This document summarizes and compares several building energy simulation programs in terms of their capabilities to couple occupancy information with HVAC energy simulation. It finds that while many programs can perform energy simulation, few systematically analyze the relationship between occupancy and HVAC energy use. It identifies gaps in research and calls for studies that incorporate occupancy data into simulation and evaluate its effects on HVAC energy consumption and the response of HVAC systems to occupancy-based controls. The document also reviews commonly used simulation programs and finds that they use different approaches to model heat transfer, load calculation, occupancy-HVAC connection, HVAC modeling, and simulation, with varying degrees of accuracy, flexibility, and user friendliness.

1. Coupling Occupancy Information with HVAC Energy
Simulation: A Systematic Review of Simulation Tools
Zheng Yang PhD Candidate
http://www.zhengyang.me
Innovation in Integrated Informatics Lab
Informatics for Intelligent Built Environment
Civil and Environmental Engineering Department
University of Southern California

2. Simulation Vs Field Experiment
(Siroky 2012, Pisello 2012, Huang 2013)
Feasible all the time
Alternatives before being implemented
Less expensive and time consuming
Reversed after implemented
Control factors that cannot
be controlled in a field experiment
Evaluate the sole consequences
of one control parameter
Non-intrusion
Output different levels of results
Easier for analysts to interpret results
Advise case-by-case design
Advantages
Virtual representation and reproduction of energy processes

3. DOE Building Energy Software Tools Directory with 405 programs
• Whole Building Analysis
• Codes and Standards
• Materials, Components, Equipment and Systems
• Other applications
 Energy simulation
 Renewable Energy
 Retrofit Analysis
 Sustainability/Green Buildings
Source: http: apps1.eere.energy.gov/buildings/toos_directory/
100+ Programs

4. Literature Review and Gap Analysis
Simulation ≠ Real Energy Consumption
Research Gaps
NO research - systematically analyze the coupling of
occupancy and HVAC energy simulation
(Yan 2008, Waddell 2010, Henninger 2010, Crawley 2008, Zhu 2012, Andolsun 2008)
• Accuracy and reliable of simulation programs;
• Advantages and disadvantages of simulation programs;
Comparison
Study
• Effects of occupancy on HVAC energy consumption;
• HVAC response to occupancy based HVAC controls;
Discrepancies from different programs

5. First Principle
Thermodynamics
Interior Impacts
Exterior Impacts

6. Radiation
Convection

7. Figure. The importance of occupant in HVAC energy consumption
Occupancy and HVAC
+ Conditioning RequirementHeat Gain

8. Demand-driven HVAC Control
Heat
Balance
HVAC
Modeling
Load
Calculation
Occupancy HVAC
Connection
HVAC
Simulation
Occupancy
Heat Gain
Conditioning
Requirement
Importance of Occupancy
Reduce HVAC Energy
Consumption
Occupant Comfort and
Building Functionality
Effects of Occupancy on
HVACEnergy Consumption
HVAC Response to Occupancy-
based Control Strategies
Simulation
Program
Coupling Occupancy with HVAC Energy Simulation
Figure Occupancy and building HVAC energy simulation

9. Commonly used Simulation Programs
1
2
Base case and reference buildings
Test bed building in different programs
Lack actual occupancy information
Different input requirements bring additional
deviations and uncertainties
Theoretical Comparison

10. SYSTEMSLOADS PLANTS
Occupancy
BDL
ECONS
Figure. Energy simulation in DOE-2 (arrow shows the flow of information)
Sequential + No Feedback
DOE-2
Figure. eQuest Graphic Interface

11. Heat transfer and balance Static space temperature
No strict heat balance
Four heat transfer surfaces
Load Calculation
System component loads
Simplify system issues
Customized weight factors
Occupancy-HVAC connection
Sequential loads calculation
Limited feedback
Lack of loads update
HVAC Modeling
Predefined system types
Limited sources
Strict requirements
HVAC Simulation
LSPE sequence
Constant temperature
Condition at previous time

12. EnergyPlus
Figure. OpenStudio Graphic Interface
Heat transfer and balance Load Calculation Occupancy-HVAC connection
State space method
Strict heat balance
Predict-correct process
Feedback and update
Incorporate with previous time
Surface and air heat balance

