the smart thermostat using occupancy sensors to save energy in homes
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The Smart Thermostat: Using Occupancy Sensors to Save Energy in Homes. Jiakang Lu, Tamim Sookoor, Vijay Srinivasan, Ge Gao, Brian Holben, John Stankovic, Eric Field, Kamin Whitehouse SenSys 2010 Zurich, Switzerland. Motivation. 43%. State of the Art. Too much cost!. $5,000 - $25,000.

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the smart thermostat using occupancy sensors to save energy in homes

The Smart Thermostat: Using Occupancy Sensors to Save Energy in Homes

Jiakang Lu, Tamim Sookoor, Vijay Srinivasan, Ge Gao, Brian Holben,

John Stankovic, Eric Field, Kamin Whitehouse

SenSys 2010

Zurich, Switzerland

state of the art
State of the Art

Too much cost!

$5,000 - $25,000

state of the art4
State of the Art

Too much hassle!

Too much hassle!

Temperature (oF)

Energy waste

User discomfort

75

Setpoint

Setpoint

70

Setback

65

60

55

Home

Home

Home

Home

00:00

08:00

18:00

24:00

how much energy can be saved with occupancy sensors
“How much energy can be saved

with occupancy sensors?”

using occupancy sensors
Using Occupancy Sensors

Temperature (oF)

75

70

65

60

55

Home

Home

Home

Home

00:00

08:00

18:00

24:00

the wrong way
The Wrong Way
  • “Reactive” Thermostat

Increase energy usage!

Temperature (oF)

Slow Reaction

Shallow Setback

Inefficient Reaction

75

70

65

60

55

Home

Home

00:00

08:00

18:00

24:00

our approach
Our Approach
  • Smart Thermostat

Temperature (oF)

Fast reaction

Preheating

Deep setback

75

70

65

60

55

Home

Home

00:00

08:00

18:00

24:00

Automatically save energy!

rest of the talk
Rest of the talk
  • System Design
    • Fast Reaction
    • Preheating
    • Deep Setback
  • Evaluation
1 fast reaction
1. Fast Reaction
  • “Reactive" Thermostat

Inactivity detector

Active/Inactive

Temperature (oF)

User discomfort

Energy waste

75

70

65

60

55

Home

Home

00:00

08:00

18:00

24:00

1 fast reaction11
1. Fast Reaction
  • Smart Thermostat

Pattern detector

Active/Away/Asleep

Temperature (oF)

Detect within minutes

Without increasing false positives

75

70

65

60

55

Home

Home

00:00

08:00

18:00

24:00

2 preheating
2. Preheating

“Why preheat?”

  • Preheat – slow but efficient
    • Heat pump
  • React – fast but inefficient
    • Electric coils
    • Gas furnace

How to decide when to preheat?

Temperature (oF)

Energy waste

Energy waste

75

70

65

60

55

Home

Home

00:00

08:00

18:00

24:00

2 preheating13
2. Preheating

Arrival Time Distribution

Preheat

3

React

Expected Energy Usage (kWh)

16:00

20:00

18:00

Optimal Preheat Time

2

1

0

16:00

20:00

18:00

Time

3 deep setback
3. Deep Setback

Arrival Time Distribution

16:00

20:00

18:00

Earliest expected

arrival time

Optimal preheat time

Temperature (oF)

Shallow setback

Deep setback

75

70

65

??

60

55

Home

Home

00:00

08:00

18:00

24:00

rest of the talk15
Rest of the talk
  • System Design
    • Fast Reaction
    • Preheating
    • Deep Setback
  • Evaluation
evaluation
Evaluation
  • Occupancy Data
  • Energy Measurements
  • EnergyPlus Simulator
energy savings
Energy Savings

60

Optimal

Reactive

50

Energy Savings (%)

Smart

40

Optimal: 35.9%

Smart: 28.8%

30

20

Reactive: 6.8%

10

0

-10

Home Deployments

A

B

C

D

E

F

G

H

user comfort
User Comfort

120

Reactive

Smart

Average Daily Miss Time (min)

100

80

Reactive: 60 min

60

Smart: 48 min

40

20

0

Home Deployments

A

B

C

D

E

F

G

H

generalization
Generalization
  • Person Types
  • House Types
  • Climate Zones
impact
Impact
  • Nationwide Savings
    • save over 100 billion kWh per year
    • prevent 1.12 billion tons of air pollutants
  • “Bang for the buck”
    • $5 billion for weatherization
    • Our technique is ~$25 in sensors per home
conclusions
Conclusions
  • Three simple techniques, but able to achieve
    • large savings: 28% on average
    • low cost: $25 in sensors per home
    • low hassle: automatic temperature control
  • Promising sensing-based solution
slide22
Q & A

Thank you!

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