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At least 199 records · Page 11

Photovoltaic and Cost Analysis for Winston-Salem, North Carolina

This study assesses the feasibility of solar installations at various sites in Winston-Salem, focusing on factors such as solar resource availability, electricity costs, and rooftop area for photovoltaic systems. The analysis begins by estimating daily energy requirements based on annual electricity use, followed by adjusting for seasonal and operational fluctuations. Using regional solar data from the National Solar Radiation Database (NSRDB), we calculate average peak sun hours to determine effective system sizing. A parametric approach using the System Advisor Model (SAM) refines this sizing process, incorporating a safety margin of 1.2 to address demand peaks. Each PV system is designed to fit available rooftop space, and a coverage threshold of 70% is identified as optimal for maximizing cost savings and sustainability. This threshold allows installations to meet substantial energy demands, supporting energy resilience and enhancing economic returns.

14 SOLAR ENERGY↗

Voices from Rural Electric Cooperatives: A Call for a DER Integration Playbook for Rural and Agricultural Income & Savings from Renewable Energy (RAISE)

Rural-serving electric utilities (RSEUs)—including electric cooperatives, municipal systems, and small investor-owned utilities—are essential players in the evolving energy landscape. These community-focused entities are increasingly being asked to consider distributed energy resources (DERs) such as rooftop and ground-mounted solar, wind, battery storage, smart water heaters, and demand response programs (NRECA 2025; Lenhart et al. 2020). Yet the path to DER adoption is far from straightforward in the rural context. This report is based on in-depth interviews with managers of rural electric cooperatives across the United States. These conversations offer a grounded, unvarnished look at how DERs are perceived, what barriers exist, and what conditions might enable integration and adoption. While the utilities interviewed vary in geography, size, and DER experience, several clear and common themes emerged across electric cooperatives such that the report recommends the development of a DER Integration Runbook to help utilities assess readiness, define local use cases, engage stakeholders, pilot projects, and iterate, expanding over time.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Project Planning for Community Resilience: Aquinnah and Chilmark, Massachusetts

This report presents the findings of an energy system planning study for the towns of Aquinnah and Chilmark, MA, on the island of Martha’s Vineyard, conducted under the U.S. Department of Energy ETIPP program. The study used the DER-CAM model to optimize the deployment of PV and battery microgrids to enhance energy resilience against power outages, particularly winter storms. Key findings show that PV is highly cost-effective and delivers net annual savings. However, due to limited rooftop space and low winter solar output, PV and battery storage alone cannot support the full critical load during outages. Solutions incorporating conventional backup generators were found to be more economically viable for achieving 100% critical load support.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

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.↗

Large-Scale Solar Development: A Playbook for Southwest Virginia

his playbook is an introductory guide for local governments to facilitate large-scale solar projects in Southwest Virginia. In a region that has a long history of energy production, solar technologies offer enormous potential for economic development and job growth. Large-scale solar can take many forms, including rooftop or ground-mounted installations at local corporate offices, nonprofit organizations, or schools. It can also encompass utility-scale projects over many acres on former agricultural or timberlands, mined lands, or industrial sites. Regardless of the type of project, solar is a widely popular, cost-competitive energy choice that helps create sustainable and prosperous communities. This playbook is directed to municipal and county governments that have an essential role to play in encouraging large-scale solar projects. The first section provides an overview of state and national trends, including recent state legislation that will impact local oversight of solar development. This is followed by an overview of the solar project approval process from a developer’s perspective. The next section is an overview of the state and local permitting process for solar projects, followed by other development considerations such as local tax revenue options, financing incentives, and considerations for solar on brownfields and previously mined lands. The playbook concludes with a step-by-step guide for local governments to facilitate large-scale solar development.This playbook is part of the Solar Workgroup of Southwest Virginia’s effort to bring solar energy and associated jobs to the region. Over the past few years, the workgroup has met with stakeholder groups and crafted a strategy for local solar energy development. The workgroup has collaborated with cities and counties to bring SolSmart designation to eight counties and cities, implemented group purchase campaigns for commercial solar, and led research efforts.