13. Figure. Energy simulation in EnergyPlus (arrow shows the flow of information)
Simultaneous + Update
SYSTEMS
LOADS
Occupancy
Manager
ECONS PLANTS
Customized performance curve
ModularityHVAC Modeling
Air loops
Water loops
HVAC Simulation

14. Figure. IES-VE Graphic Interface
IES-VE
Apache Thermal
ModuleModules
ModelIT
Module
SunCast
Module
RadianceIES
Module
Simulex
Module
IndusPro
Module
MacroFlo
Module
VISTA
Module
….
Occupancy
ApacheSim ApacheCalc ApacheLoadApacheHVAC
VISTA
MacroFlo

15. H
Heat transfer and balance
One- dimension conduction
Uniform thermal condition
Stirred tank temperature
L
Load Calculation
Dynamic Loads
Air nodes to space
Heat transfer and balance
O
Occupancy-HVAC connection
Occupancy profile
Admittance technique
No variant internal loads
H
HVAC Modeling
Pre-defined wizards
System prototyping autosizing
Customized components
S
HVAC Simulation
Simultaneous solution
Simulation with airflow analysis
ApacheSim, ApacheHVAC and Macroflo

16. TRNSYS
Figure. TRNSYS Graphic Interface
mechanical and electrical system simulationTransient
Component based simulation
DLL (dynamic link library) structure
Co-simulation with other programs

17. Simulation of individual components
Acyclic flow or loop
Simultaneous convergence
TRNSYS
H L
O
M S
Heat transfer and balance Load Calculation
Occupancy-HVAC connection
HVAC Modeling HVAC Simulation
Multiple air nodes
Iterations of components
Utility components
Building components
Customized DLLs
Input-output link
Runtime calls from outside
Standard libraries
Development by programming
Occupancy
Lab Dll
Input
TRNDll
TRNExe
Call Component
Equation Solver
Simulated Output

18. ESP-r
Figure. ESP-r Graphic Interface
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Physics Modeling
Computational Fluid
Dynamics Building System
Simulation
Open Source
+ Research Oriented

19. Heat transfer and balance
Load Calculation
Occupancy-HVAC connection
HVAC Modeling HVAC Simulation
Heat gain - thermal network
Integrated with air fluid dynamics
Data exchange with HVAC network
Crank-Nicholson difference
Finite difference nodes
Energy flow control volume
Interconnected nodal network
Component Interdependency
Equation set for load state
Assembly of components
Standard libraries
Network connections
Individual network solver
Finite difference method
Convergence of all networks
Occupancy
Airflow
Network
Building Thermal
Network
HVAC Network

20. Conceptual energy simulation
Linear system – sequential simulation
High computational efficiency
Shallow learning curve

21. Manage simulation parameters
Thermal-dynamics
Real-time heat balance
Accurate temperature estimate
Simultaneous simulation
Back forward feedback and update
Shallow learning curve

22. Integrated model
Efficient for large and complex system
Less knowledge requirement
Shallow learning curve
Different modules for loads calculation
Inaccurate occupancy- associated loads
Fail to specify certain HVAC settings

23. No assumption or default
Flexibility and customization
Open Source and component based
Cannot differentiate occupancy impacts
Steep learning curve
Requirement for system settings

24. Research oriented
Flexible and holistic
Accurate simulation of network interactions
Lack autosized and default setting
Fail in complicated and tentative tasks
Steep learning curve
Knowledge for thermal dynamics and physics

25. Multi-level
1
Dual Level Accuracy
Macro level: Overall energy - a building or a building system;
Micro level: Decompose energy consumption - functionality;
Robustness
2
Robustness
Robust to the changes resulting from the HVAC being
operated differently
Calibration Framework
1. Initial energy modeling;
2. Sensitivity analysis;
3. Parameter estimation;
4. Discrepancy analysis;
5. Discrepancy minimization;
1
2
3
4
5
Five main steps:

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GPU-accelerated supercompuater
Ranked 5th in the nation
Figure. HPCC Source: USC Website

27. THANK YOU !