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Definition and Simulation ofOccupant Behavior in Buildings
Definition and Simulation ofOccupant Behavior in Buildings
Da YanTsinghua University, China
Tianzhen HongLawrence Berkeley Lab, USA
Nov 14, 2013
Dublin, Ireland
Page 2
BackgroundBackground
• Large gaps between field data and simulation result
Source: NBI report 2008Energy Performance of LEEDFor New Construction Buildings
Page 3
BackgroundBackground
• building energy is not only affected by climate and system
Ref.: SBI/Aalborg University
Energy Use in Danish Single Family Houses – By year of construction
Page 5
BackgroundBackground
• OB has significant influence on building energy use
0123456789
101112131415
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
住户编号
空调
能耗
指标 (
kWh/m
2 )
平均值 2.3 kWh/m2 Average 2.3kWh/m2
Ene
rgy
Con
sum
ptio
n of
Coo
ling
Sys
tem
(kW
h/m
2)
Apartment No.
0123456789
101112131415
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
住户编号
空调
能耗
指标 (
kWh/m
2 )
平均值 2.3 kWh/m2 Average 2.3kWh/m2
Ene
rgy
Con
sum
ptio
n of
Coo
ling
Sys
tem
(kW
h/m
2)
Apartment No.
Elec
tric
ity C
onsu
mpt
ion
of C
oolin
g Sy
stem
0123456789
101112131415
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
住户编号
空调
能耗
指标 (
kWh/m
2 )
平均值 2.3 kWh/m2 Average 2.3kWh/m2
Ene
rgy
Con
sum
ptio
n of
Coo
ling
Sys
tem
(kW
h/m
2)
Apartment No.
0123456789
101112131415
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
住户编号
空调
能耗
指标 (
kWh/m
2 )
平均值 2.3 kWh/m2 Average 2.3kWh/m2
Ene
rgy
Con
sum
ptio
n of
Coo
ling
Sys
tem
(kW
h/m
2)
Apartment No.
Elec
tric
ity C
onsu
mpt
ion
of C
oolin
g Sy
stem
The statistics energy consumption of cooling system in different apartments of one residential building in Beijing,2006
Significant discrepancy between each apartment
Page 7
Importance and UrgencyImportance and Urgency
• OB is a Key factor for design optimization, energy diagnosis and
performance evaluation, and also building energy simulation
• Limited understanding or inadequate over-simplification on OB;
• In-depth quantitative analysis urgently needed;
• Over 20 groups all over the world studying OB individually
• Lack of consensus in common language, in good experimental design, and
in modeling methodologies.
• An international cooperation is extremely important for both knowledge
gaining and data sharing
Page 8
Importance and UrgencyImportance and Urgency
Simulated Result
Measured Data?
OCCUPANTBEHAVIORBuilding Energy Use
estimationBuilding Technology
evaluation
Page 9
ChallengesChallenges
• Focus on how OB physically and quantitatively affect on building performance
Page 10
ChallengesChallenges
• Stochastic and uncertainty
Family A Family B
Turn off
Turn off
8 : 00
Turn on
Turn on
0 : 00ONOFF
Page 11
ChallengesChallenges
• Diversity of OB
Other responses include: complain, contact facilities department, keep blankets and sweaters within reach, and open windows.
IFMA 2009 HVAC Survey of IFMA members in US and Canada with 452 responses from 3357 samples
Page 14
Research TargetResearch Target
• Identify quantitative definition, description and classification of OB
• Develop effective simulation methodologies of OB
• Integrated OB models with building energy simulation tools
• Demonstrate the OB models in design, evaluation, operation management and policy making by case studies
Page 15
Research TargetResearch Target
Develop a scientific framework for OB quantitative definition and simulation methodologies
Page 16
Research TargetResearch Target
Description
QuestionnaireInterview
Measurement
Measured action data &
environmental parameters
Model
Simulate action data
Real Actions
Page 17
Research TargetResearch Target
Set up Common Description and Definition for OB
Common Description & Definition
DesignResearch PolicyLabelling
RepresentationData Collection Modelling
Page 18
Technical ApproachTechnical ApproachTargeting Building types:
Residential buildings & Office buildings
Occupant movement and
presence
Action Model in residential buildings
Action Model in commercial
buildings
Integration of OB model with
simulation tools
Demonstration of the applications of
OB models
Sub-Task A Sub-Task B Sub-Task C
Sub-Task D
Sub-Task E
Fundamental Research
Practical Application
Page 19
ST-A ST-A Personnel presence and movement model
Occupant’s presence and movement is strongly connected with Space, Time and Events
PersonalPresence & Movement
Page 20
ST-A ST-A Personnel presence and movement model
A set of coherent personnel presence models are demanded for different application purposes
Page 21
ST-B ST-B Action model in residential buildings
Occupant’s actions are influenced by environmental and physical parameters in a stochastic way
Page 22
ST-B ST-B Action model in residential buildings
ActionModel
ObjectState
OBCharacteristic
Parameter
Object StateChange
State based Action Based
Action based models has more advantage to exhibit the relationship between OB phenomenon and physical driven force
Page 23
ST-C ST-C Action model in commercial buildings
0.006
0.095
0.163
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
Single Office Medium Office Large Office
kWh/
m2 /
day
Lighting energy consumption
Higher possibility of interaction and negotiation among occupants in commercial buildings
Page 24
ST-C ST-C Action model in commercial buildings
OccupantsOperation Manager
Assignment of the Control Authority between Occupants and Operation Managers affects performance significantly
CentralizedControl
DecentralizedControl
Page 25
ST-D ST-D Integration with simulation software
OB XML schema
Software module
EnergyPlus DeST
Designbuilder
ESP-r TRNSYS
DOE-2 ……
BEM PorgramsTools to be developed
Integration
Essential to integrate the OB models with BEMs to exhibit the influence of OB on building energy and performance
Page 26
ST-D ST-D Integration with simulation software
Develop flexible, sustainable, robust module for simulation
Page 27
ST-E ST-E Applications of OB models
To exhibit OB’s influence on comfort, environment, energy usage and technology adaptability, improve applications by case studies & guidelines
Page 28
Outcomes & AudienceOutcomes & Audience
Outcomes Target Audience
AStandard definition, description and classification of occupant behaviour in building
Building Energy ResearchersEnergy Modellers
Simulation Software DevelopersB
Systematic measurement approach, simulation modelling and validation methodology
COccupant Behavior Database with data of different temporal and spatial resolution
DSoftware to simulate OB, integrated with a building thermal and energy model
Building DesignersEnergy Saving Evaluators
HVAC EngineersSystem Operators
Energy Policy MakersE
Case studies and guidelines to demonstrate applications of the new OB definitions and models
Page 29
International Workshop for New ANNEXInternational Workshop for New ANNEX
• August 23rd, 2013 at IEA HQ in Paris• 24 participants from 13 countries• One day’s presentation and discussion about the scope of
work, technical approach and next steps
Page 30
Forum in ISHVAC 2013Forum in ISHVAC 2013
• Oct 21st, 2013• Xi’an, China• Half day with 10 presentations• 40 participants from 6 countries
Page 31
ParticipantsParticipants 24 Countries and Regions
Australia Austria Belgium Brazil Canada China
Denmark Finland France Germany HongKong Hungary
Italy Japan Korea Netherland Norway Poland
Spain Sweden Swiss UK USA Singapore
Page 32
ParticipantsParticipants
• 24 Nations or Regions, 57 institutions
• 73 participants, plus 14 participants want to be kept informed
• University, research institute, software company, design consultant company, operation manager, system control company
• ASHRAE has confirmed to join this project, CIBSE is considering participation
Page 33
TRA (10 countries)
• Technology 1: Methods to describe and model occupant behavior in buildings (TRL 3)
• Technology 2: Integration of the definition and models of occupant behavior with current building energy modelling programs (TRL 2)
• Technology 3: Application of the definition and models of occupant behavior in residential and commercial buildings to improve design, operation, and retrofit of buildings (TRL 3)
Page 34
WORK PLANWORK PLAN
• Preparation phase
– Half a year (2013.11 — 2014.6)
• Working phase
– Two and a half years (2014.7 —
2016.12)
• Reporting phase
– Half a year (2017.1 — 2017.6)
2013.11 2014.6 2015.6 2016.12 2017.6
Preparation phase
Working phase
Reporting phase
Page 35
SummarySummary
• OB has great influence on building energy usage and also
technology evaluation
• There are still lack of quantitative methods and common
language for OB description and simulation
• This proposal is focused on setting up a scientific framework
for OB definition, description, simulation and applications