14 SOLAR ENERGY↗

Rooftop Photovoltaics and Electric Vehicle Co-Adoption: Attitudes, Norms, Diffusion, and Economics

The overall objectives of the project were to (1) Identify personal and social norms, peer effects, demographics and contextual factors (such as household energy expenditures, experience with outages, charging infrastructure availability) that may facilitate or hinder Solar-EV co-adoption; (2) outline strategies for the design of programs and practices that will enable reasoned RPV and EV adoption and their co-adoption; and (3) assemble a dataset comprised of survey responses of RPV-EV co-adopters, RPV-only adopters, EV-only adopters, and non-adopters. These objectives were only partially fulfilled given the decision to terminate the project. The research team was able to complete the semi-structured interviews, the core BY1 task and summarize the results below. As well, once the team learned of the research project’s fate, it sought and obtained the DOE SETO Technical Manager’s approval to repurpose funds for BY2 tasks to the extent feasible. Rather than invest further resources in expanding the pool of potential survey respondents and having no budget to survey, the research team repurposed funds subject and undertook a more limited (geographically) survey, but also expanded to it to include contingent valuation questions. The analysis of the survey data will necessarily be delayed given the lack of budget support, although some information on the respondent sample is in the results. Given a lack of attention to co-adoption previously, the insights generated in this project should assist decision-makers and industry actors in the development of programs and practices that enable reasoned RPV adoption and EV adoption and their co-adoption.

14 SOLAR ENERGY↗

Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications: Fourth Edition

As the world increasingly seeks low-carbon energy solutions, solar power emerges as the most abundant resource on our planet. However, the challenge of effectively harnessing this energy is crucial in the coming years. Solar energy applications such as photovoltaics, solar heating and cooling, and concentrating solar power use different technologies to capitalize on sunlight. Each system has unique capabilities and requirements, underscoring the need for reliable information about solar resources across diverse installations, from residential rooftops to large-scale power plants. This is especially important for substantial projects, often exceeding $1 billion in construction costs. Before embarking on such ventures, it is imperative to obtain accurate data concerning solar resource quality and reliability at specific sites. Developers require detailed historical information, including seasonal, daily, hourly, and, ideally, subhourly variability to effectively predict a power plant's annual performance. Without these vital data, financial analyses fall short. Moreover, with the growing adoption of distributed photovoltaics, integrating these generation sources becomes critical to maintaining grid reliability and stability. By accurately forecasting generation patterns, utilities and system operators can facilitate greater integration of solar energy, thus ensuring the operational stability of the grid. The complexity and importance of these issues have prompted the foremost experts in the field to collaborate under the auspices of the International Energy Agency's (IEA's) Photovoltaic Power Systems Programme (PVPS) Task 16 to publish this handbook, which summarizes state-of-the-art information about all these topics. The efforts focus on providing reliable data and insights that can help shape our investments in solar energy and drive a sustainable future.

14 SOLAR ENERGY↗

Color-neutral, semitransparent organic photovoltaics for power window applications

Semitransparent organic photovoltaic cells (ST-OPVs) are emerging as a solution for solar energy harvesting on building facades, rooftops, and windows. However, the trade-off between power-conversion efficiency (PCE) and the average photopic transmission (APT) in color-neutral devices limits their utility as attractive, power-generating windows. A color-neutral ST-OPV is demonstrated by using a transparent indium tin oxide (ITO) anode along with a narrow energy gap nonfullerene acceptor near-infrared (NIR) absorbing cell and outcoupling (OC) coatings on the exit surface. The device exhibits PCE = 8.1 ± 0.3% and APT = 43.3 ± 1.2% that combine to achieve a light-utilization efficiency of LUE = 3.5 ± 0.1%. Commission Internationale d’eclairage chromaticity coordinates of (0.38, 0.39), a color-rendering index of 86, and a correlated color temperature of 4,143 K are obtained for simulated AM1.5 illumination transmitted through the cell. Using an ultrathin metal anode in place of ITO, we demonstrate a slightly green-tinted ST-OPV with PCE = 10.8 ± 0.5% and APT = 45.7 ± 2.1% yielding LUE = 5.0 ± 0.3% These results indicate that ST-OPVs can combine both efficiency and color neutrality in a single device.

