Targeting High-Value Solar Installations to Reduce Costs to the Electric Grid

Last registered on May 17, 2019

Pre-Trial

Trial Information

General Information

Title
Targeting High-Value Solar Installations to Reduce Costs to the Electric Grid
RCT ID
AEARCTR-0003363
Initial registration date
October 03, 2018

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
October 04, 2018, 10:07 PM EDT

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

Last updated
May 17, 2019, 1:42 PM EDT

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

Locations

Primary Investigator

Affiliation
Yale University

Other Primary Investigator(s)

PI Affiliation
yale University

Additional Trial Information

Status
In development
Start date
2018-10-05
End date
2019-06-30
Secondary IDs
Abstract
In 2017, the installed capacity of distributed solar photovoltaics (PV) reached more than 16 gigawatts in the United States. Solar PV has seen increasing investment over the last several years due to improvements in technology and steady declines in prices. However, there is little consensus on what impact residential solar deployment will have on electricity grid systems. While solar advocates tout the many benefits of increased distributed solar PV development, many electric utilities have cited concerns over how new, intermittent, distributed resources will be incorporated into existing grid infrastructure and planning.
This study targets adoption of solar installations in areas with the highest potential value to the electric grid. We analyze the costs and benefits of these high-value solar installations to the electricity network, by measuring their effect on a number of network metrics.

External Link(s)

Registration Citation

Citation
Gillingham, Kenneth and Marten Ovaere. 2019. "Targeting High-Value Solar Installations to Reduce Costs to the Electric Grid." AEA RCT Registry. May 17. https://doi.org/10.1257/rct.3363-2.0
Former Citation
Gillingham, Kenneth and Marten Ovaere. 2019. "Targeting High-Value Solar Installations to Reduce Costs to the Electric Grid." AEA RCT Registry. May 17. https://www.socialscienceregistry.org/trials/3363/history/46692
Sponsors & Partners

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

Request Information
Experimental Details

Interventions

Intervention(s)
In each targeted subcircuit we are running a behavioral intervention designed to encourage solar adoption. This intervention involves a roughly 18-week campaign, a single chosen solar installation company (based on a competitive bidding process), discount pricing, a kick-off event, targeted communication, etc.
Intervention Start Date
2018-10-05
Intervention End Date
2019-06-30

Primary Outcomes

Primary Outcomes (end points)
Highly increased penetration of distributed solar PV generation in small local subcircuits (500-2000 customers).
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Measuring the effect of increased PV penetration on a number of network metrics like line loading, voltage, losses, outages and transformer loading.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
A set of subcircuits are matched to a number of utility-identified high-value subcircuits. The utility-identified subcircuits receive a utility-managed campaign, while the matched subcircuits are randomly assigned to a "Solarize" campaign and a control group. Both campaigns start at approximately the same time.

Partner utilities collect data on all residential solar installations in their coverage area as well as the network metrics.
Experimental Design Details
Randomization Method
Randomization done in office by a computer
Randomization Unit
Randomization is at the electric subcircuit level, after initial matching
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
20 subcircuits
Sample size: planned number of observations
20+ subcircuits
Sample size (or number of clusters) by treatment arms
2 subcircuits receive solar campaign + rate rider
4 subcircuits receive solar campaign (likely additional campaigns + controls depending on funding)
6 municipalities are in the control

+ Estimate for the ones in Eversource area?
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Yale Institutional Review Board
IRB Approval Date
2016-09-23
IRB Approval Number
1608018306

Post-Trial

Post Trial Information

Study Withdrawal

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

Request Information

Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials