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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.

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At least 19 records
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DOE OSTI2022

AI-Driven Smart Community Control for Accelerating PV Adoption and Enhancing Grid Resilience

Rapid deployment of residential photovoltaic (PV) systems helps decarbonize our electricity supplies, but under certain circumstances, high-penetration PV may pose challenges to the electrical distribution grid. In a project funded by the U.S. Department of Energy's Solar Energy Technologies Office and Building Technologies Office, the National Renewable Energy Laboratory and its partners studied how flexible building loads and battery storage, when coordinated at home-level and community-level scales, can be used to address those challenges and enhance grid resilience. In this webinar, we will discuss the methodology, simulation and field pilot results, insights from partners, and lessons learned from the project.

artificial intelligence↗
DOE OSTI2022

Forecasting Distributed PV Adoption in Barranquilla, Colombia [Slides]

The objective of the dGen Colombia project is to provide projections to 2050 on distributed PV deployment by sector for a range of scenarios for Barranquilla, Colombia. NREL used the open-source Distributed Generation Market Demand Model (dGen) adapted for international projects for this analysis. As part of this analysis, technical potential, economic potential, and adoption projections of rooftop and groundmount PV for the city of Barranquilla are presented. Five main scenarios and their combinations were modeled to provide insight on the impact of increased demand from electric vehicles, air conditioning, and time-of-use tariffs.

14 SOLAR ENERGY↗
DOE OSTI2023

AI-Driven Smart Community Control for Accelerating PV Adoption and Enhancing Grid Resilience

The U.S. Department of Energy (DOE) has launched a Connected Communities program that supports projects that expand DOE's network of grid-interactive, efficient building communities nationwide. As an early pilot of Connected Communities, the National Renewable Energy Laboratory (NREL) and its partners have developed and demonstrated a community-scale, hierarchical control solution to address the potential grid issues arising from high penetration of solar photovoltaics (PV) as well as to improve grid reliability and resilience in this residential community. A field pilot study has been performed at an affordable housing development called the Basalt Vista Community, which was built for school teachers and other professionals in the local workforce and represents an autonomous energy grid with all-electric, energy-efficient homes. With no natural gas line in the community, this is the first all-electric net-zero community in rural Colorado. In the field pilot study, NREL has validated the performance of the hierarchical control solution, which consists of NREL's foresee home energy management systems (HEMS) and community aggregators, in increasing demand flexibility and self-consuming PV, reducing potential over-voltages, and supporting critical loads during emergency events. In this presentation, we will present the methodology, simulation and field pilot results, and lessons learned from the project.

all-electric community↗
DOE OSTI2025

Solar cities: A case study analysis of city-level enablers of expanded solar energy access

Rooftop solar photovoltaic (PV) adoption can benefit households by reducing electricity bills and enhancing energy resiliency. Low and moderate-income (LMI) households have been less likely to adopt PV and experience these benefits in the United States than higher-income households. Adopter income trends are often explored through quantitative analysis with limited explanatory power. Our quantitative analysis only explains around one-third of city-level variation in LMI adoption trends through socioeconomic factors such as median home values and income inequality and PV market factors such as cumulative adoption and incentives. We implement semi-structured interviews in three case studies of cities with relatively high rates of LMI PV adoption to better understand the factors that explain PV adopter income trends. The case studies partly reiterate findings from quantitative analysis, such as the role of PV incentives. The case studies reveal a broader set of LMI adoption drivers that are missed in quantitative analyses. The case studies show how city contexts can affect LMI adoption, such as the role of supportive city governments. The case studies also reveal the importance of partnerships, such as partnerships between city governments and state LMI PV program implementers. Finally, interviewees emphasized the importance of building trust among prospective LMI PV adopters. Interviewees suggested that partnerships, outreach, and consumer protection measures were crucial to building trust in PV installers among LMI households.

Adoption↗
DOE OSTI2022

Rooftop solar incentives remain effective for low- and moderate-income adoption

Financial incentives for rooftop solar photovoltaic (PV) adoption have declined in the United States over time by policy design. Incentive phase-down can efficiently promote early adoption and avoid ineffective payments to late adopters. Furthermore, incentive phase-down may exclude low- and moderate-income (LMI) households from realizing the same financial benefits from PV adoption as high-income early adopters. Here, data from two state-level LMI PV incentive programs are analyzed to test whether incentives still drive PV adoption among LMI households. As a first order approximation, the analysis suggests that incentives drove adoption that would not otherwise have happened in about 80% of cases. To the extent that policymakers prioritize PV adoption equity as part of the emerging energy justice policy agenda, the results suggest that ongoing incentive support for LMI adoption may be merited.