14 SOLAR ENERGY↗

Community Solar and Community Solar+Storage: A Roadmap of Barriers and Solutions for Commercial Systems in NYC

Sustainable CUNY worked with decision makers and subject matter experts (SME's) to identify the barriers to and solutions for advancing commercial Community Solar (CS) and CS+Storage (CS+S) in urban areas. This roadmap captures the key challenges and solutions identified by New York City (NYC) stakeholders, including the Real Estate Board of New York (REBNY), through a collaborative process. Solar, as well as storage, are among the fastest growing energy segments in the United States, with CS, also known as Community Distributed Generation (CDG), gaining popularity with those who may not own or have access to a viable roof. Urban areas like NYC, which have a large population of renters, are particularly well suited for CS projects where credits from the power produced by a large remote installation are offered on a subscription basis to residents or businesses in the community. However, CS and CS+S projects have stalled at the doorstep of many cities. Host site owners, particularly those with large rooftops, have been slow to commit to installing CS due to competing rooftop usage and programs, limited knowledge about incentives, lack of economic data, and a complicated implementation process.

14 SOLAR ENERGY↗

Tribal Renewable Energy: Bishop Paiute Tribe Youth Solar Job Training Development (Final Report)

This Project provided workshops and hands on opportunities for young tribal adults to gain education,training,and employment in the solar industry; including 1 youth to meet the eligibility requirements for the NABCEP Solar Installer Exam. 10 tribal youth, ages 16-24, attended workshops focused on learning solar fundamentals and then applied those learned skills to hands on training, installing solar on 2 tribal homes. GRID provided certificates authenticating their volunteer hours and skills learned. This program of youth training really excited the tribal leadership as well as the tribal youth. This opportunity was in alignment with the tribe’s Strategic Energy Plan, and supported tribal self-sufficiency, a path to economic development and for the youth it also represented the environmental stewardship the tribe believes in.

14 SOLAR ENERGY↗

Hardware Specification and Reference Design for the Low-Cost, Interoperable, User-Centric, Supervisory Controller Kit for Small and Medium Size Commercial Buildings

Commercial buildings are responsible for approximately 20 percent of the total United States energy consumption and greenhouse gas emissions. Over 85 percent of these buildings lack building automation systems to manage the various building systems they have. Many of these buildings are small (< 50,000 square feet), underserved, and use rooftop units (RTUs) for heating, ventilation, and air-conditioning needs. Because these buildings lack proper control systems, they have several operational deficiencies that lead to excess energy consumption. Studies have shown that managing the RTU’s heating and cooling setpoints, schedules, setbacks, and optimal start times can result in 20 to 25 percent reduction in electricity consumption in small and medium commercial buildings (SMBs). In addition, improving the demand flexibility of these buildings will result in additional cost savings for the building owner. To address the needs of the SMBs, the Department of Energy’s Building Technologies Office jointly funded Pacific Northwest National Laboratory (PNNL) and Oak Ridge National Laboratory (ORNL) to design, develop, test, and validate a low-cost, interoperable, user-centric, retrofit supervisory controller kit (SC-SMB) that can be used to continuously optimize energy consumption and deliver demand flexibility of SMBs, including all-electric buildings, and provide a means for maximizing decarbonization benefits. The team also includes industry partners Edo and Intellimation. Previously, the team drafted an SC-SMB system specification document (Goodman et al. 2023). This document describes a reference design of a low-cost supervisory control system for SMBs, including the various hardware components, software system, and an example implementation of the reference design. The final release of the reference design is planned for December 2025. Section 2.0 of the report documents the relevant building types that the SC-SMB system is suitable for. Section 3.0 documents the various hardware components, their function, cost, whether they are off-the-shelve, support standard communication, etc., and the software system. An example deployment in a 10,000-sf building with six rooftop units, a hot water heater, solar, and storage is described in Section 4.0. The planned next steps are described in Section 5.0, and references are listed in Section 6.0.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

PV Rooftop Database for Puerto Rico (PVRDB-PR)

The National Renewable Energy Laboratory's (NREL) PV Rooftop Database for Puerto Rico (PVRDB-PR) is a lidar-derived, geospatially-resolved dataset of suitable roof surfaces and their PV technical potential for virtually all buildings in Puerto Rico. The dataset can be downloaded at the AWS S3 explorer page. The GitHub documentation page provides a description of the dataset with methods and assumptions. The Puerto Rico Solar-For-All dataset provides Census Tract level estimates of residential low-to-moderate income (LMI) PV rooftop technical potential as well as solar electric bill savings potential for LMI communities at the municipality level.

