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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Spatiotemporal Downscaling Model for Solar Irradiance Forecast Using Nearest-Neighbor Random Forest and Gaussian Process

Accurate solar photovoltaic (PV) capacity estimation requires high-resolution, site-specific solar irradiance data to account for localized variability. However, global datasets, such as the National Solar Radiation Database (NSRDB), provide regional averages that fail to capture the fine-scale fluctuations critical for large-scale grid integration. This limitation is particularly relevant in the context of increasing distributed energy resources (DERs) penetration, such as rooftop PV. Additionally, it is critical to the implementation of the U.S. Federal Energy Regulatory Commission (FERC) Order 2222, which facilitates DER participation in U.S. bulk power markets. To address this challenge, this study evaluates Nearest-Neighbor Random Forest (NNRF) and Nearest-Neighbor Gaussian Process (NNGP) models for spatiotemporal downscaling of global solar irradiance data. By leveraging historical irradiance and meteorological data, these models incorporate spatial, temporal, and feature-based correlations to enhance local irradiance predictions. The NNRF model, a machine-learning approach, prioritizes computational efficiency and predictive accuracy, while the NNGP model offers a level of interpretability and prediction uncertainty by numerically quantifying correlations and dependencies in the data. Model validation was conducted using day-ahead predictions. The results showed that the average Goodness of Fit (GoF) of the NNRF model of 90.61% across all eight sites outperformed the GoF of the NNGP of 85.88%. Additionally, the computational speed of NNRF was 2.5 times faster than the NNGP. Finally, the NNGP displayed polynomial scaling while the NNRF scaled linearly with increasing number of nearest neighbors. Additional validation of the model on five sites in Puerto Rico further confirmed the superiority of the NNRF model over the NNGP model. These findings highlight the robustness and computational efficiency of NNRF for large-scale solar irradiance downscaling, making it a strong candidate for improving PV capacity estimation and real-time electricity market integration for DERs.

Asiedu, Shadrack (ORCID:0009000646004826)↗
DOE OSTI2020

The impact of policies and business models on income equity in rooftop solar adoption

Low- and moderate-income (LMI) households are less likely to adopt rooftop solar photovoltaics (PVs) than higher-income households in the United States. As the existing literature has shown, this dynamic can decelerate rooftop PV deployment and has potential energy justice implications, in light of the cost-shifting between PV and non-PV households that can occur under typical rate structures and incentive programmes. Here we show that some state policy interventions and business models have expanded PV adoption among LMI households. Additionally, we find evidence that LMI-specific financial incentives, PV leasing and property-assessed financing have increased the diffusion of PV adoption among LMI households in existing markets and have driven more installations into previously underserved low-income communities. By shifting deployment patterns, we posit that these interventions could catalyse peer effects to increase PV adoption in low-income communities even among households that do not directly benefit from the interventions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Editorial for Special Issue: Grid-Interactive Efficient Buildings—Part 2

This issue of the ASME Journal of Engineering for Sustainable Buildings and Cities (JESBC) is fully dedicated to peer-reviewed papers specific to technologies and applications of Grid-interactive Efficient Buildings (GEBs). As defined by a series of publications by the U.S. Department of Energy (DOE) and outlined in Part 1 of the editorial of JESBC August 2020 issue, GEBs are efficient, connected, smart, and flexible buildings. This GEB special issue covers some technologies and applications for grid-connected buildings and communities. Some of technologies included in the special issue are dynamic insulation systems for building envelopes, building integrated fuel cells, and rooftop PV systems. Furthermore, the issue outlines the designs and cost-benefits of net-zero energy (NZE) buildings and carbon neutral communities in the United States.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

CityBES v2021

City Buildings, Energy, and Sustainability (CityBES) is a web-based data and computing platform, focusing on energy modeling and analysis of a city's building stock to support district or city-scale building energy efficiency programs. CityBES uses an international open data standard, CityGML, to represent and exchange 3D city models. CityBES employs EnergyPlus to simulate building energy use and savings from energy efficient retrofits. Other CityBES features include energy benchmarking, district heating and cooling system modeling, rooftop PV analysis, building performance visualization, heat resilience modeling, as well as urban scale mapping of microclimate and heat vulnerability at census tract level. Different from other tools, CityBES uses integrated open and standard 3D city building data and models each individual building using EnergyPlus. CityBES can be used by urban planners, city energy managers, building owners, utilities, energy consultants and researchers.

