This paper presents a co-simulation platform which combines a building simulation tool with a cyber-physical systems (CPS) approach. Residential buildings have a great potential of energy reduction by controlling home equipment based on usage information. A CPS can eliminate unnecessary energy usage on a small, local scale by autonomously optimizing equipment activity, based on sensor measurements from the home. It can also allow peak shaving from the grid if a collection of homes are connected. However, lack of verification tools limits effective development of CPS products. The present work integrates EnergyPlus, which is a widely adopted building simulation tool, into an open-source development environment for CPS released by the National Institute of Standards and Technology (NIST). The NIST environment utilizes the IEEE high-level architecture (HLA) standard for data exchange and logical timing control to integrate a suite of simulators into a common platform. A simple CPS model, which controls local heating, ventilation, and cooling (HVAC) temperature set-point based on environmental conditions, was tested with the developed co-simulation platform. The proposed platform can be expanded to integrate various simulation tools and various home simulations, thereby allowing for cosimulation of more intricate building energy systems.

References

References
1.
Nguyen
,
T. A.
, and
Aiello
,
M.
,
2013
, “
Energy Intelligent Buildings Based on User Activity: A Survey
,”
Energy Build.
,
56
, pp.
244
257
.
2.
Griffor
,
E. R.
,
Greer
,
C.
,
Wollman
,
D. A.
, and
Burns
,
M. J.
,
2017
, “Framework for Cyber-Physical Systems: Volume 1 Overview,” National Institute of Standards and Technology, Rockville, MD, Report No.
1500-201
.https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.1500-201.pdf
3.
Lawrence Livermore National Laboratory
,
2016
, “
Energy Flow Charts: Charting the Complex Relationships Among Energy, Water, and Carbon
,” Lawrence Livermore National Laboratory, Livermore, CA, accessed Dec. 18, 2018, https://flowcharts.llnl.gov/
4.
Alhafidh
,
B. M. H.
, and
Allen
,
W. H.
,
2017
, “
High Level Design of a Home Autonomous System Based on Cyber Physical System Modeling
,” Institute of Electrical and Electronics Engineers, Piscataway, NJ, p.
45
.
5.
Hong
,
T.
,
Sun
,
H.
,
Chen
,
Y.
,
Taylor-Lange
,
S. C.
, and
Yan
,
D.
,
2016
, “
An Occupant Behavior Modeling Tool for Co-Simulation
,”
Energy Build.
,
117
, pp.
272
281
.
6.
Terpening
,
E. D.
, and
Littleton
,
A.
,
2017
, “
The State of Internet of Things in the Home—Part II: Opportunities and Challenges for Brands Selling Iot Products for the Home
,” Altimeter Group, San Mateo, CA,
Report
.https://www.slideshare.net/Altimeter/state-of-internet-of-things-in-the-home-part-2-report-preview
7.
Samanta
,
A.
,
Saha
,
S.
,
Biswas
,
J.
, and
Dutta
,
A.
,
2014
, “
Evaluation of Impact of Shading Devices on Energy Consumption of Buildings in Tropical Regions
,”
ASME J. Energy Resour. Technol.
,
136
(
2
), p.
024503
.
8.
Ma
,
S.
,
Zhou
,
D.
,
Zhang
,
H.
,
Weng
,
S.
, and
Shao
,
T.
,
2018
, “
Modeling and Operational Optimization Based on Energy Hubs for Complex Energy Networks With Distributed Energy Resources
,”
ASME J. Energy Resour. Technol.
,
141
(
2
), p.
022002
.
9.
Wong
,
K. V.
, and
Chan
,
R.
,
2013
, “
Smart Glass and Its Potential in Energy Savings
,”
ASME J. Energy Resour. Technol.
,
136
(
1
), p.
012002
.
10.
Oyarzábal
,
B.