14 SOLAR ENERGY↗
DOE OSTI2021

City-Wide Distributed Roof-Top Photovoltaic System Adoption Forecast, Grid Impact Simulation, & Neighborhood Microgrid Contribution Assessment

The adoption of distributed photovoltaic (PV) systems grew significantly in recent years. Market projections anticipate future growth for both residential and commercial installations. To understand grid impacts associated with distributed PV, useful hosting capacity studies require accurate representations of the spatial distribution of PV adoptions. Prediction of PV locations and numbers depends on median income data, building use zoning maps, and permit records to understand existing trends and predict future adoption rates and locations throughout an entire city. Using the PV adoption data, advanced and realistic simulations were performed to capture the distributed PV impacts on the grid. Also, using graph theory community detection hundreds of neighborhood microgrids can be discovered for the entire city by identifying densely connected loads that are sparsely connected to other communities. Then, based on the PV adoption predictions, this work identified the contribution of PV within each of the newly discovered graph theory defined microgrid communities.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Machine learning reduces soft costs for residential solar photovoltaics

Further deployment of rooftop solar photovoltaics (PV) hinges on the reduction of soft (non-hardware) costs—now larger and more resistant to reductions than hardware costs. The largest portion of these soft costs is the expenses solar companies incur to acquire new customers. In this study, we demonstrate the value of a shift from significance-based methodologies to prediction-oriented models to better identify PV adopters and reduce soft costs. We employ machine learning to predict PV adopters and non-adopters, and compare its prediction performance with logistic regression, the dominant significance-based method in technology adoption studies. Our results show that machine learning substantially enhances adoption prediction performance: The true positive rate of predicting adopters increased from 66 to 87%, and the true negative rate of predicting non-adopters increased from 75 to 88%. We attribute the enhanced performance to complex variable interactions and nonlinear effects incorporated by machine learning. With more accurate predictions, machine learning is able to reduce customer acquisition costs by 15% ($0.07/Watt) and identify new market opportunities for solar companies to expand and diversify their customer bases. Our research methods and findings provide broader implications for the adoption of similar clean energy technologies and related policy challenges such as market growth and energy inequality.

14 SOLAR ENERGY↗
DOE OSTI2023

The electric vehicles-solar photovoltaics Nexus: Driving cross-sectoral adoption of sustainable technologies

Residential and transportation energy consumption account for more than one-half of the overall energy consumption in the United States. Adoption of electric vehicles (EVs) can play a key role in decarbonizing the transportation sector, while the adoption of renewable energy sources (e.g., solar photovoltaics [PVs]) could bring similar benefits to the residential energy sector and in turn support transport electrification. Although the market shares for both EVs and PVs continue to grow, both of these emerging technologies are deployed rather disjointly, without considering the existence of potential similarities among users who own (or aspire to own) these technologies. This might be due to lack of understanding of the behavioral interdependence in consumer preferences toward these technologies. To fill this gap in knowledge, this study utilizes data from the 2018 WholeTraveler Transportation Behavior Study to develop an integrated model system that explores interactive EV and PV adoption behaviors. A structural equation model is employed that incorporates direct effects as well as error correlations among the adoption behaviors for EVs and PVs. Model results indicate that the adoption behavior for both these technologies is indeed interconnected and significantly influenced by attitudes, values, and personality traits. Findings from this research suggest that incentives (e.g., subsidies) that drive bundled adoption of EV-PV systems could accelerate the adoption of both of these sustainable technologies. In conclusion, this study highlights the need to consider transport and building energy-efficient technology adoption behavior in a single integrated structure.

