Beausoleil, M., and Krarti, M., 1997, “Neural Network Model for Ground-Coupled Heat Loss Calculation,” Proc. of Building Simulation 97.
49.
Salehi M., and Krarti, M., 2001, “An Evaluation of NN-based Model for the Prediction of Foundation Heat Transfer from Basements,” Proc. of ASME International Mechanical Engineering Congress and Exposition, New York, NY.
50.
Krarti
,
M.
,
Claridge
,
D. E.
, and
Kreider
,
J. F.
,
1988
, “
ITPE Technique Applications to Time Varying Two-Dimensional Ground-Coupling Problems
,”
Int. J. Heat Mass Transfer
,
31
(
9
), pp.
1899
1911
.
51.
Krarti
,
M.
,
Claridge
,
D. E.
, and
Kreider
,
J. F.
,
1990
, “
The ITPE Method Applied to Time-Varying Three-Dimensional Ground-Coupling Problems
,”
ASME J. Heat Transfer
,
112
(
4
), pp.
849
856
.
52.
Kintner-Meyer
,
M.
, and
Emery
,
A. F.
,
1995
, “
Optimal Control of an HVAC System Using Cold Storage and Building Thermal Capacitance
,”
Energy Build.
,
23
(
1
), pp.
19
31
.
53.
Akbari, H., and Sezgen, O., 1992, “Case Studies of Thermal Energy Systems: Evaluation and Verification of System Performance,” LBL-30582, Lawrence Berkeley Laboratory, Univ. of California, Energy and Environment Division, Berkeley, CA.
54.
Tran
,
N.
, and
Kreider
,
J. F.
,
1989
, “
Field Measurements of Chilled Water Storage Thermal Performance
,”
ASHRAE Trans.
,
95
(
1
), pp.
1106
1112
.
55.
Henze
,
G. P.
,
Dodier
,
R.
, and
Krarti
,
M.
,
1997
, “
Development of Predictive Optimal Controller for Thermal Energy Storage Systems
,”
HVAC & R Research
,
3
(
3
), pp.
233
264
.
56.
Drees, K. H., and Braun, J. E., 1994, “Modeling and Control of Area-Constrained Ice Storage Systems,” Report No. 1796-2 HL 94-21, Johnson Controls, Inc.
57.
Zhou, G., Ihm, P., Krarti, M., Liu, S., and Henze, G. P., 2003, “Integration of an Optimization Module Within EnergyPlus,” submitted to IPBSA Conf. 2003.
58.
Glover, F., and Laguna, M., 2000, Tabu Search, Kluwer Academic Publishers, New York, NY.
59.
Pape
,
F. L. F.
,
Mitchell
,
J. W.
, and
Beckman
,
W. A.
,
1991
, “
Optimal Control and Fault Detection in Heating, Ventilating, and Air-Conditioning Systems
,”
ASHRAE Trans.
,
97
(
1
), pp.
729
745
.
60.
Norford
,
L. K.
, and
Little
,
R. D.
,
1993
, “
Fault Detection and Load Monitoring in Ventilation Systems
,”
Int. J. Mol. Sci.
,
99
(
1
), pp.
590
602
.
61.
Ahn
,
B. C.
,
Mitchell
,
J. W.
, and
McIntosh
,
I. B.
,
2001
, “
Model-Based Fault Detection and Diagnosis for Cooling Towers
,”
ASHRAE Trans.
,
107
(
2
), pp.
839
846
.
62.
Rossi
,
T. M.
, and
Braun
,
J. E.
,
1997
, “
A Statistical, Rule-Based Fault Detection and Diagnostic Method for Vapor Compression Air Conditioners
,”
International Journal of HVAC&R
,
3
(
1
), pp.
19
37
.
63.
Stylianou
,
M.
,
1997
, “
Application of Classification Functions to Chiller Fault Detection and Diagnosis
,”
ASHRAE Trans.
,
103
(
1
), pp.
645
656
.
64.
Lee
,
W. Y.
,
House
,
J. M.
, and
Shin
,
D. R.
,
1997
, “
Fault Detection of an Air-Handling Unit Using Residual and Recursive Parameter Identification Method
,”
ASHRAE Trans.
,
103
(
1
), pp.
528
539
.
65.
Ngo
,
D.
, and
Dexter
,
A. L.
,
1999
, “
A Robust Model-Based Approach to Diagnosing Faults in Air-Handling Units
,”
ASHRAE Trans.
,
105
(
1
), pp.
1078
1086
.
66.
Breekweg
,
M. R. B.
,
Gruber
,
P.
, and
Ahmed
,
O.
,
2000
, “
Development of a Generalized Neural Network Model to detect Faults in Building Energy Performance-Part II
,”
ASHRAE Trans.
,
106
(
1
), pp.
74
83
.
67.
Dexter
,
A. L.
, and
Ngo
,
D.
,
2001
, “
Fault Diagnosis in Air-Conditioning Systems: A Multi-Step Fuzzy Model-Based Approach
,”
HVAC&R Research Journal
,
7
(
1
), pp.
83
102
.
68.
Katipamula, S. T., Pratt, R. G., and Braun, J., 2001, “Building Systems Diagnostics and Predictive Maintenance,” Handbook of Heating, Ventilation, and Air Conditioning, J. F. Kreider (ed.), CRC Press, Boca Raton, FL.
69.
Dalton, T., Patton, R. J., and Miller, P. J. H., 1995, “Methods of Fault Detection for a Centrifugal Pump System,” On-Line Fault Detection and Supervision in the Chemical Process Industries, IFAC Workshop, New-Castle Upon Tyne, U.K, Pergamon Press, New York.
70.
Xu
,
C.
, and
Lu
,
Y.
,
1987
, “
Fuzzy Model Identification and Self-Learning for Dynamic Systems
,”
IEEE Trans. Syst. Man Cybern.
,
17
(
4
), pp.
683
689
.
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