New thermal comfort and air conditioning behavioral research methods for residential settings

Prof. Richard de DearDr. Christhina Cndido

Thomas Parkinson

Indoor Environmental Quality LaboratoryFaculty of Architecture, Design and Planning, The University of Sydney

History of thermal comfort research

Over 100 years of thermal comfort research Overwhelming majority of that research focused on

office environments, followed by health care environments, schools, vehicular cabins, outdoor and semi-outdoors etc.

Its leap of faith that one set of research findings from one type of environment can be generalized across diverse settings deterministic logic

Whats missing?

These investigations have made great contributions to our understanding of thermal comfort in last 100 years

However, what has been largely missing from the discourse is an understanding of comfort inside residences

Yet we spend most of our lives inside our homes?

Whats so different about homes? Why would we expect residential comfort to be different?

Greater adaptive opportunities Different and more flexible clothing patterns Energy price signal directly affects the comfort consumer Different occupant activities indoors

These contextual factors must influence thermal perceptual processes, yet very little work has been done in this context, because theres no requirement for temperature standardisation

However, there are significant policy drivers relating to the the energy expended in the pursuit of comfort in the residential sector

Policy drivers

Greenhouse emissions In Australia over the last 20 years there has been 40%

growth in direct CO2 emissions from the residential sector

Peak electricity demand Air-conditioning now ranks as one of the fastest

growing end-uses of electricity in Australian residential sector

In New South Wales (incl. Sydney) more than 60% of households now own at least one air-conditioning system

Australian Home Insulation Program

The Energy Efficient Homes Package, which included the Home Insulation Program introduced in 2011

Policy driven by technocrats who ignored the human comfort and behavioral dimensions of heating and cooling related GHG emissions in the residential sector

Again, this was based on deterministic comfort logic: IF comfort stays constant AND housing envelope efficiency increases THEN

electricity demand (incl. peak demand) and greenhouse gas emissions decrease

But the householders behaved quite differently IF housing envelope efficiency increases AND electricity demand (and GHG

emissions) remain static or even increase THEN comfort can increase This is the behavioral economists concept of rebound effect

The Rebound Effect

Defined as The behavioral or other systemic responses to the introduction of new technologies that increase the efficiency of resource use. These behavioral responses tend to offset the beneficial effects of the new technology.

As a result of the rebound effect, actual electricity of GHG savings are significantly less than savings calculated by technocrats using deterministic comfort logic

Why is residential comfort so under-researched?

Its clear that there are many good reasons for understanding thermal comfort in the residential sector better than we do at present, so why are residential comfort studies so rare?

Logistics! In offices, you get permission to obtain objective and

subjective comfort evaluations within a concentrated sample (i.e. its quick and easy!)

Peoples homes are geographically dispersed, scheduling and logistics are difficult, issues with long-term installation of equipment, and the ongoing ethics concern of householder privacy

Previous residential studies Hunt & Gidman (1982) found their data to be

biased from a cold spell during measurement period temporal sampling issues

The Warm Front initiative following the European heat wave had only initial surveys to support half-hourly measurements that lasted 2-4 weeks in each house

Lomas & Kane (2012) reported having only 49% useable data from 312 households after all their missing or incomplete observations were removed

Our new Smart[phone] Approach Phenomenal growth in smartphone penetration over

the past few years (in Australia now 84% and rising) Interactive touch devices offer excellent user

experience Always-on and tethered to their owners Generates data with high spatial and temporal

resolution Footloose respondents dont have to be seated at their

computer desk to complete a questionnaire

Smartphones present a direct, frictionless link between researcher and questionnaire respondent

Introducing Comfort Chimp smartphone questionnaire

Questionnaires created through Online Control Panel Participants receive a personalised SMS invitation containing a

hyperlink to the questionnaire Questionnaires are issued to participants by an SMS gateway

through their local telecom provider (

Comfort Chimp

For our longitudinal research design the comfort questionnaires were designed to be very quick (

Temperature and RH measurements

Maxim iButtons Cheap (US$25), self-sufficient,

hermetically sealed devices 0.5C accuracy 0.5C resolution (8-bit) 3 months storage at 15-min

sampling interval 10 year battery life Temperature + relative

humidity version also available (US$40)

Determining AC usage patterns

iButtons were placed within the occupied zone of different rooms of each house

An iButton was also installed in the supply air vent of the AC terminal unit

Im here!

Defining AC usage

An Excel macro used to determine AC events If dT/dt of AC supply air >|X| then AC was just

switched ON If T between the AC and occupied zone

temperatures is > +X then system is in heating mode;

if < X then system is in cooling mode X is empirically determined for each household

Householder Questionnaire

Contextual information about the house and its occupants obtained at time of iButton installation

Includes descriptions of building physics, householder demographics, householder socio-economics, HVAC equipment (type, installed rooms, capacity, age etc).

