Electricity consumption and effect pricing – A large-scale field experiment in Norway

Last registered on March 04, 2023

View Trial History

Pre-Trial

Trial Information

General Information

Title

Electricity consumption and effect pricing – A large-scale field experiment in Norway

RCT ID

AEARCTR-0005209

Initial registration date

December 26, 2019

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

January 03, 2020, 5:11 PM EST

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

Last updated

March 04, 2023, 2:19 AM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country

Norway

Region

Ringerike

Primary Investigator

Name

Øystein Hernæs

Affiliation

The Ragnar Frisch Centre for Economic Research

Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status

Completed

Start date

2018-11-01

End date

2020-04-30

Keywords

Environment & Energy

Additional Keywords

electricity consumption, energy, field experiments, nudges

JEL code(s)

C93, E21, L92, Q31

Secondary IDs

Prior work

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

Abstract

This study evaluates the impact of interventions aimed at reducing residential electricity consumption during peak load days. The main intervention will increase the price of consuming electricity in the afternoon and early evening on 10 selected days in the period November 2019-April 2020. These days will be announced by text messages. The text messages will further ask participants to reduce consumption to try to reduce electricity consumption if possible. The group assigned to this intervention will be compared to an intervention group assigned to receiving similar information that a peak load day is upcoming, but that will face no price changes, and a control group. Starting from peak load day 4, a subset of customers in the two intervention groups will also receive information about their consumption relative to their neighbors on peak load days.

External Link(s)

Registration Citation

Citation

Hernæs, Øystein. 2023. "Electricity consumption and effect pricing – A large-scale field experiment in Norway." AEA RCT Registry. March 04. https://doi.org/10.1257/rct.5209-1.1

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Intervention (Hidden)

Residential electricity customers are randomly assigned to one of three groups. We will call these the price, information or control group, respectively.

The price group
Prior to the start of the experiment, the price group will get an e-mail explaining that reducing peak load is desirable in order to reduce the investments needed to enlarge the grid. The e-mail will also say that the alternative is a higher rental grid charge to finance the investments. Then, the e-mail will provide the details about the pricing scheme the customer will face the coming winter and that they will be notified by text messages the day prior to each peak load event. Customers will have the opportunity to withdraw from participating (opt-out) if they contact the utility after receiving the e-mail.

The main intervention will increase the price of consuming electricity in the afternoon and early evening on 10 selected days in the period November 2019-April 2020. These days, which are predicted to be high load days, will be announced the day before by text messages. The text messages will state that the energy charge will increase to 7.5 NOK/kWh the next day in the time period 16-22 and that consumers can save money by reducing consumption.

The day after the peak load day, the customer will get a text message informing about how much the customer actually used and what the grid rental charge amounted to.

The information group
The information group will also get an e-mail prior to the experiment. This e-mail will only include the information for why reducing the peak load is desirable and that peak load days will be announced by text messages the coming winter.

The day before a peak load day, the information group will get a text message informing that a peak load day is upcoming. The text message will suggest reducing consumption in the time period 16-22 if possible. The information group will also get a text message the day after, informing about how much the customer actually used.

Intervention Start Date

2019-12-01

Intervention End Date

2020-04-30

Primary Outcomes

Primary Outcomes (end points)

Log of hourly electricity consumption in and outside of the treatment window (16-22).

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

Residential electricity customers are randomly assigned to one of three groups. We will call these the price, information or control group, respectively.

Experimental Design Details

The price group
Prior to the start of the experiment, the price group will get an e-mail explaining that reducing peak load is desirable in order to reduce the investments needed to enlarge the grid. The e-mail will also say that the alternative is a higher rental grid charge to finance the investments. Then, the e-mail will provide the details about the pricing scheme the customer will face the coming winter and that they will be notified by text messages the day prior to each peak load event. Customers will have the opportunity to withdraw from participating (opt-out) if they contact the utility after receiving the e-mail.

The main intervention will increase the price of consuming electricity in the afternoon and early evening on 10 selected days in the period November 2019-April 2020. These days, which are predicted to be high load days, will be announced the day before by text messages. The text messages will state that the energy charge will increase to 7.5 NOK/kWh the next day in the time period 16-22 and that consumers can save money by reducing consumption.

The day after the peak load day, the customer will get a text message informing about how much the customer actually used and what the grid rental charge amounted to.

The information group
The information group will also get an e-mail prior to the experiment. This e-mail will only include the information for why reducing the peak load is desirable and that peak load days will be announced by text messages the coming winter.

The day before a peak load day, the information group will get a text message informing that a peak load day is upcoming. The text message will suggest reducing consumption in the time period 16-22 if possible. The information group will also get a text message the day after, informing about how much the customer actually used.

Randomization Method

randomization done in office by a computer

Randomization Unit

Electricity meter (one per household)

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

11712

Sample size: planned number of observations

11712

Sample size (or number of clusters) by treatment arms

11712 / 3

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

From simulations based on data from the winter of 2018, we estimate that we will have a minimum detectable effect size of -0.017% at the 5% significance level with 80% power. This is only taking into account one treatment. kWh per hour. sd 1.4..

Supporting Documents and Materials

IRB