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Solar Energy Evolution and Diffusion Studies

A street and a row of townhomes with solar panels on each roof.

The Solar Energy Evolution and Diffusion Studies (SEEDS) are a series of industry-wide studies that use data-driven and evidence-based methods to identify characteristics, motivations, and barriers to photovoltaic (PV) adoption.

SEEDS 2017-2019 Study

The National Renewable Energy Lab (NREL) is leading a 3-year study funded under the U.S. Department of Energy’s (DOE’s) SEEDS-2 program to identify new strategies to dramatically boost solar adoption rates in low and moderate income (LMI) communities. The goal of the program is to give LMI communities the same access to solar power that wealthier communities often enjoy.

A map of the United States is color-coded by zip code to show nationwide suitability of small buildings for solar power.  The greatest potential, above 90% can be found in south Florida and much of Texas. There is significant variation, but potential is generally less in more northern states, with less than 70% potential in parts of northern Washington, Idaho, Montana, and Minnesota.

In determining the solar technical potential of the LMI market in the United States, the SEEDS 2017-2019 study will build off previous NREL work, shown here, that found widespread suitability for rooftop solar power on small buildings in the United States (Gagnon et al 2016).

A cross-disciplinary research team will:

  • Identify social barriers to PV adoption in LMI communities
  • Develop new datasets and modeling approaches to analyze solar diffusion
  • Validate alternative marketing techniques and ownership models that could reach these households at scale.

SEEDS 2014-2016 Study

The SEEDS 2017-2019 study builds upon the SEEDS 2014-2016 study, which was funded by DOE and led by NREL to understand the evolution of customer motivations and adoption barriers in residential PV markets. Through three surveys, the project collected new data to understand characteristics of consumers who have adopted solar for their homes, those who have considered solar, and those who have not considered it for their homes.

The market data revealed that:

  • Economic considerations are the biggest overall driver—but also the largest barrier—to solar adoption
  • Current solar adopters are overwhelmingly satisfied and likely to refer others
  • A large fraction of consumers have not seriously considered solar for their home.

Informed by the market data, the project developed models of U.S. household PV adoption. The project also conducted two market pilots to test methods to increase lead generation and conversion using digital marketing.

To learn more about some of the most useful insights revealed by the SEEDS 2014-2016 study check out "Seven Common Mistakes Solar Installers Make."


Over the course of the SEEDS program, NREL researchers and their collaborators have published research on many topics related to solar adoption. These publications are collected here, organized by year of publication.

Rooftop Solar Technical Potential for Low-to-Moderate Income Households in the United States

Relying on LiDAR scans, Census data, and complex statistical analysis, this study provides a novel assessment of the solar generation potential in low-to-moderate income (LMI) households in the United States, demonstrating that LMI rooftop solar could contribute up to 42 percent of all rooftop technical potential in the residential sector.

Agent‐Based Explorations of Environmental Consumption in Segregated Networks

This chapter, part of a book on social systems engineering, presents a theoretical, agent‐based model of how individuals in a social system make choices about adopting a high‐cost, environmentally friendly technology such as solar PV. The authors present the agent-based model in detail and discuss its implications.

Explaining Interest in Adopting Residential Solar Photovoltaic Systems in the United States: Toward an Integration of Behavioral Theories

This study, published in Energy Research & Social Science, proposes a theoretical framework for investigating the psychological and social determinants of interest in residential solar. It draws from three theories that may explain the decision to pursue solar: diffusion of innovations theory, theory of planned behavior, and value-belief-norm theory. The framework is tested using survey data from 904 non-adopter homeowners, with the aim of identifying potential levers for intervention.

A Non-Modeling Exploration of Residential Solar Photovoltaic (PV) Adoption and Non-Adoption

This study helps to inform a more detailed understanding of residential PV adoption, consideration, and non-adoption, as well as attitudes and experiences with PV overall. The study draws on a diverse set of survey data—collected from nearly 3,600 single-family, owner-occupied households across four different states—to examine residential PV adoption and non-adoption, the varieties of adopters and non-adopters, and the roles of policies and marketing in shaping these segments.

The Price-Concentration Relationship in Early Residential Solar Third-Party Markets

It is often assumed that more competition leads to lower prices in residential PV markets, but this is not universally true. This study focuses on identifying the causal relationship between market structure and the prices paid by consumers. Using a unique data set of third-party-owned contract terms for the residential solar PV market in the San Diego Gas & Electricity service territory, this study finds that firms charged higher prices in more competitive markets in the sample.

Using Machine Learning and Data Analysis to Improve Customer Acquisition and Marketing in Residential Solar

This fact sheet offers a broad overview of the work SEEDS researchers have undertaken to improve our understanding of solar adoption and to reduce the costs of customer acquisition and marketing.

Agent-Based Modelling of Consumer Energy Choices

This study, published in Nature Climate Change, provides an overview of agent-based modeling (ABM) work in the area of consumer energy choices, with a focus on identifying specific ways in which ABM can improve understanding of the demand side of energy to aid the design of better policies and programs. The study also touches on future research needs for improving the practice of ABM to better understand energy demand.

The Distributed Generation Market Demand Model (dGen): Documentation

The dGen model is a geospatially rich, bottom-up, market-penetration model that simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the continental United States through 2050. NREL developed dGen to analyze the key factors that will affect future market demand for distributed solar, wind, storage, and other DER technologies in the United States within a single modeling platform.


Watch videos and download presentations from webinars about the SEEDS studies.

More Information

As the SEEDS 2017-2019 study progresses, more information and resources will become available on this website. Learn more about DOE’s SEEDS-2 program. If you have questions about NREL’s work on the SEEDS project, contact Ben Sigrin.