Array↗

Performance of solar leasing for low- and middle-income customers in Connecticut

Policymakers are increasingly interested in expanding access to rooftop photovoltaic systems. This study analyzes the financial performance of a Connecticut Green Bank (CGB) solar leasing program, run in partnership with PosiGen, that targets low- and moderate-income customers. We show that this program has successfully reached underserved customers and has reasonable repayment rates given the credit characteristics of the participants. The CGB/PosiGen program reaches many more underserved customers than other PV financing programs in Connecticut.For example, the majority of CGB/PosiGen participants (58%) live in census tracts that have a median income of less than 80% of the area median income (AMI). In contrast, only 9% of participants in the other CGB solar financing programs live in these census tracts. Furthermore, the majority of CGB/PosiGen participants (56%) have FICO scores that would generally be considered non-prime (<670), whereas only 2% of participants in the other programs have similarly low scores. Credit, not income, is the primary factor that explains participants’ financial performance. Overall, we find that delinquency and annualized losses are higher for PosiGen (2.3% and 0.9%) than for other CGB programs (1.4% and 0.1%). Across the CGB programs, lower credit scores are associated with higher rates of delinquency and loss. Therefore, participants’ lower credit scores explain much of the program’s higher rates of delinquency and annualized losses. PosiGen leases perform competitively with market-rate solar and non-solar leases and loans. When compared to securities backed by market-rate PV loans and leases with similar amounts of seasoning, we find that the PosiGen leases have higher delinquency rates but comparable gross loss rates. The similarity in losses is notable given that loss rates for PosiGen leases were higher than those of the other CGB leases and loans. Rather than the PosiGen leases having high loss rates, other CGB leases and loans have unusually low loss rates. We also compare PosiGen to non-solar benchmarks, including indices of auto and consumer loans. We find that the PosiGen leases have significantly less delinquency than non-prime auto loans and have performance comparable to many consumer loans. The U.S. Department of Energy’s Solar Energy Technologies Office supported this research.

14 SOLAR ENERGY↗

Panel-Segmentation: A Python Package for Automated Solar Array Metadata Extraction Using Satellite Imagery

The NREL Python Panel-Segmentation package is a toolkit that automates the process of extracting accurate and valuable metadata related to solar array installations, using publicly available Google Maps satellite imagery. Previously published work includes automated azimuth estimation for individual solar installations in satellite images. Our continued research focuses on automated detection and classification of solar installation mounting configuration (tracking or fixed-tilt; rooftop, ground, or carport). Specifically, a Faster-RCNN Resnet-50 feature pyramid network (FPN) model was trained and validated on 862 manually labeled satellite images. This model was used to perform object detection on satellite imagery, locating and classifying individual solar installations' mounting configuration and type. Model results showed a mean average precision score (mAP) of 77.79%, with the model strongest at detecting fixed-tilt ground mount and fixed-tilt carport installations. The object detection model and its outputs have been incorporated into the Panel-Segmentation package's automated metadata extraction pipeline, which returns the mounting configuration and azimuth for individual solar arrays in satellite imagery. The complete image data set with labels has been released on the U.S. Department of Energy (DOE) DuraMAT DataHub, to encourage further research in this area.

