definition and simulation of occupant behavior in buildings

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

BackgroundBackground

• Large gaps between field data and simulation result

Source: NBI report 2008Energy Performance of LEEDFor New Construction Buildings


• 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


Courtesy: Danny Parker, FSEC


• OB has significant influence on building energy use

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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.

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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 )


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 )


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 )


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

Occupant behavior is a key factorOccupant behavior is a key factor

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

Importance and UrgencyImportance and Urgency

Simulated Result

Measured Data?

OCCUPANTBEHAVIORBuilding Energy Use

estimationBuilding Technology

evaluation

ChallengesChallenges

• Focus on how OB physically and quantitatively affect on building performance


• Stochastic and uncertainty

Family A Family B

Turn off

Turn off

8 ： 00

Turn on

Turn on

0 ： 00ONOFF


• 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


• Complexity of OB


• Typical OB Category and Distribution

X 10

X 7

X 9

X 12

X 6

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


Develop a scientific framework for OB quantitative definition and simulation methodologies


Description

QuestionnaireInterview

Measurement

Measured action data &

environmental parameters

Model

Simulate action data

Real Actions


Set up Common Description and Definition for OB

Common Description & Definition

DesignResearch PolicyLabelling

RepresentationData Collection Modelling

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

ST-A ST-A Personnel presence and movement model

Occupant’s presence and movement is strongly connected with Space, Time and Events

PersonalPresence & Movement

ST-A ST-A Personnel presence and movement model

A set of coherent personnel presence models are demanded for different application purposes

ST-B ST-B Action model in residential buildings

Occupant’s actions are influenced by environmental and physical parameters in a stochastic way

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

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

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

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

ST-D ST-D Integration with simulation software

Develop flexible, sustainable, robust module for simulation

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

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

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

Forum in ISHVAC 2013Forum in ISHVAC 2013

• Oct 21st, 2013• Xi’an, China• Half day with 10 presentations• 40 participants from 6 countries

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

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

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)

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

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

Thank you for your attention!Thank you for your attention!

definition and simulation of occupant behavior in buildings

Documents

ob quantitative definition

energy diagnosis

energy simulationlimited

backgroundbuilding energy

stb action model

stc action model

ob phenomenon

building performancepage