,
von Spakovsky
,
M. R.
, and
Ellis
,
M. W.
,
2004
, “
Optimal Synthesis/Design of a Pem Fuel Cell Cogeneration System for Multi-Unit Residential Applications–Application of a Decomposition Strategy
,”
ASME J. Energy Resour. Technol.
,
126
((
1
), pp.
30
39
.
11.
Gunes
,
M. B.
, and
Ellis
,
M. W.
,
2003
, “
Evaluation of Energy, Environmental, and Economic Characteristics of Fuel Cell Combined Heat and Power Systems for Residential Applications
,”
ASME J. Energy Resour. Technol.
,
125
(
3
), pp.
208
220
.
12.
Priedeman
,
D. K.
, Mem. ASME,
Garrabrant
,
M. A.
,
Mathias
,
J. A.
,
Stout
,
R. E.
, and
Christensen
,
R. N.
,
2001
, “
Performance of a Residential-Sized GAX Absorption Chiller
,”
ASME J. Energy Resour. Technol.
,
123
(
3
), pp.
236
241
.
13.
Al-Hadban
,
Y.
,
Sreekanth
,
K. J.
,
Al-Taqi
,
H.
, and
Alasseri
,
R.
,
2017
, “
Implementation of Energy Efficiency Strategies in Cooling Towers—A Techno-Economic Analysis
,”
ASME J. Energy Resour. Technol.
,
140
(
1
), p.
012001
.
14.
Panna
,
R.
,
Thesrumluk
,
R.
, and
Chantrapornchai
,
C.
,
2013
, “
Development of Energy Saving Smart Home Prototype
,”
Int. J. Smart Home
,
7
(
1
), pp.
47
66
https://pdfs.semanticscholar.org/0bfc/42e9d9be9c242f1b33f2d1ab53a20ed6a923.pdf.
15.
Bustamante
,
S.
,
Castro
,
P.
,
Laso
,
A.
,
Manana
,
M.
, and
Arroyo
,
A.
,
2017
, “
Smart Thermostats: An Experimental Facility to Test Their Capabilities and Savings Potential
,”
Sustainability
,
9
(
8
), p.
1462
.
16.
Kontes
,
G. D.
,
Giannakis
,
G. I.
,
Horn
,
P.
,
Steiger
,
S.
, and
Rovas
,
D. V.
,
2017
, “
Using Thermostats for Indoor Climate Control in Office Buildings: The Effect on Thermal Comfort
,”
Energies
, 2017,
10
(
9
), p.
1368
.
17.
Roth
,
T.
,
Song
,
E.
,
Burns
,
M.
,
Neema
,
H.
, and
Emfinger
,
W.
,
2017
, “
Cyber-Physical System Development Environment for Energy Applications
,”
ASME
Paper No. ES2017-3589
.
18.
IEEE
,
2010
, “
IEEE Standard for Modeling and Simulation (M&S) High Level Architecture (HLA)–Framework and Rules
,” Institute of Electrical and Electronics Engineers, Piscataway, NJ, Standard No.
1516-2010
.
19.
U.S. DOE, BTO, and NREL
,
2017
, “
EnergyPlus
,” Department of Energy's, Building Technologies Office and National Renewable Energy Laboratory, Philadelphia, PA, accessed Dec. 18, 2018, https://energyplus.net/
20.
Hong
,
T.
, and
Lin
,
H.-W.
,
2013
, “
Occupant Behavior: Impact on Energy Use of Private Offices
,” Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, CA, Paper No.
LBNL-6128E
.https://www.osti.gov/servlets/purl/1172115
21.
Liu
,
Y.
,
Qiu
,
B.
,
Fan
,
X.
,
Zhu
,
H.
, and
Han
,
B.
,
2016
, “
Review of Smart Home Energy Management Systems
,”
Energy Procedia
,
104
, pp.
504
508
.
22.
Modelisar
,
2010
, “
Functional Mock-Up Interface for Co-Simulation v1.0 (Documentation)
,” Modelica Association, Linkoping, Sweden, accessed Dec. 18, 2018, https://fmi-standard.org/
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