deep learning↗

A New Look For Greenbelt

Greenbelt, Maryland, 12 miles from the nation's capital, is an efficiently planned model town and most of its 1600 homes are almost identical in appearance. Four of them, however, stand out from their neighbors; they have distinctive blue glass rooftop superstructures made up of a series of solar collectors. They are part of a NASA community aid program, a joint energy research project involving the Greenbelt housing cooperative and NASA's Goddard Space Flight Center, located near the community. Built in 1935, Greenbelt is one of three government-planned communities of President Franklin D. Roosevelt's first administration; the others are Greendale, Wisconsin and Greenhills, Ohio. The government built the towns to make available low-cost housing, provide employment for workers on relief in the Great Depression era, and to establish models designed to encourage construction of similar developments by private industry. In 1952, the residents of Greenbelt formed a nonprofit cooperative called Greenbelt Homes, Inc., which bought the dwellings, facilities and a large part of the land from the government. The homes are individually owned but collectively maintained by the co-op, with each owner paying a prorated share of utility and maintenance costs. Greenbelt residents are mostly in the low and medium income brackets, and one of every three families lives on a fixed retirement income. For that reason, the sharp escalation of fuel oil prices that began in 1973 imposed particular hardship on the co-op community. So Greenbelt Homes' management asked its NASA neighbor, Goddard Space Flight Center, for assistance in setting up a solar energy research project. The idea was to conduct a small scale demonstration to show what savings could be realized by solar heating Greenbelt homes, with an eye toward possible future expansion of solar energy systems as a means of combating rising fuel costs. Goddard undertook the project as part of the federal government's effort to research and demonstrate ways of conserving energy. The Center was well qualified for the assignment, having acquired extensive expertise in designing thermal control systems for satellites, which must maintain stable temperatures for successful operation.

Source record↗

Technical Potential and Meaningful Benefits of Community Solar in the United States

The report describes the methodology and results from a study on the technical potential of community solar and associated meaningful benefits. A key finding of the study suggests that the opportunity space for community solar to meet unmet demand for solar energy is not primarily constrained by technical potential, but by technological, market, and policy factors. NREL used rooftop and ground-mount photovoltaic siting data to model annual energy production from community solar based on various constraints and system performance. Given modeled results and community solar deployment, we discuss potential benefits including household savings, low-to-moderate income household access to solar, resilience and grid benefits, community ownership, workforce development and entrepreneurship as well as insights into community solar siting opportunities.

14 SOLAR ENERGY↗

Achieving Scale: Community Solar Technical Potential and Meaningful Benefits in the United States

The slide deck was presented at the webinar on February 28th titled Achieving Scale: Community Technical Potential and Meaningful Benefits in the United States. It describes the National Community Solar Partnership program followed by methodology and results from a study on the technical potential of community solar and associated meaningful benefits. A key finding of the study suggests that the opportunity space for community solar to meet unmet demand for solar energy is not primarily constrained by technical potential, but by technological, market, and policy factors. NREL used rooftop and ground-mount photovoltaic siting data to model annual energy production from community solar based on various constraints and system performance. Given modeled results and community solar deployment, we discuss potential benefits including household savings, low-to-moderate income household access to solar, resilience and grid benefits, community ownership, workforce development and entrepreneurship as well as insights into community solar siting opportunities.

community solar↗

Panel-Segmentation [SWR-21-18]

Panel-Segmentation contains the scripts for automated metadata extraction of solar PV installations, using satellite imagery coupled with computer vision techniques. In this package, the user can perform the following actions: *Automatically generate a satellite image using a set of lat-long coordinates, and a Google Maps API key. Users would need to set up a Google Cloud account and get a Maps Static API key. Please refer to Setting Up Google Maps Static API Key section for this process. *Perform image segmentation on the satellite image, to locate the solar array(s) in the image on a pixel-by-pixel basis, using an image segmentation model (panel_detection_model.pth). Get classification of the installation (rooftop, ground mounted fixed-tilt or tracking, carport, etc). *Perform azimuth estimation on each solar array cluster in the masked image. *Detect solar panels and get its latitude, longitude, and address within a geographic bounding box through the SOL-Searcher Pipeline. *Detect and calculate hurricane damage on solar installations given pre-hurricane and post-hurricane satellite imagery through the Hurricane Detection Pipeline. *Detect and calculate hail damage on solar installations given satellite imagery through the Hail Detection pipeline. *Convert NOAA MESH (Maximum Estimated Size of Hail) grib2 files into kml or geojson files. *Estimate tilt and azimuth of a solar array by processing USGS LiDAR data for the array’s location.

Edun, Ayobami↗