Agrivoltaics information and community preferences for utility-scale solar energy systems

Last registered on April 03, 2025
View Trial History

Pre-Trial

Trial Information

General Information

Title
Agrivoltaics information and community preferences for utility-scale solar energy systems
RCT ID
AEARCTR-0015622
Initial registration date
March 27, 2025

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
April 03, 2025, 11:11 AM EDT

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

Locations

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Primary Investigator

Name
Jian Chen
Affiliation
Iowa State University
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Hongli Feng
PI Affiliation
Iowa State University
Contact Investigator

Additional Trial Information

Status
In development
Start date
2025-03-26
End date
2026-03-31
Keywords
Agriculture, Behavior, Environment & Energy
Additional Keywords
Agrivoltaics, community preferences, information treatments, land quality, utility-scale solar energy
JEL code(s)
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
Utility-scale solar development has raised considerable local land use concerns. Agrivoltaic systems, which integrate solar energy production with agricultural activities, have emerged as a promising solution to mitigate land-use conflicts associated with utility-scale solar development. Through a combination of an information treatment experiment and a choice experiment, this study investigates how evidence-based information about dual-land use of agrivoltaic systems, including positive, cautious, and balanced information framing, can shift community preferences for utility-scale solar projects, valuations for project attributes and the trade-offs between utility-scale solar development and the preservation of high-quality farmland.
External Link(s)

Registration Citation

Citation
Chen, Jian and Hongli Feng. 2025. "Agrivoltaics information and community preferences for utility-scale solar energy systems." AEA RCT Registry. April 03. https://doi.org/10.1257/rct.15622-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
We will implement a survey with an information treatment experiment and a choice experiment.

The information treatment experiment is designed with an emphasis on different framing of information concerning agrivoltaics systems: the control group receives no information, one category focuses on positive information related to the integration of utility-scale solar energy production and agricultural activities, one category provides cautious information related to agrivoltaics, and the remaining categories offer balanced information highlighting both positive and cautious sides of agrivoltaics.

The choice experiment features 4 attributes, each with two to three levels. The four attributes are expected carbon emissions reduction relative to coal-fired power plants, expected annual lease payment to landowners, expected savings on the monthly electricity bill for your household, and land quality of the occupied farmland. Participants will be presented with six choice scenarios. In each scenario, we present two potential plans, and the participants are asked to report which plan they were more likely to support in their community and their preferences for "opt-out" options.
Intervention Start Date
2025-03-27
Intervention End Date
2026-03-31

Primary Outcomes

Primary Outcomes (end points)
Preferences for utility-scale solar projects and agrivoltaics projects; choices of proposed utility-scale solar projects
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Participants will be randomly assigned to one of the four versions of the information treatment, each with one category of information. The D-optimal design yields choice scenarios that are divided into two blocks and participants are randomly assigned to one of the two survey blocks, each containing six scenarios. In each scenario, we presented two potential plans for a typical medium-sized solar PV project (i.e., 50 MW of nameplate capacity) that are under consideration within a local community; the two plans are identical except for variations in attribute levels. Participants were asked to report which plan they were more likely to support in their communities, and their preferences for "opt-out" options. We also include a series of views questions regarding solar energy systems and demographic questions in the survey.
Experimental Design Details
Not available
Randomization Method
Randomization of information treatment versions and choice experiment blocks by Qualtrics.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1000
Sample size: planned number of observations
1000
Sample size (or number of clusters) by treatment arms
250 for the control group and each information treatment group, and 500 for each choice experiment block.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Iowa State University Institutional Review Board
IRB Approval Date
2025-02-07
IRB Approval Number
22-306
Analysis Plan