Hong, Tianzhen↗
DOE OSTI2025

Prioritizing urban heat adaptation infrastructure based on multiple outcomes: Comfort, health, and energy

Globally, cities face increasing extreme heat, impacting comfort, health, and energy consumption. Infrastructure-based heat adaptation strategies can improve these outcomes, but each strategy has a unique mix of benefits and drawbacks. Here, we apply an urbanized meteorological model (WRF) with the newly integrated multilayer BEP-Tree street tree model to dynamically downscale Earth System Model projections and a 3-D microclimate model (TUF-Pedestrian) to simulate the street-scale radiation environment impacting pedestrians. We evaluate the performance of five heat adaptation strategies (street trees, cool roofs, green roofs, rooftop photovoltaics (PV), and reflective pavements) during extreme heat events in three cities with contrasting background climates (Toronto, Phoenix, and Miami), under contemporary and end-of-century projected climates, based on three metrics: outdoor heat stress, air conditioning (AC) energy use, and ventilation of vehicular air pollution. No single adaptation strategy improves all three outcomes. While street trees inhibit ventilation, they reduce outdoor heat stress four times more effectively than the next best strategy via shade provision, fully offsetting heat stress increases under a high-emissions end-of-century climate scenario in all cities studied. Cool roofs and green roofs moderately reduce heat stress and energy use. Alternatively, rooftop PV with energy storage can generate sufficient power for space cooling but have marginal effects on heat stress. Reflective pavements are the least effective across metrics. Where the ventilation of street-level emissions is of less concern, our results clearly support the combination of street trees and rooftop PV as a highly complementary and effective means of adaptive mitigation across different climates and neighborhood densities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Observations and Lessons Learned in Residential Roofing Integrated Photovoltaics

The data file includes field observations of residential roofing integrated photovoltaics installation that happened between July 2021 and June 2022 in California. There are 21 observations - 2 in the re-roofing category and 19 in the new construction category. The file includes two time and motion forms (Re-Roofing & New Construction) we used to capture the time it takes for each activity in the rooftop solar and electrical installation process. You will see the duration for detailed steps along with activities that are included for total installation time for the paper. There are three parts to the time and motion form - Part 1 has project and crew characteristics, product information, and inspection and permitting data and can be filled before the installation. Part 2 has the actual installation time stamps and related notes. Part 3 has the crew information and can be filled on-site or off-site, but this section is optional. The re-roofing form has pre-solar activities and gutters and vents section in Part 2 of the form, whereas new construction form includes a section for capturing the time it took for rough wiring. The re-roofing form does not include rough wiring but instead includes the final electrical wiring process. These are the key differences in both the forms. Each day/step/installation activity needs to include the crew break time as they happen and there is space available to capture the crew breaks duration. In Table 1 below, the different terms used in the time and motion form are defined and their corresponding unit of measurement stated. We also highlight the optional sections. The data is captured in total mins, total hours, person mins, person hours. You can use this form or make edits to the form to recreate the study or make your own observations. The data herein was reviewed but may not be comprehensive. NREL invites questions and inputs to improve the data, including to: Correct erroneous information Fill in missing/updated information Clarifications on data and variables Updated information may be submitted to Sushmita Jena at sushmita.jena@nlr.gov.

14 SOLAR ENERGY↗
DOE OSTI2024

Sicangu Village Solar Project

The Sicangu Village Solar Project, spearheaded by the Rosebud Sioux Tribe in partnership with GRID Alternatives, aimed to enhance energy sustainability within the community through the installation of a 149 kW community solar Photovoltaic (PV) array and 13 residential rooftop solar PV systems. Located in Todd County, South Dakota, the project addresses longstanding challenges of rising electricity costs and economic disparities faced by the Tribe. By leveraging solar energy production, the project not only reduces electricity expenses for the community, but also serves as a pivotal step towards achieving the Tribe's energy sovereignty goals. Despite encountering interconnection challenges and delays, particularly exacerbated by regulatory and infrastructure complexities, the project has successfully demonstrated the feasibility of solar energy deployment within the community.

