Energy Conservation for Non-Solar Hours: Experimental Evidence from India

Last registered on March 05, 2026
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Pre-Trial

Trial Information

General Information

Title
Energy Conservation for Non-Solar Hours: Experimental Evidence from India
RCT ID
AEARCTR-0016644
Initial registration date
February 26, 2026

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 05, 2026, 6:45 AM EST

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
Saksham Singh
Affiliation
UW-Madison
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Other Primary Investigator(s)

PI Name
Anirudh Tagat
PI Affiliation
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PI Name
Deepansh Jagga
PI Affiliation
PI Name
Yiwei Zhang
PI Affiliation
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Additional Trial Information

Status
In development
Start date
2026-03-15
End date
2026-07-31
Keywords
Environment & Energy
Additional Keywords
JEL code(s)
C93, Q48, N75
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
Developing countries face a dual challenge of rising electricity demand from climate-induced temperature increases and the simultaneous pressure to decarbonize energy systems. In India, solar generation has become cost-competitive, yet the daily “duck curve” load profile produces carbon-intensive evening peaks. While time-of-use pricing is politically and institutionally constrained, non-price behavioral interventions offer a promising alternative for managing residential demand.

This study evaluates outcomes from a randomized controlled trial (RCT) of a demand response program implemented by a major distribution utility in India. The intervention leverages WhatsApp as the delivery platform to test four approaches: financial incentives, financial incentives (non-linear), descriptive social norms, and informational tips. Over 30,000 households are enrolled. The program is organized around discrete demand response events during evening peak demand, where treatment households receive notifications and earn symbolic rewards based on relative reductions in electricity use.

The study evaluates the relative performance of three interventions: 1) peer comparison, 2) financial incentives, and 3) financial incentives (non-linear pricing), on household electricity consumption during demand response events. Outcomes are measured using anonymized smart meter data combined with WhatsApp engagement metrics. By comparing behavioral and financial interventions in a developing country setting, the study provides evidence on scalable, non-price tools for peak demand management.
External Link(s)

Registration Citation

Citation
Jagga, Deepansh et al. 2026. "Energy Conservation for Non-Solar Hours: Experimental Evidence from India." AEA RCT Registry. March 05. https://doi.org/10.1257/rct.16644-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
The communication strategy is structured around three types of messages:
- Notifications: Days ahead messages sent in advance of each event, explaining its purpose (reducing peak demand, lowering emissions), and describing the incentives available. These messages set expectations and encourage participation.
- Alerts: Hours ahead reminders sent on the day of the event, emphasizing urgency and encouraging immediate action (e.g., “Event start at 8 PM tonight—reduce usage to save and earn rewards!”). These alerts may also highlight the role of peers or the advance incentive provided.
- Feedback Messages: Sent after the event, providing customers with personalized information on their performance. Depending on treatment arm, feedback may include:
-- Confirmation of rewards earned (Financial Incentives)
-- Peer comparisons (Descriptive Social Norms)
-- Reinforcement of conservation behavior through tips and encouragement
Intervention Start Date
2026-03-15
Intervention End Date
2026-06-30

Primary Outcomes

Primary Outcomes (end points)
- Electricity consumption (kWh)
- Link clicks
- WhatsApp meta-data
- Message performance
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The intervention is a randomized controlled trial (RCT) designed to test the effectiveness of different behavioral levers in reducing evening peak electricity demand. The program is implemented in partnership with a major distribution utility in India and delivered through WhatsApp, a widely used communication platform.

Households are randomly assigned to treatment and control groups. Treatment groups receive behaviorally informed messages during designated demand response events (8:00 PM–10:00 PM), when solar generation falls and the grid relies on carbon-intensive fossil fuels. The messages are structured around three main approaches:
- Financial Incentives: Customers are informed they can earn rewards based on the extent of their electricity savings relative to baseline consumption. A sub-randomized group will receive advance unconditional incentives (Rs. 20) and advance information on potential savings.
- Financial Incentives (non-linear): Customers are informed they can earn rewards based on the extent of their electricity savings relative to baseline consumption. Customers will be eligible for higher electricity rebates if they save more. A sub-randomized group will receive advance unconditional incentives (Rs. 20) and advance information on potential savings.
- Descriptive Social Norms: Customers receive peer-comparison messages that highlight how their electricity use compares to that of similar households in their neighborhood.
A fourth informational stream delivers energy-saving tips, designed to complement other treatments but not tied to incentives.
Experimental Design Details
Not available
Randomization Method
Randomization will be conducted through stratified random sampling to ensure balanced representation of households across key characteristics that are likely to influence treatment response. The sampling frame will be drawn from residential customers with smart meters in the utility’s service area.
Strata will be defined on the basis of, sanctioned load

Within each stratum, households will be randomly assigned by computer to one of the treatment groups (Financial Incentives, Bonus Financial Incentives, Descriptive Social Norms, Energy-Saving Tips) or the control group. Stratification ensures that treatment and control groups are comparable in terms of baseline consumption, while preserving the integrity of random assignment.
Randomization Unit
Individual customers
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
30000
Sample size: planned number of observations
30000
Sample size (or number of clusters) by treatment arms
Control Group: ~6,000 households
Treatment 1 (Financial Incentives): ~6,000 households
Treatment 2 (Financial Incentives- Non-linear): ~6,000 households
Treatment 3 (Descriptive Social Norms): ~6,000 households
Treatment 4 (Energy-Saving Tips): ~6000 households
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Monk Prayogshala IRB
IRB Approval Date
2025-06-05
IRB Approval Number
#176-025
Analysis Plan

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