Price Sensitivity and the Welfare Impacts of Managed Charging: Pre-Registration

Last registered on February 16, 2024
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Pre-Trial

Trial Information

General Information

Title
Price Sensitivity and the Welfare Impacts of Managed Charging: Pre-Registration
RCT ID
AEARCTR-0013037
Initial registration date
February 14, 2024

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
February 16, 2024, 4:11 PM EST

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

Locations

Country
United Kingdom of Great Britain and Northern Ireland
Region

Primary Investigator

Name
Cohen R. Simpson
Affiliation
Centre for Net Zero, Octopus Energy Group
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Other Primary Investigator(s)

PI Name
Andrew Schein
PI Affiliation
Centre for Net Zero, Octopus Energy Group
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PI Name
Robert Metcalfe
PI Affiliation
Centre for Net Zero, Octopus Energy Group
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Additional Trial Information

Status
In development
Start date
2024-02-15
End date
2024-12-31
Keywords
Behavior, Environment & Energy, Welfare
Additional Keywords
Domestic Consumption, Electric Vehicles
JEL code(s)
Q41, I30, C93
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Generalised uptake of the supplier-managed charging of electric vehicles (EVs) is thought to be a major prerequisite for the wide-scale electrification of personal transport without costly investment in grid infrastructure. Yet this arrangement requires private individuals
to cede control of their domestic environment to an energy retailer, potentially hampering adoption. To empirically probe the malleability of private EV owners’ preferences around “handing over” control of their charging schedules, we will run a five-arm randomised field trial in 2024 involving 13,233 customers of a British energy supplier. These individuals will be offered randomly-assigned amounts of money to test how much it costs to switch them to a “smart” tariff combining supplier-managed EV charging with a static daily off-peak electricity price for their entire home.
External Link(s)

Registration Citation

Citation
Metcalfe, Robert, Andrew Schein and Cohen R. Simpson. 2024. "Price Sensitivity and the Welfare Impacts of Managed Charging: Pre-Registration." AEA RCT Registry. February 16. https://doi.org/10.1257/rct.13037-1.0
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Experimental Details

Interventions

Intervention(s)
Details withheld until study completion.
Intervention Start Date
2024-02-15
Intervention End Date
2024-06-26

Primary Outcomes

Primary Outcomes (end points)
We have two outcome variables. The first is a binary indicator for whether or not a customer has adopted a “smart” tariff combining the supplier-managed charging of one's electric vehicle with a static daily off-peak electricity price for their entire home. The second is a continuous variable for one's domestic electricity consumption between 16:00 to 20:00 GMT.
Primary Outcomes (explanation)
Neither of our primary outcome variables will be constructed. Our binary indicator will simply reflect the start and end dates of formal electricity tariff contract agreements. Our continuous outcome will be the sum of one's electricity consumption between 16:00 to 20:00 GMT for each of the 195 days of our observation period, where consumption data will be measured using smart meters that record electricity usage in 30-minute intervals.

Secondary Outcomes

Secondary Outcomes (end points)
Our secondary outcome is a continuous variable for the CO2 value of one's domestic electricity consumption.
Secondary Outcomes (explanation)
Briefly, to construct our secondary outcome, we will multiply a customer's electricity consumption during a given half hour by the average marginal CO2 emissions value of consumption during that same half hour. Marginal CO2 values will be operationalised as Marginal Operating Emissions Rates (MOERs). Calculated and published by WattTime, a US-based non-profit (https://watttime.org/data-science/data-signals/marginal-co2/), a MOER is an estimate of the change in CO2 emissions due to a change in power generation or electricity use in a particular geographic location at a specific point in time over one five-minute interval. We will take the average of the six MOERs for a particular half-hour to perform the multiplication to derive the CO2 value of one's electricity consumption, summing to the level of each of the 195 days of our observation period.

Experimental Design

Experimental Design
Details withheld until study completion.
Experimental Design Details
Not available
Randomization Method
Block randomisation of customers performed using the R library “blockTools” (https://www.ryantmoore.org/html/software.blockTools.html).
Randomization Unit
13,322 customers (i.e., clusters wherein 195 daily observations are nested).
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
13,233 customers (clusters) within 1,109 blocks (i.e., strata).
Sample size: planned number of observations
2,580,435 customer-day observations (i.e., 13,233 customers x 195 days of observation)
Sample size (or number of clusters) by treatment arms
Control Group (2,205 Customers); Treatment Group 1 (7,720 Customers); Treatment Group 2 (1,101 Customers); Treatment Group 3 (1,102 Customers); Treatment Group 4 (1,105 Customers)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Please see pre-registered analysis plan for our simulation-based assessment of statistical power.
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
University of Southern California
IRB Approval Date
2023-08-18
IRB Approval Number
UP-23-00733
Analysis Plan

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