1 an empirical analysis of marginal efficiency … 2014... · 1=multipane window houses with manual...

AN EMPIRICAL ANALYSIS OF MARGINAL

EFFICIENCY GAINS WITHIN AND ACROSS END

USES: IMPLICATIONS FOR THE REBOUND

EFFECT FOR HOUSEHOLDS

[email protected]

June 16th, 2014

Nour Bouhou, MS, PhD Candidate

The University Of Texas At Austin

Civil, Architectural, & Environmental Engineering

Advisor: Dr. Michael Blackhurst

1

Energy Simulations of Buildings

� Engineering modeling is dominant paradigm� EnergyPlus

� BeOpt

� Demand-side management (Energy Change = - Efficiency Change)

� Even sophisticated engineering models perform

poorly

� Empirical models use statistics to predict

observed consumption given variation in

descriptive factors

2

Empirical Efficiency Research

� Observed energy efficiency outcomes often

different than predicted

� Some studies attribute this difference to behavior

changes (i.e., the “rebound effect”)

� Pecan Street data offer unique insight to more

empirically assess efficiency outcomes

3

How do homeowners respond to efficiency

changes?

Behavior change

Effect on Energy Savings

Example

None All technically feasible

savings realized

Direct

rebound

Homeowners use

more of the more

efficient service

Consumer drives more

with a more fuel efficient

car

Indirect

rebound

Homeowners leverage

efficiency gains in one

service for another

Savings from efficient

lighting spend on 2nd

refrigerator

Expand

Services

Homeowners increase

energy services in

home

Efficiency gains spent on

new TV

Net energy savings

4


changes?

Behavior change


Example


savings realized

Direct

rebound

Homeowners use

more of the more

efficient service



car

Indirect

rebound

Homeowners leverage


service for another



refrigerator

Expand

Services

Homeowners increase

energy services in

home


new TV

Net energy savings

5


changes?

Behavior change


Example


savings realized

Direct

rebound

Homeowners use

more of the more

efficient service



car

Indirect

rebound

Homeowners leverage


service for another



refrigerator

Expand

Services

Homeowners increase

energy services in

home


new TV

Net energy savings

6


changes?

Behavior change


Example


savings realized

Direct

rebound

Homeowners use

more of the more

efficient service



car

Indirect

rebound

Homeowners leverage


service for another



refrigerator

Expand

Services

Homeowners increase

energy services in

home


new TV

Net energy savings

7


changes?

Behavior change


Example


savings realized

Direct

rebound

Homeowners use

more of the more

efficient service



car

Indirect

rebound

Homeowners leverage


service for another



refrigerator

Expand

Services

Homeowners increase

energy services in

home


new TV

Net energy savings

8

Empirical Model

Household electricity consumption is a function of

�Physical characteristics (floorspace, insulation, etc.)

�Demographic characteristics (income, occupancy, etc.)

�Self-reported behaviors (appliance use)

�Technology choices (Energy Star appliances, insulation, etc.)

�Exogenous factors (weather, etc.)

9

Empirical Model

Where

� Yit represents monthly electricity consumption (kWh/month)

� βj are the predictor coefficient for fixed effects

� Sijλ represents a series of household structural factors

� Dijλ represents a series of household demographic factors

� Bijλ represents household behaviors and cognitive factors

� Tij represents technology choices

� Ri represents the household identification codes

� εij are the error terms.

10

Empirical Model

Where









11

Empirical Model

Where









12

Empirical Model

Where









13

Empirical Model

14

e.g.: Programmable thermostat * Multipane

windows

Total 354 262 187 197 145 103 11 111 88 82

New 265 198 119 191 127 64 1 94 49 55

Retrofit 89 64 68 6 18 39 10 17 39 27

Inspections

& Drawings

Household

survey

Energy

audit

Elec.

Production

Elec.