14 SOLAR ENERGY↗
DOE OSTI2021

U.S. Solar Photovoltaic System and Energy Storage Cost Benchmark: Q1 2021 [Slides]

Our benchmarking method includes bottom-up accounting for all necessary system and projectdevelopment costs incurred when installing residential, commercial, and utility-scale systems, and it models the Q1 2021 costs for such systems, excluding any previous supply agreements or contracts. In general, we attempt to model the typical installation techniques and business operations from an installed-cost perspective, and our benchmarks are national averages. The residential PV-only benchmark and the commercial rooftop PV-only benchmark average costs by inverter type (string inverters, string inverters with direct current [DC] optimizers, and microinverters), weighted by inverter market share. The residential PV-only benchmark is further averaged across small installer and national integrator business models, weighted by market share. All benchmarks include variations—accounting for the differences in size, equipment, and operational use (particularly for storage)—that are currently available in the marketplace. All benchmarks assume nonunionized construction labor; residential and commercial PV systems predominantly use nonunionized labor, and the type of labor required for utility-scale PV systems depends heavily on the development process. All benchmarks assume the use of monofacial monocrystalline silicon PV modules. Benchmarks using cadmium telluride or bifacial modules could result in significantly different results. The data in this annual benchmark report inform the formulation of and track progress toward the U.S. Department of Energy (DOE) Solar Energy Technologies Office’s Government Performance and Reporting Act cost targets.

14 SOLAR ENERGY↗
DOE OSTI2024

Pueblo of Laguna Village Community Solar

The project was to install approximately 11.44 kilowatts (kW) rooftop solar photovoltaic (PV) system on the Mesita Village Community Center, an approximately 9.24 kW rooftop solar PV system on the Paguate Village Community Center, an approximately 21.56 kW rooftop solar PV system on the Paraje Village Community Center, and an approximately 11.00 kW rooftop solar PV system on the Seama Community Center, for a total of about 53.24 kW on four village community centers. The systems were expected to generate approximately 93,329 kWh annually. Installing solar PV systems on the four village community centers would have helped achieve the Pueblo of Laguna’s six energy objectives: community development (decreased utility bills, funds for other needs), economic development (training and participation in the renewable energy economy), energy reliability (future storage), community resilience (alternative sources), relationship to people and the natural world (reducing fossil fuel use), and energy sovereignty (Pueblo decision-making). Installing solar PV systems would have also met specific project goals to offset not less than 85% of each selected building’s annual electricity use, ranging from 87% to 103% of demand; save a minimum of 70% of the cost of utility bills per year for each building, ranging from 75% to 77% percent (including service charges); and would have had payback periods shorter than the estimated useful life of the project

14 SOLAR ENERGY↗
DOE OSTI2022

Case Study: WashREIT's Multifamily Solar PV

This case study describes the installation process and resulting payback of rooftop solar PV systems on two multifamily apartment buildings in Washington, D.C. owned by WashREIT.

solar, solar PV, photovoltaic, onsite solar, multi↗
DOE OSTI2022

SolarAPP+ Performance Review: 2021 Data

Accelerating rooftop solar photovoltaic (PV) deployment has strained the capacity of local authorities responsible for permitting, inspection, and interconnection (PII). Given the ongoing expansion of rooftop PV, a growing number of authorities having jurisdiction (AHJs) and utilities are reforming PII processes to reduce delays. AHJs could significantly reduce PII timelines through reforms such as expedited reviews for small-scale systems, online customer portals, and over-the-counter permitting. However, independent reforms do not resolve issues associated with PII variability across AHJs, and many AHJs lack the resources to implement reforms. In response to these challenges, the National Renewable Energy Laboratory (NREL) developed the Solar Automated Permit Processing Plus (SolarAPP+) platform, in collaboration with local governments, code development organizations, and industry stakeholders. This report shows SolarAPP+ performance in 2021 across AHJs.

14 SOLAR ENERGY↗
DOE OSTI2021

Disaggregating Customer-Level Behind-the-Meter PV Generation Using Smart Meter Data and Solar Exemplars

Customer-level rooftop photovoltaic (PV) has been widely integrated into distribution systems. In most cases, PVs are installed behind-the-meter (BTM), and only the net demand is recorded. Therefore, the native demand and PV generation are unknown to utilities. Separating native demand and solar generation from net demand is critical for improving grid-edge observability. In this paper, a novel approach is proposed for disaggregating customer-level BTM PV generation using low-resolution but widely available hourly smart meter data. The proposed approach exploits the strong correlation between monthly nocturnal and diurnal native demands and the high similarity among PV generation profiles. First, a joint probability density function (PDF) of monthly nocturnal and diurnal native demands is constructed for customers without PVs, using Gaussian mixture modeling (GMM). Deviation from the constructed PDF is utilized to probabilistically assess the monthly solar generation of customers with PVs. Then, to identify hourly BTM solar generation for these customers, their estimated monthly solar generation is decomposed into an hourly timescale; to do this, we have proposed a maximum likelihood estimation (MLE)-based technique that utilizes hourly typical solar exemplars. Leveraging the strong monthly native demand correlation and high PV generation similarity enhances our approach's robustness against the volatility of customers’ hourly load and enables highly-accurate disaggregation. Furthermore, the proposed approach has been verified using real native demand and PV generation data.

14 SOLAR ENERGY↗
DOE OSTI2025

ComStock Measure Documentation: Thermostat and Lighting Control for Load Shedding + Photovoltaics With 40% Rooftop Coverage

This report describes the modeling methodology for an upgrade package of two end-use savings shape measures - Thermostat Control for Load Shedding and Lighting Control for Load Shedding - and briefly introduces key results. The package combines thermostat control for load shedding, lighting control for load shedding, and PV with 40% rooftop coverage measures to reduce the net building load during the building's electricity peak window every weekday. The measure takes daily peak load schedule inputs generated by the method "Dispatch Schedule Generation" described in the "Supplemental Documentation: Dispatch Schedule Generation for Demand Flexibility Measures" to determine the start and end times of the predicted peak window, and then relaxes the thermostat setpoints and dims the lighting level from the original schedules during the peak window to reduce the peak demand, while applying the fixed rooftop PV application for onsite electricity generation. The measure is applicable to (large, medium and small) offices, warehouses, and primary and secondary schools, which correspond to approximately 68% of the stock floor area of commercial buildings in ComStock analysis. The measure demonstrates 5%-15% daily peak demand reduction performance for applicable buildings, and around 1% total site energy savings (0 trillion British thermal units [TBtu]) for the U.S. commercial building stock modeled in ComStock.

14 SOLAR ENERGY↗
NASA NTRS2010

Effects of Solar Photovoltaic Panels on Roof Heat Transfer

Building Heating, Ventilation and Air Conditioning (HVAC) is a major contributor to urban energy use. In single story buildings with large surface area such as warehouses most of the heat enters through the roof. A rooftop modification that has not been examined experimentally is solar photovoltaic (PV) arrays. In California alone, several GW in residential and commercial rooftop PV are approved or in the planning stages. With the PV solar conversion efficiency ranging from 5-20% and a typical installed PV solar reflectance of 16-27%, 53-79% of the solar energy heats the panel. Most of this heat is then either transferred to the atmosphere or the building underneath. Consequently solar PV has indirect effects on roof heat transfer. The effect of rooftop PV systems on the building roof and indoor energy balance as well as their economic impacts on building HVAC costs have not been investigated. Roof calculator models currently do not account for rooftop modifications such as PV arrays. In this study, we report extensive measurements of a building containing a flush mount and a tilted solar PV array as well as exposed reference roof. Exterior air and surface temperature, wind speed, and solar radiation were measured and thermal infrared (TIR) images of the interior ceiling were taken. We found that in daytime the ceiling surface temperature under the PV arrays was significantly cooler than under the exposed roof. The maximum difference of 2.5 C was observed at around 1800h, close to typical time of peak energy demand. Conversely at night, the ceiling temperature under the PV arrays was warmer, especially for the array mounted flat onto the roof. A one dimensional conductive heat flux model was used to calculate the temperature profile through the roof. The heat flux into the bottom layer was used as an estimate of the heat flux into the building. The mean daytime heat flux (1200-2000 PST) under the exposed roof in the model was 14.0 Watts per square meter larger than under the tilted PV array. The maximum downward heat flux was 18.7 Watts per square meters for the exposed roof and 7.0 Watts per square meters under the tilted PV array, a 63% reduction due to the PV array. This study is unique as the impact of tilted and flush PV arrays could be compared against a typical exposed roof at the same roof for a commercial uninhabited building with exposed ceiling and consisting only of the building envelope. Our results indicate a more comfortable indoor environment in PV covered buildings without HVAC both in hotter and cooler seasons.