Sydney results using this method

220 years of temperature history inside 45 homes 7.65 million data points 2,100 at-home questionnaire responses 4,900 AC events (switch-on) 11,800 hours of AC use

Residential Clothing Insulation Behaviour

0%10%20%30%40%50%60%70%80%90%

100%

0.2clo 0.4clo 0.6clo 1clo

Residential AC events by month

0

100

200

300

400

500

600

700

800

900

Num

ber o

f AC

Even

ts

Cooling Heating

AC duration

0

200

400

600

800

1000

1200

Num

ber o

f AC

Even

ts

Cooling Heating

Time of AC use

Cooling Heating

00:00 - 06:0006:00 - 10:0010:00 - 16:0016:00 - 00:00

AC trigger temperatures

0%

5%

10%

15%

20%

25%

30%

35%

40%

8-10 10-12 12-14 14-16 16-18 18-20 20-22 22-24 24-26 26-28 28-30 30-32 32-34 34-36 36-38

Cooling Heating

Adaptive Comfort

5

10

15

20

25

30

35

40

5 10 15 20 25 30

Indo

or A

C Tr

igge

r Tem

pera

ture

Running Mean Outdoor Temperature

Adaptive Model Compliance Cooling HeatingAbove 80% 23% 0%Below 80% 1% 64%

Within Range 77% 36%

ApresentadorNotas de apresentao90th Percentile Heating = 20.6; Median Heating = 16.710th Percentile Cooling = 23.7; Median Heating = 26.6

Cooling Trigger Temps

0%

5%

10%

15%

20%

25%

30%

35%

40%

20-22 22-24 24-26 26-28 28-30 30-32 32-34

Daytime Night

ApresentadorNotas de apresentaoDaytime = 10AM 4PMNight = 4PM 12AM

Heating Trigger Temps

0%

5%

10%

15%

20%

25%

30%

35%

8-10 10-12 12-14 14-16 16-18 18-20 20-22 22-24 24-26

Morning Night

ApresentadorNotas de apresentaoMorning = 6AM 10AMNight = 4PM 12AM

Bedroom Temps

1012141618202224262830

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Occ

upie

d Zo

ne T

empe

ratu

re (d

egC)

Average Bedroom Temperatures at Night (10PM-7AM)

With AC Without AC

ApresentadorNotas de apresentaoSummertime AC bedroom temperatures on average 23~34degCWintertime bedroom temperatures are warmed by non-AC heating systems

Living Room

1012141618202224262830

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Occ

upie

d Zo

ne T

empe

ratu

re (d

egC)

Average Livingroom Temperatures during the day (7AM-10PM)

With AC Without AC

Average Thermal SensationLiving Rooms

0,0

0,5

1,0

1,5

2,0

23-24 24-25 25-26 26-27 27-28 28-29Indoor Air Temperature (degC)

Without AC With AC

Physics Physiology Psychology Behaviour

Warm

SlightlyWarm

Neutral

73 19 102 26 94 35 67 22 59 19 31 12

Average Thermal SensationLiving Rooms

0,0

0,5

1,0

1,5

2,0

23-24 24-25 25-26 26-27 27-28 28-29Indoor Air Temperature (degC)

Without AC With AC

Warm

SlightlyWarm

Neutral

73 19 102 26 94 35 67 22 59 19 31 12

Psychology Behaviour

Conclusions Context matters! Comfort is not deterministic

(physics > physiology > psychology > behaviour) Residential AC usage patterns are not 100% rational Implications for peak electricity demand;

Time-of-use tariffs, but what about frivolous-use tariffs? Australia is an economy with cheap energy, rapidly rising AC

penetration in residential sector, and excessively high GHG emissions per capita

What about the emerging BRICs? This is a well-developed, turn-key research method so lets

collaborate!

Thank you for your attention

New thermal comfort and air conditioning behavioral research methods for residential settings History of thermal comfort researchWhats missing?Whats so different about homes?Policy driversAustralian Home Insulation ProgramThe Rebound EffectWhy is residential comfort so under-researched?Previous residential studiesOur new Smart[phone] ApproachIntroducing Comfort Chimp smartphone questionnaireNmero do slide 12Comfort ChimpTemperature and RH measurementsDetermining AC usage patternsDefining AC usageHouseholder QuestionnaireSydney results using this methodResidential Clothing Insulation BehaviourResidential AC events by monthAC durationTime of AC useAC trigger temperaturesAdaptive ComfortCooling Trigger TempsHeating Trigger TempsBedroom TempsLiving RoomAverage Thermal SensationLiving RoomsAverage Thermal SensationLiving RoomsConclusionsThank you for your attention