Modeling Multiple Occupant Behaviors In Buildings For Increased Simulation Accuracy

143 Pages·2014·7.25 MB·English

by  Yoon Soo Lee

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Publicly Accessible Penn Dissertations
2013
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Yoon Soo Lee
University of Pennsylvania, [email protected]
Follow this and additional works at: https://repository.upenn.edu/edissertations
Part of the Architectural Engineering Commons, and the Social and Behavioral Sciences Commons
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Lee, Yoon Soo, "Modeling Multiple Occupant Behaviors in Buildings for increased Simulation Accuracy: An
Agent-Based Modeling Approach" (2013). Publicly Accessible Penn Dissertations. 885.
https://repository.upenn.edu/edissertations/885
This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/885
For more information, please contact [email protected].
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The dissertation addresses the limitation of current building energy simulation programs in accounting
for occupant behaviors, which have been identified as having significant impact on the overall building
energy performance. It introduces a new simulation methodology using an agent- based modeling
approach that helps to both predict real-world occupant behaviors observed in an operating building and
to calculate behavior impact on energy use and occupant comfort. A series of experiments has been
conducted using the new methodology and yielded simulation results that not only distinguish
themselves from current simulation practices, but also uncover emerging phenomena that enhance the
insights on building dynamics.
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Dissertation
DDeeggrreeee NNaammee
Doctor of Philosophy (PhD)
GGrraadduuaattee GGrroouupp
Architecture
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Ali M. Malkawi
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David E. Leatherbarrow
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agent-based modeling, building simulation, building technology, energy efficiency, human behavior,
simulation coupling
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Architectural Engineering | Architecture | Social and Behavioral Sciences
This dissertation is available at ScholarlyCommons: https://repository.upenn.edu/edissertations/885
MODELING MULTIPLE OCCUPANT BEHAVIORS IN BUILDINGS FOR INCREASED
SIMULATION ACCURACY: AN AGENT-BASED MODELING APPROACH
Yoon Soo Lee
A DISSERTATION
in
Architecture
Presented to the Faculties of the University of Pennsylvania
in
Partial Fulfillment of the Requirements for the
Degree of Doctor of Philosophy
2013

Supervisor of Dissertation
_______________________
Ali M. Malkawi
Professor, Architecture

Graduate Group Chairperson
________________________
David E. Leatherbarrow, Professor, Architecture

Dissertation Committee
Barry G. Silverman Professor, Electrical and Systems Engineering
Yun Kyu Yi Assistant Professor, Architecture
MODELING MULTIPLE OCCUPANT BEHAVIORS IN BUILDINGS FOR INCREASED
SIMULATION ACCURACY: AN AGENT-BASED MODELING APPROACH
COPYRIGHT
2013
Yoon Soo Lee
This work is licensed under the
Creative Commons Attribution-
NonCommercial-ShareAlike 3.0
License

To view a copy of this license, visit
http://creativecommons.org/licenses/by-ny-sa/2.0/
Dedication

To my loving family
for their unconditional support
and
tolerance throughout this
LONG
journey.

iii
ABSTRACT

MODELING MULTIPLE OCCUPANT BEHAVIORS IN BUILDINGS FOR INCREASED
SIMULATION ACCURACY: AN AGENT-BASED MODELING APPROACH

Yoon Soo Lee
Ali M. Malkawi
The dissertation addresses the limitation of current building energy simulation programs in
accounting for occupant behaviors, which have been identified as having significant impact on the
overall building energy performance. It introduces a new simulation methodology using an agent-
based modeling approach that helps to both predict real-world occupant behaviors observed in an
operating building and to calculate behavior impact on energy use and occupant comfort. A series
of experiments has been conducted using the new methodology and yielded simulation results
that not only distinguish themselves from current simulation practices, but also uncover emerging
phenomena that enhance the insights on building dynamics.

iv
TABLE OF CONTENTS

ABSTRACT
 ...............................................................................................................................
 IV

LIST OF TABLES
 ..................................................................................................................
 VII

LIST OF ILLUSTRATIONS
 ................................................................................................
 VIII

1.
  INTRODUCTION
 ...............................................................................................................
 1

1.1.
  Emergence of Human Behavior in Architecture .............................................................. 1

1.1.1.
  Role of Human Behavior in Energy Conservation ......................................................... 2

1.1.2.
  Human Behavior and Impact on Building Energy Use .................................................. 3

1.2.
  Uncertainties of Human Behavior ..................................................................................... 4

2.
  BACKGROUND
 ................................................................................................................
 7

2.1.
  Literature Review ................................................................................................................ 8

2.2.
  Evolution of Computational Building Simulation .......................................................... 11

2.2.1.
  Social Science Modeling ............................................................................................. 11

2.2.2.
  Simulating Uncertainties .............................................................................................. 14

2.3.
  Human Behavior Research .............................................................................................. 15

3.
  METHODOLOGY
 ...........................................................................................................
 17

3.1.
  Human Behavior in Buildings ......................................................................................... 19

3.2.
  Human Behavior Modeling .............................................................................................. 21

3.2.1.
  Simulative Model ......................................................................................................... 21

3.2.2.
  Reasoned Action Model .............................................................................................. 23

3.3.
  Agent-Based Modeling ..................................................................................................... 29

3.3.1.
  ABM Mindset ............................................................................................................... 30

3.3.2.
  ABM Decision-Making Process ................................................................................... 33

3.3.3.
  ABM Cost Function ...................................................................................................... 36

3.3.4.
  ABM Learning and Interaction ..................................................................................... 39