Consum-

ption Natural gas Water

Elec. Cons

+ Survey

Elec Cons

+ Survey +

Audit

Gas Cons +

Survey +

Audit

Indicated household consist across table

89

homes

existing

at start

of study

265 homes new at start of

study

89

homes

existing

at start

of study

Sample from Pecan Street Research

Institute15

Total 354 262 187 197 145 103 11 111 88 82

New 265 198 119 191 127 64 1 94 49 55

Retrofit 89 64 68 6 18 39 10 17 39 27

Inspections

& Drawings

Household

survey

Energy

audit

Elec.

Production

Elec.

Consum-


Elec. Cons

+ Survey

Elec Cons

+ Survey +

Audit

Gas Cons +

Survey +

Audit


89

homes

existing

at start

of study


study

89

homes

existing

at start

of study


InstituteStatic data

16

Total 354 262 187 197 145 103 11 111 88 82

New 265 198 119 191 127 64 1 94 49 55

Retrofit 89 64 68 6 18 39 10 17 39 27

Inspections

& Drawings

Household

survey

Energy

audit

Elec.

Production

Elec.

Consum-


Elec. Cons

+ Survey

Elec Cons

+ Survey +

Audit

Gas Cons +

Survey +

Audit


89

homes

existing

at start

of study


study

89

homes

existing

at start

of study


InstituteStatic data High resolution consumption data

17

Total 354 262 187 197 145 103 11 111 88 82

New 265 198 119 191 127 64 1 94 49 55

Retrofit 89 64 68 6 18 39 10 17 39 27

Inspections

& Drawings

Household

survey

Energy

audit

Elec.

Production

Elec.

Consum-


Elec. Cons

+ Survey

Elec Cons

+ Survey +

Audit

Gas Cons +

Survey +

Audit


89

homes

existing

at start

of study


study

89

homes

existing

at start

of study


InstituteStatic data High resolution consumption data

18Our

Sample

Electricity End-Uses in Study

Air conditioning

Electricity

Consumption Fitted

To

AC Energy Efficiency Ratio (EER)

Windows (multi- or single pane)

Attic R-value

Programmable thermostat

Appliances (Energy Star or Code Min)

Refrigerator

Dishwasher

Clothes washer

New services

Devices (TVs, Computers, Tables, Game

Consoles)

19


Air conditioning

Electricity

Consumption Fitted

To



Attic R-value



Refrigerator

Dishwasher

Clothes washer

New services


Consoles)

Technical

Change

Within AC

(Direct)

20


Air conditioning

Electricity

Consumption Fitted

To



Attic R-value



Refrigerator

Dishwasher

Clothes washer

New services


Consoles)

Technical

Change

Within AC

(Direct) Technical

Change

Across End-

Uses (Direct,

Indirect)

21


Air conditioning

Electricity

Consumption Fitted

To



Attic R-value



Refrigerator

Dishwasher

Clothes washer

New services


Consoles)

Technical

Change

Within AC

(Direct) Technical

Change

Across End-

Uses (Direct,

Indirect)

New

Energy

Services

(Direct +

Indirect)

22

Results with No Interaction Terms

(No cross effects or marginal analysis)23

Explanatory variable Coefficient

estimate

p-value % change in consumption

for 1 unit (or 10%++)

increase in X variable

Constant (bo) 7.97 0 *

Cooling Degree Days 0.00129 0 * 0.129%

1/ √(House Area) -73.8 0 * 8.15% ++

Insulation R value -0.00562 0.051 * -0.56%

Devices 0.0153 0.066 * 1.54%

Programmable Thermostat 0.0898 0.256 9.4%

Energy Star Clothes washer 0.0542 0.382 5.56%

Photovoltaic panels -0.05 0.625 -4.88%

Note: Devices include computers, TVs, tablets, cable or satellite boxes, DVRs/DVD/VCR/BluRay, Stereo systems, and gaming systems .

* Statistically significant results to the 10% level

Margins Plot PrimerF

itte

d (

or

Pre

dic

ted)

log(

Ele

ctr

icity

Consum

ption)

Efficiency

Increase in consumption (possible behavior change)

Decrease in consumption (good!)