14 SOLAR ENERGY↗
DOE OSTI2022

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↗
DOE OSTI2025

The missing correlation between the potential rate impacts of rooftop solar and the timing of state net metering policy revisions

Residential solar photovoltaic (PV) output in most states is credited at the retail electricity rate, a policy commonly known as net metering. Twelve states have replaced net metering with alternative rate structures that reduce PV adopter bill savings. Proponents of these revisions argue that net metering increases the electricity rates of customers without PV. Here, we analyze the degree to which the timelines of net metering revisions have correlated with potential electricity rate impacts. We estimate that potential rate impacts at the end of 2023 were less than 1% of typical customer bills in 37 of 44 states that have offered net metering. There are no statistically significant differences in average or median estimated rate impacts between states that have and have not revised net metering. Nine of the states that had revised net metering did so when estimated impacts were less than 1% of typical customer bills. Many states have retained net metering into higher PV deployment levels with increased risk of potential rate impacts. Only two states—California and Hawaii—retained net metering beyond estimated rate impacts of 5%, and both have revised net metering. These findings do not suggest a clear, consistent link between net metering revision timelines and potential rate impacts. The timing and nature of net metering revisions are ultimately policy decisions based on state-level priorities and considerations.

14 SOLAR ENERGY↗
DOE OSTI2026

Selecting Critical Scenarios of DER Adoption in Distribution Grids Using Bayesian Optimization

We develop a new methodology to select scenarios of DER adoption most critical for distribution grids. Anticipating risks of future voltage and line flow violations due to additional PV adopters is central for utility investment planning but continues to rely on deterministic or ad hoc scenario selection. We propose a highly efficient search framework based on multi-objective Bayesian Optimization. We treat underlying grid stress metrics as computationally expensive black-box functions, approximated via Gaussian Process surrogates and design an acquisition function based on probability of scenarios being Pareto-critical across a collection of line- and bus-based violation objectives. Our approach provides a statistical guarantee and offers an order of magnitude speed-up relative to a conservative exhaustive search. Case studies on realistic feeders with 200-400 buses demonstrate the effectiveness and accuracy of our approach.

Mulkin, Olivier↗
DOE OSTI2025

The Missing Correlation Between the Potential Rate Impacts of Rooftop Solar and the Timing of State Net Metering Policy Revisions

Data supporting the article “The Missing Correlation Between the Potential Rate Impacts of Rooftop Solar and the Timing of State Net Metering Policy Revisions” (https://www.nlr.gov/docs/fy25osti/93543.pdf). Residential solar photovoltaic (PV) output in most states is credited at the retail electricity rate, a policy commonly known as net metering. Twelve states have replaced net metering with alternative rate structures that reduce PV adopter bill savings. Proponents of these revisions argue that net metering increases the electricity rates of customers without PV. Here, we analyze the degree to which the timelines of net metering revisions have correlated with potential electricity rate impacts. We estimate that potential rate impacts at the end of 2023 were less than 1% of typical customer bills in 37 of 44 states that have offered net metering. There are no statistically significant differences in average or median estimated rate impacts between states that have and have not revised net metering. Nine of the states that had revised net metering did so when estimated impacts were less than 1% of typical customer bills. Many states have retained net metering into higher PV deployment levels with increased risk of potential rate impacts. Only two states-California and Hawaii-retained net metering beyond estimated rate impacts of 5%, and both have revised net metering. These findings do not suggest a clear, consistent link between net metering revision timelines and potential rate impacts. The timing and nature of net metering revisions are ultimately policy decisions based on state-level priorities and considerations.

14 SOLAR ENERGY↗
DOE OSTI2025

Rooftop Solar Deployment, Potential Electricity Rate Impacts, and the Timing of Revisions to State Net Metering Policy

Most U.S. states require utilities to credit residential solar photovoltaic (PV) output at the retail electricity rate, a structure known as net metering. However, 12 states have replaced net metering with alternative rate structures that reduce PV adopter bill savings. The share of households living in states that require net metering fell from around 84% in 2014 to around 57% by the end of 2023. Proponents of net metering revisions have argued that net metering can affect the electricity rates of customers without PV. This report analyzes the relationships between state PV deployment levels, potential electricity rate impacts on PV nonadopters, and the timing of revisions to net metering policy.