3.4.
  Simulation Coupling ......................................................................................................... 42

4.
  EXPERIMENTS
 ..............................................................................................................
 46

v
4.1.
  Simulating Behaviors through Dynamic Schedules ..................................................... 46

4.1.1.
  Introduction .................................................................................................................. 47

4.1.2.
  Methodology ................................................................................................................ 49

4.1.3.
  Case Study .................................................................................................................. 53

4.1.4.
  Results and Discussion ............................................................................................... 60

4.2.
  Single Behavior Simulation using ABM ......................................................................... 61

4.2.1.
  Introduction .................................................................................................................. 62

4.2.2.
  Methodology ................................................................................................................ 63

4.2.3.
  Simulation Experiment ................................................................................................. 65

4.2.4.
  Results and Discussion ............................................................................................... 69

4.3.
  Multiple Behavior Simulation using ABM ...................................................................... 74

4.3.1.
  Introduction .................................................................................................................. 75

4.3.2.
  Agent-Based Modeling Overview ................................................................................ 75

4.3.3.
  Methodology ................................................................................................................ 76

4.3.4.
  Experiment and Simulation Results ............................................................................. 81

4.3.5.
  Results and Discussion ............................................................................................... 87

4.4.
  ABM Sensitivity Analyses ................................................................................................ 88

4.4.1.
  Sensitivity to Different Weather Conditions ................................................................. 88

4.4.2.
  Sensitivity to Different Agent Populations .................................................................... 91

4.4.3.
  Sensitivity to Multi-Zone Space ................................................................................... 97

5.
  CONCLUSION
 .............................................................................................................
 102

APPENDIX A. SUMMARY OF CURRENT HUMAN BEHAVIOR RESEARCH
 107

APPENDIX B. SURVEY QUESTIONS FOR WINDOW USE BEHAVIOR
 .......
 110

APPENDIX C. USER-DEFINED INPUT FOR ABM
 ................................................
 112

APPENDIX D. PMV PARAMETERS IN THE ABM
 .................................................
 114

APPENDIX E. SIMULATION COUPLING PROCEDURE
 .....................................
 119

APPENDIX F. ABM CLASS DIAGRAM
 .....................................................................
 125

BIBLIOGRAPHY
 ..................................................................................................................
 127

INDEX
 .....................................................................................................................................
 132

v i
LIST OF TABLES

Table 3.1 Four basic levels of knowledge ....................................................................... 21

Table 4.1 EnergyPlus simulation results for the case study ............................................ 60

Table 4.2 List of behaviors and relevant PMV parameter (behavior trigger) ................... 76

Table 4.3 List of behaviors and belief values .................................................................. 78

Table 4.4 Analyses on behavior priority .......................................................................... 84

Table 4.5 Behavior sets optimized for energy savings and comfort (Philadelphia, PA) .. 86

Table 4.6 Behavior sets optimized for energy savings and comfort (San Francisco, CA)
................................................................................................................................. 90

Table 4.7 Behavior sets optimized for energy savings and comfort (Phoenix, AZ) ........ 90

Table 4.8 Behavior sets optimized for energy savings and comfort (Calgary, Canada) . 90

Table 4.9 Comparison of energy and comfort performances by climate conditions and
zone division .......................................................................................................... 101

Table A.1 State of the art in current human behavior research .................................... 107
Table C.1 Clothing level categorization [ASHRAE Thermal Comfort (Table 7)] ........... 114

Table C.2 Metabolic activity level categorization [ASHRAE Thermal Comfort (Table 4)]
............................................................................................................................... 114

v ii
LIST OF ILLUSTRATIONS

Figure 2.1 Research interest and objective ....................................................................... 8

Figure 3.1 Core elements of the research ....................................................................... 17

Figure 3.2 Definition of behavior used in the dissertation ............................................... 20

Figure 3.3 Influence diagram of research objective and behavior components .............. 22

Figure 3.4 Schematic diagram of the Reasoned Action Model ....................................... 24

Figure 3.5 Process diagram for human behavior model construction [Fishbein et al.,
2010] ........................................................................................................................ 25

Figure 3.6 Comparison between existing and proposed ABM process for simulating
window use behavior ............................................................................................... 31

Figure 3.7 Main ABM function (decision-making process and simulation coupling) ....... 34

Figure 3.8 PMV and agent behaviors .............................................................................. 35

Figure 3.9 Examples of causal model between the reasoned action model and belief on
comfort ..................................................................................................................... 37

Figure 3.10 ABM interpretation of agent learning and interaction ................................... 41

Figure 3.11 Agent decision-making process linked with agent learning and agent
interaction ................................................................................................................ 42

Figure 3.12 Overview of data exchange from simulation coupling (between ABM and
EnergyPlus) ............................................................................................................. 44

Figure 3.13 All-encompassing research process ............................................................ 45

Figure 4.1 A detailed process of the ‘Dynamic Schedule’ ............................................... 49

Figure 4.2 ‘Schedule Generation’ process for routine meetings ..................................... 50

Figure 4.3 Schedule prediction model for routine meetings ............................................ 53

Figure 4.4 Daily and weekly schedule generated by the ‘Schedule Generation’ process
................................................................................................................................. 54

Figure 4.5 Class diagram for converting schedules for building energy simulation
programs .................................................................................................................. 56

Figure 4.6 Simulation results comparison – ASHRAE, actual, and dynamic schedule ... 58

Figure 4.7 (a) Dynamically generated daily schedules, distribution and average (n=100),
(b) Schedule comparison – ASHRAE, actual, and dynamic schedule ..................... 59

vi ii