24

Elec Use ~ 640 kWh/

month

Elec Use ~ 844 kWh/

month Elec Use ~ 829 kWh/

month

Elec Use ~ 712 kWh/

month

6.2

6.3

6.4

6.5

6.6

6.7

6.8

6.9

7

Fitted

valu

es o

f Lo

g(E

lect

rici

ty C

onsu

mption)

Windows:

0= Single pane windows 1=Multipane window

Houses with Manual Thermostat Houses with Programmable Thermostat

Marginal Efficiency Gains Within Space

Conditioning25

0 1

Manual Thermostat Programmable Thermostat

Elec Use ~ 640 kWh/

month

Elec Use ~ 844 kWh/


month

Elec Use ~ 712 kWh/

month

6.2

6.3

6.4

6.5

6.6

6.7

6.8

6.9

7

Fitted

valu

es o

f Lo

g(E

lect

rici

ty C

onsu

mption)

Windows:




Conditioning26

0 1

32%

Manual Thermostat

Elec Use~ 640

kWh/month

Elec Use~ 844

kWh/month

Elec Use ~ 640 kWh/

month

Elec Use ~ 844 kWh/


month

Elec Use ~ 712 kWh/

month

6.2

6.3

6.4

6.5

6.6

6.7

6.8

6.9

7

Fitted

valu

es o

f Lo

g(E

lect

rici

ty C

onsu

mption)

Windows:




Conditioning27

0 1

Elec Use~ 829

kWh/month

Elec Use~ 712

kWh/month

-14%

32%

Houses with

programmable

thermostat

Predicted use = 829

kWh/month

windows

Predicted use =

844 kWh/month

multi-paneHouses with

Predicted

use = 712

kWh/mont

h

-14%

Elec Use~ 640

kWh/month

Elec Use~ 844

kWh/month


Elec Use ~ 640 kWh/

month

Elec Use ~ 844 kWh/


month

Elec Use ~ 712 kWh/

month

6.2

6.3

6.4

6.5

6.6

6.7

6.8

6.9

7

Fitted

valu

es o

f Lo

g(E

lect

rici

ty C

onsu

mption)

Windows:




Conditioning28

0 1

Elec Use~ 829

kWh/month

Elec Use~ 712

kWh/month

-14%

32%

Houses with

programmable

thermostat

Predicted use = 829

kWh/month

windows

Predicted use =

844 kWh/month


Predicted

use = 712

kWh/mont

h

-14% -16%

-16%

Elec Use~ 640

kWh/month

Elec Use~ 844

kWh/month


Elec Use ~ 616 kWh/

month

Elec Use ~ 825 kWh/

month

Elec Use ~738 kWh/

month

Elec Use ~ 736 kWh/

month

6.2

6.3

6.4

6.5

6.6

6.7

6.8

6.9

7

Fitte

d v

alu

es

of

Log(E

lect

rici

ty C

onsu

mption)

Clothes washer:

0= Code Minimum Clothes Washer

1=Energy Star Clothes Washer


Marginal Efficiency Gains Across End-Uses

29

0 1

Elec Use~ 825

kWh/month

34%

Elec Use~ 616

kWh/month

Manual Thermostat Programmable ThermostatManual Thermostat

Elec Use ~ 616 kWh/

month

Elec Use ~ 825 kWh/

month

Elec Use ~738 kWh/

month

Elec Use ~ 736 kWh/

month

6.2

6.3

6.4

6.5

6.6

6.7

6.8

6.9

7

Fitte

d v

alu

es

of

Log(E

lect

rici

ty C

onsu

mption)

Clothes washer:





30

0 1

Elec Use~ 738

kWh/month

Elec Use~ 736

kWh/month

Elec Use~ 616

kWh/month

Elec Use~ 825

kWh/month

-0.2%

34%



0

31

(2)

Elec Use ~ 616 kWh/

month

Elec Use ~ 825 kWh/

month

Elec Use ~738 kWh/

month

Elec Use ~ 736 kWh/

month

6.2

6.3

6.4

6.5

6.6

6.7

6.8

6.9

7

Fitte

d v

alu

es

of

Log(E

lect

rici

ty C

onsu

mption)

Clothes washer:




0 1

Elec Use~ 738

kWh/month

Elec Use~ 736

kWh/month

Elec Use~ 616

kWh/month

(1) Houses with a baseline clothes washer consume more electricity (∆Elec~122 kWh/month) if they have a

programmable thermostat as well.

Elec Use~ 825

kWh/month

(1)



0

32

(2)

Elec Use ~ 616 kWh/

month

Elec Use ~ 825 kWh/

month

Elec Use ~738 kWh/

month

Elec Use ~ 736 kWh/

month

6.2

6.3

6.4

6.5

6.6

6.7

6.8

6.9

7

Fitte

d v

alu

es

of

Log(E

lect

rici

ty C

onsu

mption)

Clothes washer:




0 1

Elec Use~ 738

kWh/month

Elec Use~ 736

kWh/month

Elec Use~ 616

kWh/month

Elec Use~ 825

kWh/month

(1)

(2)

(1) Houses with a baseline clothes washer consume more electricity (∆Elec~122 kWh/month) if they have a

programmable thermostat as well.


(2) Houses with Energy Star clothes washer and a programmable

thermostat decrease their electricity consumption (∆Elec~ -89 kWh/month).

Eelec Use~677 kWh/

month

Eelec Use~1424 kWh/

month

Eelec Use~736 kWh/

month

Eelec Use~728 kWh/

month

6.2

6.4

6.6

6.8

7

7.2

7.4

7.6

7.8

Fit

ted

va

lues

of

Lo

g(E

lect

ric

ity

Co

nsu

mp

tio

n)

Vehicles:

0= Houses with no Electric Vehicle

1=Houses with Electric Vehicle

Houses with Manual Thermostat Houses with programmable thermostat

Efficiency Gains for New Services

33

(2)

Elec Use~ 736

kWh/month

Elec Use~ 728

kWh/month Elec Use~ 677

kWh/month

Elec Use~ 1424

kWh/month

0

-1%

110%


1

Eelec Use~677 kWh/

month

Eelec Use~1424 kWh/

month

Eelec Use~736 kWh/

month

Eelec Use~728 kWh/

month

6.2

6.4

6.6

6.8

7

7.2

7.4

7.6

7.8

Fit

ted

va

lues

of

Lo

g(E

lect

ric

ity

Co

nsu

mp

tio

n)

Vehicles:




Efficiency Gains for New Services

34

(2)

Elec Use~ 736

kWh/month

Elec Use~ 728

kWh/month Elec Use~ 677

kWh/month

Elec Use~ 1424

kWh/month

0


1

(1)

(2)

(1) Houses with no Electric Vehicle consume more electricity (∆elec~59 kWh/month) if they have a programmable

thermostat as well.

(2) Houses with an Electric Vehicle and a programmable

thermostat decrease their electricity consumption (∆Elec~ -696 kWh/month).