Dominguez, A.↗
DOE OSTI2022

Passive and active peer effects in the spatial diffusion of residential solar panels: A case study of the Las Vegas Valley

This research analyzes the role of peer influences on the adoption of residential rooftop solar photovoltaic panels (PV) within the context of the Diffusion of Innovation Theory. PV literature indicates that adopters are influenced by word of mouth (WOM) information exchange with peers, i.e., active peer effects, while other studies suggest that living near households with visible rooftop PV installations influences adoption, i.e., passive peer effects. We bridge the gap in this literature by conducting a mixed methods analysis. We develop and administer a survey to Las Vegas Valley (LVV) residents to identify current and potential PV adopters' perceptions of peer-effects and consumer intention variables. We conduct a spatial analysis of Google's Project Sunroof data to identify LVV neighborhoods in the later stages of the PV diffusion process, i.e., those with the highest PV adoption rates. Key results show that current PV adopters living in early diffusion areas report significantly higher active and passive peer effects compared to adopters in later diffusion areas. Potential adopters in later diffusion areas report higher passive peer effects than those in early diffusion areas. Overall, because LVV has a low PV adoption rate (<3%), short term strategies aimed at increasing PV adoption should emphasize WOM active peer effects. Here, we caution against long-term green marketing strategies focusing solely on peer-effects as the PV market matures.

14 SOLAR ENERGY↗
DOE OSTI2023

Characterizing Current THD’s Dependency on Solar Irradiance and Supraharmonics Profiling for a Grid-Tied Photovoltaic Power Plant

The rapidly increasing distributed energy resources (DERs) in power systems are now getting interconnected to set community grid structures, where power quality will be a major concern. The grid-to-grid (G2G) bidirectional power transfer among the distribution microgrid will not be considered commercially feasible unless the upstream harmonics are under the limits. The aggregation of such harmonics, measured as total harmonic distortion (THD), is feared to be beyond tolerable limits with the progression of rooftop grid-tied PV-like installations. Hence, this THD needs to be characterized with DER generation end variables. In this work, the photovoltaic (PV) DERs’ dependency on environment variables such as irradiance was profiled in the context of generating and injecting harmonics into the grid. A mathematical model of a grid-tied three-phase PV DER was developed as part of this correlation characterization, matching the fundamental unit structure of a 1.4 MW solar canopy located on the Florida International University (FIU) Miami campus. To determine the qualitative association with produced THD patterns, the model was evaluated with various irradiance settings. A real-time digital simulation (RTDS) platform was used to verify it. Following this confirmation, sets of data from power quality meters at the point of common coupling and FIU field sensors were utilized to validate further the correlation model. The results showed that the grid current’s THD exhibited a high correlation with the irradiance profile and its variation over time. The early morning and late afternoon periods of the day, associated with a low irradiance, constantly had higher harmonics generated from the PV DER. The midday THD was rather rational with partial shadings, hence a geolocation-dependent factor. These findings were verified by an RTDS and validated by real field data. In quantifying the THD injected by a single DER at a high-frequency (2–150 kHz) supraharmonics (SH) level, a 3% peak increment in magnitude was observed from the high-fixed to the low-fixed irradiance profile. The correlation characteristics depicted that the hybrid microgrid suffered from a daytime-dependent harmonic insertion from the grid-tied DER. This is a global problem unless specific measures are taken to mitigate the harmonics. The electrically notorious higher-frequency SH was found to increase proportionally. The G2G power transfer can be limited because of the higher THD in the early morning and late afternoon, which will also worsen because the numbers of grid-tied PV DERs (i.e., rooftop solar and industrial solar) are likely to increase rapidly soon. The community grid structure can thus have a controlled harmonics filtration setup purposefully designed to address the findings of this work, which also fall within the scope of our future research.

14 SOLAR ENERGY↗