Understanding the Role of Knowledge in Peak-avoidance Behaviour of Electricity Consumption: Experimental Evidence from Residential Energy Use

Last registered on March 15, 2024

Pre-Trial

General Information

Title

RCT ID

AEARCTR-0013098

Initial registration date

March 02, 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

March 15, 2024, 2:33 PM EDT

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

Locations

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Primary Investigator

Name

Yu Wang

Affiliation

University of Leeds

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Other Primary Investigator(s)

PI Name

Lorenz Goette

PI Affiliation

National University Of Singapore

Contact Investigator

PI Name

Erte Xiao

PI Affiliation

Monash University

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PI Name

Yacan Wang

PI Affiliation

Beijing Jiaotong University

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Additional Trial Information

Status

On going

Start date

2024-02-12

End date

2024-12-31

Keywords

Behavior, Environment & Energy

Additional Keywords

Knowledge, Electricity consumption, Peak-avoidance, Habit formation, Randomized Control Trial

JEL code(s)

C93, D12, D83, Q2

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

Lack of information about energy usage inhibits efficiency in energy conservation but can be overcome by providing simple, low-cost information. This study uses a randomized control trial to test the effect of knowledge information on the peak-avoidance behaviour of electricity consumption, with a design of various rounds of household-level message sending to test the mechanism for persistence in behaviour and habit formation process. We anticipate that our design and findings will help develop low-cost and long-lasting interventions for guiding households to choose peak-avoidance behaviour.

External Link(s)

Registration Citation

Citation

Goette, Lorenz et al. 2024. "Understanding the Role of Knowledge in Peak-avoidance Behaviour of Electricity Consumption: Experimental Evidence from Residential Energy Use." AEA RCT Registry. March 15. https://doi.org/10.1257/rct.13098-1.0

Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)

1. Control group: Participants receive weather forecast information through SMS every Monday lasting for 8 weeks;
2. Knowledge groups(there are 4 groups with different treatment cycles): Participants receive knowledge information through SMS. The knowledge information includes revealing the peak/off-peak periods of electricity consumption, negative externalities of excessive electricity consumption during peak periods, and suggestions for how to peak avoidance. Message sending lasts for 8 weeks, but different groups have different sending frequencies. In weeks of no treatment, households will receive weather forecast information.

Intervention Start Date

2024-02-19

Intervention End Date

2024-04-08

Primary Outcomes

Primary Outcomes (end points)

1. Household Electricity Usage - During the Experiment
2. Household Electricity Usage - After the Experiment
3. Peak Avoidance Behaviour - During the Experiment

Primary Outcomes (explanation)

1. Household Electricity Usage - During the Experiment: This experiment will obtain the hourly electricity usage of users during peak, off-peak, and shoulder periods through the company's system during the experiment period.
2. Household Electricity Usage - After the Experiment: After the intervention ends, this experiment will continue to track users' electricity usage behaviour for 2-3 months. By continuing to track the households' electricity usage patterns, we can observe whether their peak avoidance behaviour persists in the long term.
3. Peak Avoidance Behavior - During the Experiment: By comparing users' electricity consumption during the experiment with their historical electricity consumption, this experiment explores whether users choose to shift their electricity usage from peak periods to off-peak and shoulder periods.

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

1 Treatment groups
This experiment has five treatment groups, and each group is planned to have 2000 subjects.
Control group
Knowledge group - frequency 1
Knowledge group - frequency 2
Knowledge group - frequency 3
Knowledge group - frequency 4

2 Treatment design
This experiment plans to send SMS messages to all 5 treatment groups every Monday lasting for 8 weeks. Different groups have different sending cycles.

3 Randomization
The data used for randomization is from 10000 households, covering 15 Jan to 21 Jan 2024, including household ID and the electricity consumption in each hour.

Experimental Design Details

Not available

Randomization Method

Stratified randomization by STATA

Randomization Unit

Household

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

10000 Households

Sample size: planned number of observations

10000 Households

Sample size (or number of clusters) by treatment arms

2000 Control group
2000 Knowledge group - frequency 1
2000 Knowledge group - frequency 2
2000 Knowledge group - frequency 3
2000 Knowledge group - frequency 4

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Unit of measurement: change of hourly average electricity consumption during peak hours. For an error probability of alpha = 0.05, a power of 1- k = 0.95, and the standardized minimum detectable effect size is 0.1, N =1278 per treatment group.

Supporting Documents and Materials

IRB

Institutional Review Boards (IRBs)

IRB Name

School of Economics and Management，Beijing Jiaotong University

IRB Approval Date

2023-09-08

IRB Approval Number

B23SK00560

Analysis Plan