Search NASA⌕ Search

SEARCH · Search NASA

Results for “solar adoption”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

Characterizing local rooftop solar adoption inequity in the US

Abstract Residential rooftop solar is slated to play a significant role in the changing US electric grid in the coming decades. However, concerns have emerged that the benefits of rooftop solar deployment are inequitably distributed across demographic groups. Previous work has highlighted inequity in national solar adopter deployment and income trends. We leverage a dataset of US solar adopter household income estimates—unique in its size and resolution—to analyze differences in adoption equity at the local level and identify those conditions that yield more equitable solar adoption, with implications for policy strategies to reduce inequities in solar adoption. The solar inequities observed at the national and state levels also exist at more granular levels, but not uniformly so; some US census tracts exhibit less solar inequity than others. Some demographic, solar system, and market characteristics robustly lead to more equitable solar adoption. Our findings suggest that while solar adoption inequity is frequently attributed to the relatively high costs of solar adoption, costs may become less relevant as solar prices decline. Results also indicate that racial diversity and education levels affect solar adoption patterns at a local level. Finally, we find that solar adoption is more equitable in census tracts served by specific types of installers. Future research and policy can explore ways to leverage these findings to accelerate the transition to equitable solar adoption.

14 SOLAR ENERGY↗

Supply sunspots and shadows: Business siting patterns and inequitable rooftop solar adoption in the United States

Entrepreneurs in certain industries tend to locate new businesses in relatively affluent areas. Preferences to site businesses in affluent areas can reduce low-income household access to certain products. Some argue that business siting patterns could explain inequitable consumption patterns, though such causal claims are often empirically weak. Here, we explore whether business siting patterns partly explain inequitable adoption of rooftop solar photovoltaics in California. We show that solar business formation drives an immediate and sustained increase in local solar adoption, including in low-income areas. However, solar business siting patterns have only weak impacts on solar adoption equity. The data show how solar businesses headquartered in low-income areas nonetheless install solar for relatively affluent customers. Customer-level adoption inequity partly offsets the potential equity gains of siting more businesses in low-income areas. We discuss how the emergent nature and unique business model of rooftop solar help explain these nuanced results.

14 SOLAR ENERGY↗

Residential Solar-Adopter Income and Demographic Trends: November 2022 Update [Slides]

The report describes income, demographic, and other socio-economic trends among U.S. residential rooftop solar adopters. The report is based on address-level data for roughly 2.8 million residential rooftop solar systems installed through 2021, representing 86% of all U.S. systems. With its unique size, geographic scope, and level of detail, this report is intended to serve as a foundational reference document for policy-makers, industry stakeholders, and researchers. Key findings include the following: -Median solar adopter income was about $\$110$k/year in 2021, compared to a U.S. median of about $\$63$k/year for all households and $\$79$k/year for all owner-occupied households -The degree of income skew varies significantly across all states, but all states exhibit some positive income skew, with median solar-adopter incomes ranging from 131-168% of the respective county-median income for all households -Notwithstanding the fact that solar adopter incomes skew high, a substantial share of adopters could be considered low-to-moderate income (LMI), with 22% of all 2021 adopters earning less than 80% of area median income, and an additional 21% between 80% and 120% of area median income. -Solar-adopter incomes are declining over time, with median incomes dropping from $\$129$k in 2010 to $\$110$k in 2021, as adoption becomes more proportionately distributed across the population and has started to broaden into low- and middle-income states since 2016. -Solar-adopter incomes are consistently higher for systems paired with battery storage, for host-owned systems, and for systems installed on single-family homes; higher income adopters also consistently install larger systems. -Solar adopters tend to live in Census Tracts not identified as “disadvantaged communities” (using the U.S. Department of Energy’s interim definitions developed March 2022), making up 11% of adopters compared to 18% of U.S. households. -Compared to the broader population, solar adopters tend to: identify as Non-Hispanic White, be primarily English-speaking, have higher education levels, be middle-aged, work in business and finance-related occupations, and live in higher-value homes In conjunction with the report, Berkeley Lab has published an updated accompanying set of online data visualizations that allow users to further explore the underlying data. Berkeley Lab is also offering related analytical support to states, local agencies, and other organizations on issues related to solar adoption among low-to-moderate income households; requests for analytical support may be submitted through this online form.

13 HYDRO ENERGY↗

Residential Solar-Adopter Income and Demographic Trends: 2024 Update [Slides]

The report describes income, demographic, and other socio-economic trends among U.S. residential rooftop solar adopters. The report is based on address-level data for roughly 4.1 million residential rooftop solar systems installed through 2023, representing 87% of all U.S. systems. With its unique size, geographic scope, and level of detail, this report is intended to serve as a foundational reference document for policy-makers, industry stakeholders, and researchers. Key findings include the following: -The median income of households that installed solar in 2023 was about $\$$115k/year, compared to a U.S. median of $\$$75k/year for all households and $\$$94k/year for all U.S. owner-occupied households. -Compared to owner-occupied households in the same state, 2023 solar-adopter incomes were 7% higher in the median case, and in 10 states, median solar-adopter incomes were below the corresponding median income for all owner-occupied households. -Roughly 49% of solar adopters in 2023 had incomes below 120% of their area median income (AMI), a threshold sometimes used to define “low-and-moderate income” (or LMI), while 26% were below 80% of AMI, often used to define “low-income”. -Solar adoption continues to shift toward less affluent households over time, with the median present-day income of solar adopters dropping from $\$$141k for households that installed systems in 2010 to $\$$115k in 2023. -PV systems installed in 2023 by households earning less than $\$$50k had a median size of 6.4 kW, 33% were third-party owned, and 6% included battery storage, compared to corresponding values of 8.0 kW, 18%, and 14% for households earning more than $\$$200k. -Compared to all households in their respective state, solar adopters in 2023 were slightly more likely to be college educated and to live in rural areas; had higher home values; and were more likely to live outside a disadvantaged community (DAC), be middle-aged, identify as non-Hispanic white, work in a business or financial occupation, and own a single-family home. In conjunction with the report, Berkeley Lab has published an updated accompanying set of online data visualizations that allow users to further explore the underlying data. Berkeley Lab is also offering related analytical support to states, local agencies, and other organizations on issues related to solar adoption among low-to-moderate income households; requests for analytical support may be submitted through this online form.

14 SOLAR ENERGY↗

Residential Solar-Adopter Income and Demographic Trends: 2023 Update [Slides]

The report describes income, demographic, and other socio-economic trends among U.S. residential rooftop solar adopters. The report is based on address-level data for roughly 3.4 million residential rooftop solar systems installed through 2022, representing 86% of all U.S. systems. With its unique size, geographic scope, and level of detail, this report is intended to serve as a foundational reference document for policy-makers, industry stakeholders, and researchers. Key findings include the following: (1) Median solar adopter income was about $\$117$k/year in 2022, compared to a U.S. median of about $\$69$k/year for all households and $\$86$k/year for all owner-occupied households; (2) The degree of income skew varies significantly across all states, but all exhibit some positive income skew relative to all households in the state, with median solar-adopter incomes ranging from 108-180% of the respective state-median income for all households; (3) Roughly 45% of solar adopters in 2022 had incomes below 120% of their area median income (AMI), a threshold sometimes used to define “low-and-moderate income” (or LMI), while 23% were below 80% of AMI, often used to define “low-income”; (4) Solar adoption continues to shift toward less affluent households, with the median current income of solar adopters dropping from $\$140$k for households that installed systems in 2010 to $\$117$k in 2022; (5) PV systems installed in 2022 by households earning less than $50k had a median size of 6.1 kW, 34% were third-party owned, and 5% included battery storage, compared to corresponding values of 7.6%, 17%, and 15% for households earning more than 200 dollars k; and (6) Compared to all households in their respective state, solar adopters tend to be negligibly more rural; have higher home values; and are more likely to be college educated, identify as non-Hispanic white, live outside a disadvantaged community (DAC), be middle-aged, work in a business or financial occupation, and own a single-family home In conjunction with the report, Berkeley Lab has published an updated accompanying set of online data visualizations that allow users to further explore the underlying data. Berkeley Lab is also offering related analytical support to states, local agencies, and other organizations on issues related to solar adoption among low-to-moderate income households.

14 SOLAR ENERGY↗

Residential Solar-Adopter Income and Demographic Trends: 2021 Update [Slides]

The report describes income, demographic, and other socio-economic trends among U.S. residential rooftop solar adopters. The report is based on data for roughly 1.9 million residential rooftop solar systems installed through 2019, representing 82% of all U.S. systems. With its unique size, geographic scope, and level of detail, this report is intended to serve as a foundational reference document for policy-makers, industry stakeholders, and researchers. Key findings include the following: Solar adopters generally skew towards higher incomes, though that trend continues to diminish over time. Solar adopter incomes vary considerably and encompass many low-to-moderate income (LMI) households. Solar-adopter incomes are consistently higher for systems paired with battery storage, for host-owned systems, and for systems installed on single-family homes. Solar adopters differ from the broader U.S. population in terms of a variety of other demographic and socioeconomic measures. State-level comparisons indicate that solar-adopters tend to live in neighborhoods with relatively high non-Hispanic White and Asian populations, and with relatively low Hispanic and Black populations. In conjunction with the report, Berkeley Lab has published an updated accompanying set of online data visualizations that allow users to further explore the underlying data. Berkeley Lab is also offering related analytical support to states, local agencies, and other organizations on issues related to solar adoption among low-to-moderate income households.

14 SOLAR ENERGY↗

New Pathways for Equitable Solar Adoption in Texas

As part of the SEIN Round 3 program, a diverse group of energy stakeholders in Texas set out to develop and pilot new pathways to increase rooftop solar adoption at no upfront cost to lowincome households. One potentially promising pathway we identified involved combining funding from existing utility and federal programs promoting weatherization and energy efficiency. Our objective was to demonstrate pilot projects that equitably deployed rooftop solar to properties owned or rented by families in disadvantaged communities. Our goal was to create a clear path for lowincome households to achieve electricity bill relief and to access clean energy by leveraging existing utility energy efficiency programs with existing federal resources, such as the U.S. Department of Health and Human Services (HHS) Low-Income Home Energy Assistance Program (LIHEAP) and/or U.S. Department of Energy (DOE) Weatherization Assistance Program (WAP) funding in Texas. This has been attempted in a few other states with varying degrees of success, but not yet in Texas.

14 SOLAR ENERGY↗

Addressing the Split Incentive Challenge for Enhanced Solar Adoption in Multifamily Rental Properties [Abstract]

The split incentive problem is particularly pronounced in rental markets, where landlords prioritize investments that directly increase property value or rental income. Since energy savings from solar photovoltaic (PV) systems primarily benefit tenants, landlords may perceive little return on investment unless mechanisms exist to recapture some of the financial gains. The primary objective of this project is to develop a publicly available, web-based tool to analyze the U.S. Department of Energy’s ResStock database, which models the U.S. residential building stock. The tool allows users to filter buildings by location, type, HVAC system, square footage, and other characteristics, and outputs typical electric load profiles. By leveraging location-specific electric load data, Fram Energy aims to advance business strategies that address the split incentive barrier and promote the adoption of solar PV installations in rental properties. In addition, a machine learning model will be developed to weigh the marginal contribution of building features across the dataset in predicting electricity demand, supporting guided decision making in forecasting electric load profiles. Lastly, based on each building’s location, load profile, and utility’s electricity rate, an optimized solar photovoltaic array and battery energy storage system will be sized to provide energy arbitrage opportunities.

14 SOLAR ENERGY↗

Residential Solar Adoption Timelines and Impacts from the COVID-19 Pandemic

In this study we evaluate PII and other PV adoption timelines from 2017-2021. We use project-level data collected by the National Renewable Energy Laboratory (NREL) for the Solar Time-Based Residential Analytics and Cycle Time Estimator (SolarTRACE). Additionally, we conducted a survey of 171 AHJs about their experiences, challenges, and process changes during the first 18 months of the COVID-19 pandemic. The survey findings were supplemented with follow up interviews with 5 AHJs from 4 states. We find that the pandemic moderately increased the duration and variability of pre-install timelines (contract signing to install), particularly in the permit review phase (permit submit to approval). In contrast, post-install timelines (install to final utility interconnection) continued to decline during the pandemic. The net result is that overall project timelines (contract signing to final interconnection) continued to decline during the pandemic. Our findings suggest that AHJs and installers faced challenges throughout the pandemic but ongoing improvements in PII processes - particularly post-install processes - more than offset these challenges. Furthermore, the pandemic may have catalyzed or accelerated a widespread adoption of online/electronic permitting, among other process efficiency improvements.

14 SOLAR ENERGY↗

Community Solar Reaches Adopters Underserved by Rooftop Solar

Community solar, a business model where multiple customers buy output from shared solar systems, has expanded solar access among multifamily housing occupants, renters, and low-income households. Policies to enable community solar could be expanded and benefits of access augmented through targeted measures to support community solar adoption in underserved communities.

community solar↗

Impacts of non-residential solar on residential adoption decisions

Household decisions to adopt rooftop solar photovoltaics are partly driven by social influence. Previous research on solar adoption influence has focused on influence among residential peers. Here, we expand the framework of solar adoption influence by exploring the influence of non-residential installations on residential adoption decisions. We use staggered differences-in-differences to estimate non-residential influence effects using a large data sample of residential adoptions. We also critically evaluate prevailing frameworks for solar adoption influence. We find that non-residential installations are associated with accelerated residential adoption rates, on the order of 0.4 additional residential adoptions per quarter per non-residential installation. We show that non-residential systems exert a continuous, long-term influence on residential adoption decisions. We explore separate results and influence mechanisms for solar installed on commercial buildings, government buildings, and houses of worship. The results suggest that non-residential solar adopters could serve as partners in policies to “seed” residential adoption in underserved communities.

14 SOLAR ENERGY↗

Advancing Solar Innovation for Low and Moderate-Income Households (Final Technical Report)

The overarching goal of this project was to deepen the understanding of the social and economic aspects of solar adoption, with a specific eye towards any pathways or barriers that could be identified that directly impact low and moderate-income households. Specific objectives included (1) identifying and assessing significant non-economic barriers that complicate the ability of LMI households to adopt and benefit from solar, even under scenarios with low economic barriers; (2) assessing the differential ability of groups to benefit from solar adoption based on their ability to invest in different solar innovations; (3) explaining why some LMI communities nonetheless experience significantly higher rates of solar adoption and benefit than others; (4) developing a methodological model for generating data addressing key issues to the project; and (5) designing and developing an interactive web portal that aggregates existing datasets, provides researchers trend analysis capabilities, standardizes project protocols for other states and communities; provides the opportunities for researchers using the same protocol in other communities to upload their results; and engages with the general public by providing them the ability to upload their own perspectives and stories of solar technology adoption. Through a common framework for conducting semi-structured field interviews. In partnership with cooperative extension services, in conjunction with survey research and the aggregation of existing solar adoption datasets, this study has identified that currently ,there is a strong values alignment and knowledge access challenge that continues to affect solar adoption. Participants in this study – many of whom are either low or moderate-income and/or live in underserved rural communities do not believe solar is an option where they live or believe solar is appropriate for their lifestyle. This perception challenge is further exacerbated by the absolute dearth of adopters in most communities and a total lack of local marketing for solar energy. What marketing that does exist is geared towards audiences other than those in the participant's community, reinforcing a perception that 22% of survey respondents (n = 1,551) have: that solar energy is not meant for them and their community. Overcoming these serious human challenges pertaining to knowledge and marketing are critical to reducing the customer acquisition costs incurred amongst LMI communities and especially those in rural America where the opportunities solar provides to increase local energy resilience, security, all while engaging in personal stewardship of the planet could align with local values. Community-Based Social Marketing, built in partnership with community leaders and geared towards meeting local visions of ideal life, is a near term opportunity to bridge the gap between local priorities and national market and policy imperatives for solar while moving towards the administration's goals for renewable energy as part of a just and equitable decarbonization program. The tools and methods developed for this study can serve as a template for identifying other specific local challenges for solar adoption in other state, and provide the opportunity for a common data framework for understanding system-wide trends and barriers to achieving uptake of residential solar in communities that may, ultimately, benefit the most from the technology.

14 SOLAR ENERGY↗

Social Learning and Solar Photovoltaic Adoption

Growing literature points to the effectiveness of leveraging social interactions and nudges to spur adoption of prosocial behaviors. This study investigates a large-scale behavioral intervention designed to actively leverage social learning and peer interactions to encourage adoption of residential solar photovoltaic systems. Municipalities choose a solar installer offering group pricing and undertake an informational campaign driven by volunteer ambassadors. We find a causal treatment effect of 37 installations per municipality from the campaigns and no evidence of harvesting or persistence. The intervention also lowers installation prices. Randomized controlled trials based on the intervention show that selection into the program is important, whereas group pricing is not. Our results suggest that the program provided economies of scale and lowered consumer acquisition costs, leading to low-cost emission reductions. This paper was accepted by Matthew Shum, marketing.

Business & Economics↗

Machine-Learning-Based Mapping and Modeling of Solar Energy with Ultra-High Spatiotemporal Granularity

Despite the rapid growth of solar energy, we still lack a dynamic, high-fidelity database that tracks the spatiotemporal variations of solar PVs and their associated infrastructures across different places at a spatially resolved scale. The absence of such data presents a barrier to various applications such as solar PV growth projection, solar energy integration, solar incentive design, and climate risk assessment. In this project, we aim to bridge this gap by developing AI-based algorithms to extract granular information about solar PV installations and their associated infrastructures (i.e., distribution grids) from widely available unstructured data like remote sensing images and street views. As a result, we have built the Solar Energy Atlas, a fine-grained, large-scale geospatial overlay of distributed solar PVs and distribution grids. On top of it, we have advanced the understanding of solar adoption and distribution grid vulnerability to climate-induced extremes. Our major contributions can be summarized as follow: (1) By developing new AI algorithms, we have built the most comprehensive solar PV spatiotemporal database covering the entire US. This is the first time we obtained the exact GPS locations, size, subtype, and installation year information for rooftop solar PVs across the US. This database can be used for solar PV growth projection, solar energy integration, solar energy policy analysis and design, and spatially-resolved climate risk assessment. (2) Leveraging this database, we have uncovered the socioeconomic driving factors that are correlated with earlier onset of solar adoption and higher saturated adoption levels. We have identified the heterogeneity in the effects of different types of financial incentives on solar adoption and provided implications for tailoring incentive design based on local income levels to promote equitable solar adoption. (3) We have developed a distribution grid GIS mapping algorithm which can obtain granular geospatial and topology information about distribution grids using multi-modal open data, reducing the dependency on hard-to-obtain smart meter data of conventional approaches. It shows effectiveness in both the U.S. and Sub-Saharan Africa. Using this algorithm, we have uncovered the non-uniform vulnerability of distribution grids to wildfires in California in the aspects of undergrounding protection and Distributed Energy Resources (DER) preparedness. This has provided important implications for improving the affordability and equity of grid adaptation approaches. (3) We have made our produced database publicly available and provided user-friendly interface to enable various stakeholders and the general public to interact with the data. We have also integrated the produced data into the Data Commons platform to enable the public to access the data and correlate it with other location-specific characteristics simply using natural language as queries. The impact of our project is three-fold: (1) New algorithms for mapping solar PVs and distribution grids across space and time, which are open source to facilitate researchers and industry; (2) New databases of solar PVs and distribution grids that have been made publicly available for engineering, social, and policy applications; (3) New understandings and actionable insights on the potential approaches to promoting solar adoption and reducing energy infrastructure vulnerabilities. In this report, we start by discussing the project background and motivation (section 5), followed by the overview of project objectives (section 6). Results and discussion for each task are presented in section 7. Significant accomplishments are summarized in section 8. This report will be concluded by discussing the paths forwards (section 9), products (section 10), and team roles (section 11).

14 SOLAR ENERGY↗

Affordable and Accessible Solar for All: Barriers, Solutions, and On-Site Adoption Potential

Solar energy technologies can be used as part of a suite of tools to reduce the energy burden of low-income customers, but to date, low- and moderate-income (LMI) customers have not adopted solar at the same rate as other income groups. This paper summarizes the barriers of LMI solar adoption related to finance and funding, community engagement, site suitability, policy and regulatory, and resilience and recovery and discusses existing and potential future solutions to address these barriers. In addition, we model future LMI on-site solar adoption, using the National Renewable Energy Laboratory's (NREL's) dGen model. We model future scenarios assuming no changes in the current LMI solar policy and program environment, and we add two incentives to low-income households for adopting solar: a $\$$3,000 incentive and a full incentive (i.e., the full cost of a PV system). While we model a financial incentive, this dollar reduction in cost could also come from other efforts, for example, reductions in solar soft costs. We find that by 2050, 48-49% of LMI households adopt solar, resulting in $\$$69- $\$$101 billion in first year utility bill savings to these consumers.

14 SOLAR ENERGY↗