Change in electricity use with Marginal

Efficiency Gains

R <19 19 <R < 29 R>30 7 eer 11 eer 14 eer count=5 count=10 count=15

R <19

19 <R < 29

R>30

7 eer

11 eer

14 eer

count=5

count=10

count=15Electric Vehicle

ES Clothes washer

Devices

ES Refrigerator

ES Dishwasher

Air Conditioning

EER

Multipane Windows

Insulation R value

ES Clothes washer

Devices Electric Vehicle

Programmable Thermostat


Multipane Window

Insulation R value Air Conditioning EER ES Refrigerator

ES Dishwasher

Houses with Programmable thermostat

Houses

with

Multipane winows

35

Houses withprogrammable

thermostat windows

-14% change -16% change

Predicted use = 829

kWh/monthPredicted

use = 712

kWh/mont

h

Predicted use =

844 kWh/month


-14%

-16%


Efficiency Gains36


* -14% * 0% * -1%

* -16%R <19

19 <R < 29

R>30

7 eer * -15% * -31%

11 eer * 12% * -4%

14 eer * 38% * 24%

*-11%

count=5

count=10

count=15

* -49%

LEGEND

Increase in electricity consumption

No effect

Net energy savings

* Statistically significant results to 10% level

Electric Vehicle

Electric Vehicle

* 0%

Insulation R value

Multipane Windows


Multipane Window


ES Dishwasher

ES Clothes washer

Devices


Air Conditioning

EER

ES Refrigerator

ES Dishwasher * 5%ES Clothes washer

Devices

Summary of Efficiency Analysis

� The observed effect of technical change is most significantly influenced by the presence of a programmable thermostat

37

Results with No Interaction Terms

(No cross effects or marginal analysis)38

Explanatory variable Coefficient

estimate

p-value % change in consumption

for 1 unit (or 10%++)

increase in X variable

Constant (bo) 7.97 0 *

Cooling Degree Days 0.00129 0 * 0.129%

1/ √(House Area) -73.8 0 * 8.15% ++

Insulation R value -0.00562 0.051 * -0.56%

Devices 0.0153 0.066 * 1.54%

Programmable Thermostat 0.0898 0.256 9.4%

Energy Star Clothes washer 0.0542 0.382 5.56%

Photovoltaic panels -0.05 0.625 -4.88%

Note: Devices include computers, TVs, tablets, cable or satellite boxes, DVRs/DVD/VCR/BluRay, Stereo systems, and gaming systems .

* Statistically significant results to the 10% level


Efficiency Gains39


* -14% * 0% * -1%

* -16%R <19

19 <R < 29

R>30

7 eer * -15% * -31%

11 eer * 12% * -4%

14 eer * 38% * 24%

*-11%

count=5

count=10

count=15

* -49%

LEGEND

Increase in electricity consumption

No effect

Net energy savings

* Statistically significant results to 10% level

Electric Vehicle

Electric Vehicle

* 0%

Insulation R value

Multipane Windows


Multipane Window


ES Dishwasher

ES Clothes washer

Devices


Air Conditioning

EER

ES Refrigerator

ES Dishwasher * 5%ES Clothes washer

Devices

Summary of Efficiency Analysis

� The observed effect of technical change is most significantly influenced by the presence of a programmable thermostat

� “Enough” efficiency improvement is needed to overcome behavioral responses

� Homes do not appear to be rebounding into appliances (Saturation)

� Homeowners may leverage efficiency gains for device use

� Baseline technical state of home (and order of technical change)

matters

40

Policy Implications

� Make people thermally comfortable first

� Bundle incentives to achieve “enough” efficiency gains to overcome behavioral responses

� Could we better design incentives using existing technical state of home (per energy audit)?

� Would coupling education about this research with incentives affect outcomes?

41

Photovoltaic technology in the US

How do homeowners leverage the PV gains?

Possible scenarios:

�Displace conventional electricity

�Utilize for conventional end-uses (efficiency measure)

�Utilize for new services (devices, EV, etc.)

43

Empirical model:


44

Efficiency measures New services

LOW demand-side

characteristics

Manual R value ~ 16 Code minimum

dishwasher

Number of devices ~ 5 No Electric vehicle

HIGH demand-side

characteristics

Programmable R value ~ 36 EnergyStar Dishwasher Number of devices ~

15

At least one electric

vehicle


45


LOW demand-side

characteristics


dishwasher


HIGH demand-side

characteristics


15


vehicle


46


LOW demand-side

characteristics


dishwasher


HIGH demand-side

characteristics


15


vehicle


Key findings:

�Houses with PV could achieve energy reductions with the appropriate level of technological efficiency.

�The impact of PV adoption on energy demand depends on the efficiency performance of the household

�Homeowners do not appear to leverage PV gains for appliances: ‘Saturation’effect.

�Houses might utilize PV gains for electronic devices but not Electric vehicles.

NOTE: ~90% of PV costs were subsidized for our sample

47

Acknowledgements

� This work was funded by

� The University of Texas at Austin

� The data was provided by

� The Pecan Street Research Institute

� Academic Advisor:

� Dr. Michael Blackhurst

48

[email protected]

Thank you!

Questions?

49


Conditioning50

Elec Use ~ 640 kWh/

month

Elec Use ~ 844 kWh/


month

Elec Use ~ 712 kWh/

month

6.2

6.3

6.4

6.5

6.6

6.7

6.8

6.9

7

Fitted

valu

es o

f Lo

g(E

lect

rici

ty C

onsu

mption)

Windows:



0 1

Elec Use~ 829

kWh/month

Elec Use~ 712

kWh/month

(2)

(1)

Elec Use~ 640

kWh/month

(1) Houses with single pane windows consume more electricity (∆Elec~189

kWh/month) if they have a programmable thermostat as well.

Elec Use~ 844

kWh/month

(2) Houses with multipane windows and a programmable thermostat decrease their

electricity consumption (∆Elec~ -132 kWh/month).


Efficiency Gains for New

Services51

Eelec Use~677 kWh/

month

Eelec Use~1424 kWh/

month

Eelec Use~736 kWh/

month

Eelec Use~728 kWh/

month

6.2

6.4

6.6

6.8

7

7.2

7.4

7.6

7.8

Fit

ted

va

lues

of

Lo

g(E

lect

ric

ity

Co

nsu

mp

tio

n)

Vehicles:




(

1

)

(2)

10

Households’ responses to solar energy

gains 52

Eelec Use~677 kWh/

month

Eelec Use~1424 kWh/

month

Eelec Use~736 kWh/

month

Eelec Use~728 kWh/

month

6.2

6.4

6.6

6.8

7

7.2

7.4

7.6

7.8

Fit

ted

va

lues

of

Lo

g(E

lect

rici

ty C

on

sum

pti

on

)

Vehicles:




(1)

(2)

(1) Houses with no Electric Vehicle consume more

electricity (∆elec~59 kWh/month) if they have

a programmable thermostat as well.

(2) Houses with an Electric

Vehicle and a programmable thermostat

decrease their electricity consumption (∆Elec~ -696 kWh/month).

10

Households’ responses to solar energy

gains 53

1

Eelec Use~ 609 kWh/month

Eelec Use~ 793 kWh/month Eelec Use~ 746 kWh/month

Eelec Use~ 725 kWh/month

6.1

6.2

6.3

6.4

6.5

6.6

6.7

6.8

6.9

0 1

Fit

ted

valu

es o

f L

og

(Ele

ctri

city

Con

sum

pti

on

)

Space Conditioning:

0= Houses with no Programmable Thermostat

1= Houses with Programmable Thermostat

Houses with no Photovoltaic panels

Houses with Photovoltaic panels

(1)

(2)

(1) Houses with no programmable thermostat consume more electricity

(∆elec~ 137 kWh/month) if they have a solar panels

as well.(2) Houses with solar panels

and a programmable thermostat decrease their electricity consumption

(∆Elec~ -66 kWh/month).

The State of knowledge

o No quantitative literature

o Very limited qualitative literature:

o Kierstead (2007): few self-reported behavioral changes

o Erge et al. (2001): No difference in electricity consumption

o Haas et al. (1999): high-energy consumers (> 3500 kWh per year)

reduced overall demand after installation of PV whereas low

consumers increased their demand

o McAndrews (2011):nearly 80% self-report no change in energy

demands

Research questions

o Limitations: Self-reported data, energy consumption is not

evaluated quantitatively, short-term analysis.

o Question: How do homeowners leverage the PV gains?

o Displace conventional electricity?

o Utilize for conventional end-uses (efficiency measure)?

o Utilize for new services?

o Notes:

o ~90% of PV costs were subsidized for our sample

1 an empirical analysis of marginal efficiency … 2014... · 1=multipane window houses with manual...

Documents