14 SOLAR ENERGY↗
DOE OSTI2025

Residential and Small Commercial Solar Photovoltaic and Storage Permitting, Inspection, and Interconnection Timelines: A Retrospective Review (2017-2023)

This report is part of the ongoing Solar Time-Based Residential Analytics and Cycle Time Estimator (SolarTRACE) project, led by the National Renewable Energy Laboratory (NREL). The SolarTRACE project utilizes time-stamped project-level data provided by installer-partners to assess nationwide and AHJ- and utility-level PI&I and other solar PV adoption timelines since 2017. Our dataset now covers 22% of residential solar and 33% of residential storage installs in the U.S. since 2017. This report provides an update to our previous 2022 report (Cruce et al., 2022b) and includes: updated 2017 2023 project timelines for residential rooftop solar PV up to 20kW; updated tracking of permitting process changes at nearly 4,000 AHJs nationwide; and first-ever reporting of timelines for residential PV+storage projects up to 20kW.

14 SOLAR ENERGY↗
DOE OSTI2022

Encouraging voluntary government action via a solar-friendly designation program to promote solar energy in the United States

Sustainable development requires an accelerated transition toward renewable energy. In particular, substantially scaling up solar photovoltaics (PV) adoption is a crucial component of reducing the impacts of climate change and promoting sustainable development. However, it is challenging to convince local governments to take action. This study uses a combination of propensity score matching (PSM) and difference-in-differences (DID) models to assess the effectiveness of a voluntary environmental program (VEP) called SolSmart that targets local governments to engage in solar-friendly practices to promote the local solar PV market in the United States. Via specific designation requirements and technical assistance, SolSmart simplifies the process of acting on interest in being solar friendly, has a wide coverage of basic solar-friendly actions with flexible implementation, and motivates completion with multiple levels of designation. We find that a local government’s participation in SolSmart is associated with an increased installed capacity of 18 to 19%/mo or with less statistical significance, an increased number of installations of 17%/mo in its jurisdiction. However, SolSmart has not shown a statistically significant impact on soft cost reductions to date. In evaluating the impact of the SolSmart program, this study improves our understanding of the causation between a VEP that encourages solar-friendly local government practices and multiple solar market outcomes. VEPs may be able to promote shifts toward sustainable development at the local level. Our findings have several implications for the design of VEPs that promote local sustainability.

14 SOLAR ENERGY↗
DOE OSTI2022

Is the Adoption of Electric Vehicles (EVs) and Solar Photovoltaics (PVs) Interdependent or Independent? An Integrated EVs-PVs Modeling Framework

Transportation and residential energy consumption account for more than one-half of the overall energy consumption in the United States. Adoption of electric vehicles (EVs) can play a key role in decarbonizing the transportation sector, while the adoption of renewable energy sources (e.g., solar photovoltaics or PVs) could bring similar benefits to the residential energy sector and in turn support transport electrification. Although the market share for both EVs and PVs continue to grow, both these emerging technologies are deployed rather disjoint without considering the existence of potential similarities among users who own (or aspire to own) EVs and PVs. This might be due to lack of understanding of the behavioral interdependence in consumer preferences towards these technologies. To fill this gap in knowledge, this study utilizes data from the 2018 WholeTraveler Transportation Behavior Study to develop an integrated model system that explores EV and PV adoption behaviors. A structural equations model (SEM) is employed that incorporates direct effects as well as error correlations among the adoption behaviors for EVs and PVs. Model results indicate that the adoption behavior for both these technologies is indeed interconnected and significantly influenced by attitudes, values and personality traits. Findings from this research suggest that incentives (e.g., subsidies) that drive 'bundled' adoption of EVs and PVs could accelerate the adoption of both these sustainable technologies. The results highlights the need to consider transport and building energy efficient technology adoption behavior in a single integrated structure.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2021

Protection of Distribution Circuits with High Penetration of Solar PV: Distance, Learning, and Estimation-Based Methods

The results of DOE Solar Energy Technologies Office project 34233 are presented. The newest version of IEEE Standard 1547 enables photovoltaic inverters to ride through voltage disturbances, improving bulk system reliability, at the expense of removing undervoltage trip as a fast method of de facto fault detection in high PV adoption scenarios. The project explored new methods of fault detection that don't rely on communication systems and could be available quickly, including distance-based schemes, focused directional relays, and two different data-driven schemes. The schemes were evaluated with fast-phasor simulation, electromagnetic transient simulation, and field data collection at partner utilities Chattanooga Electric Power Board and Dominion Energy Virginia. Accomplishments and possible paths forward are summarized.

14 SOLAR ENERGY↗