Incentives vs nudges to shift EV charging behaviour

Last registered on October 31, 2022
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Pre-Trial

Trial Information

General Information

Title
Incentives vs nudges to shift EV charging behaviour
RCT ID
AEARCTR-0010282
Initial registration date
October 21, 2022

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
October 31, 2022, 10:44 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Country
Canada
Region

Primary Investigator

Name
Blake Shaffer
Affiliation
University of Calgary
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Megan Bailey
PI Affiliation
University of Calgary
Contact Investigator
PI Name
David Brown
PI Affiliation
University of Alberta
Contact Investigator
PI Name
Frank Wolak
PI Affiliation
Stanford University
Contact Investigator

Additional Trial Information

Status
On going
Start date
2022-01-01
End date
2023-06-30
Keywords
Environment & Energy
Additional Keywords
electric vehicles, charging, flexible demand, incentives, nudges
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Electric vehicles (EVs) are expanding their market share across global vehicle fleets rapidly. Their impact on electric grids will largely depend on when they are charged. If charged during peak periods, when owners return from work, EVs will increase capacity costs of meeting system peaks. Conversely, charging during off-peak hours can take advantage of lower energy costs and minimize strain on the grid. Using a field experiment of EVs in an urban setting, we test the effectiveness of financial incentives vs moral suasion ``nudges'', both intended to shift charging to off-peak hours.

External Link(s)

Registration Citation

Citation
Bailey, Megan et al. 2022. "Incentives vs nudges to shift EV charging behaviour." AEA RCT Registry. October 31. https://doi.org/10.1257/rct.10282-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
We recruit 250 EV owners to be part of a study on EV charging behaviour within an urban utility's service territory. We install monitoring devices in each vehicle to track charging and driving behaviour at a fine temporal scale. We follow behaviour of all vehicles for 3 months. We then use a cluster-stratified randomization to place EV-owners into one of 3 groups: (1) a control group receiving no intervention; (2) an education group that receives an email encouraging them to charge their vehicle during off-peak hours (10pm-6am); and (3) a financial group that receives the same encouragement email plus a monetary incentive per kWh of off-peak charging. We subsequently follow charging behaviour across all 3 groups.

The primary intervention is the different emails with different rewards for behaviour, for each group.
Intervention Start Date
2022-04-01
Intervention End Date
2022-12-31

Primary Outcomes

Primary Outcomes (end points)
Charging kilowatt-hours, charging minutes, and a charging dummy by hour before vs after the intervention, across the three groups.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We recruit 250 EV owners to be part of a study on EV charging behaviour within an urban utility's service territory. We install monitoring devices in each vehicle to track charging and driving behaviour at a fine temporal scale. We follow behaviour of all vehicles for 3 months. We then use a cluster-stratified randomization to place EV-owners into one of 3 groups: (1) a control group receiving no intervention; (2) an education group that receives an email encouraging them to charge their vehicle during off-peak hours (10pm-6am); and (3) a financial group that receives the same encouragement email plus a monetary incentive per kWh of off-peak charging. We subsequently follow charging behaviour across all 3 groups.
Experimental Design Details
Randomization Method
We first cluster EV owners based on observable characteristics. Then, within each cluster we randomly assign individual EV owners to a treatment group using a computer randomization.
Randomization Unit
The EV owner.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
250 EVs
Sample size: planned number of observations
We have 8760 hours x 250 EVs = 2,190,000 observations.
Sample size (or number of clusters) by treatment arms
50 control, 100 education group, 100 financial group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
The Conjoint Faculties Research Ethics Board (CFREB), University of Calgary
IRB Approval Date
2022-05-18
IRB Approval Number
REB22-0080
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials