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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Optimal Efficiency and Operational Cost Savings: A Framework for Automated Rooftop PV Placement

Residential energy consumers are charged based on a utility rate structure, such as net metering or feed-in tariff. To lower consumers' electricity bills, expensive batteries are deployed to reduce the electricity fed from the grid during peak hours. However, strategic photovoltaic (PV) panel placement enables the reduction of operational energy cost while considering the spatial feasibility and efficiency for hosting rooftop PV. In this paper, we present a framework to automatically identify the optimal location of rooftop PV panels on residential buildings. Our framework integrates multiple workflows, including energy and environmental simulation, parametric modeling, and optimization to identify the ideal location of PV panels to balance the demand and supply at a building and community scale. These workflows are linked using the Grasshopper plug-in for Rhinoceros CAD software. The framework includes two different workflows, each satisfying a target for optimal PV placement: (a) maximizing PV panel efficiency, where users aim to maximize energy generation, and (b) minimizing operational energy cost, where "best'' panels are selected considering utility rates for operational energy cost. Our framework is demonstrated in a residential community in Fort Collins, Colorado, to generate the optimal PV placement for each of the two aforementioned targets. Results from the two workflows are compared to illustrate the effect of PV location and orientation on solar energy production efficiency and operational energy cost. The developed workflows are introduced as tools within the Grasshopper plug-in to investigate the solar potential of rooftop PV panels while taking into account factors such as contextual shading, utility rate structures, and buildings' energy demand profiles.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

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↗
DOE OSTI2020

Puerto Rico Solar-for-All: LMI PV Rooftop Technical Potential and Solar Savings Potential

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. Each dataset is broken out by income group, defined by the Area Median Income (AMI), by tenure, and by building type. The underlying LiDAR data used the estimation were collected in 2015-2017 and the American Community Survey (ACS) data are from 2011-2015. This Puerto Rico Solar-For-All dataset is intended to extend the SEEDSII Solar-For-All estimates for the US 50-states ( https://www.nlr.gov/docs/fy18osti/70901.pdf ) for the territory of Puerto Rico using updated methods. Please see the data documentation for details.

14 SOLAR ENERGY↗
DOE OSTI2022

Intersections of Disadvantaged Communities and Renewable Energy Potential: Data Set and Analysis to Inform Equitable Investment Prioritization in the United States

Renewable energy development can bolster local economies through job creation, local tax revenues, and reduced energy costs; however, communities most in need of economic development and employment opportunities often see lower levels of renewable energy deployment. We sought to identify areas where disadvantaged community indicators and high generation potential from cost-effective renewable energy opportunities intersect and deployment could lead to economic development and job creation. This presentation will highlight several of our findings. This research and the associated county-level data set are intended to inform national- and state-level energy-related assistance programs, economic development efforts, and infrastructure programs seeking to prioritize investments in disadvantaged communities.

community energy planning↗
DOE OSTI2020

Patience is a virtue: A data-driven analysis of rooftop solar PV permitting timelines in the United States

© 2020 The Authors Local permitting can ensure the safe installation and operation of rooftop solar photovoltaic (PV) systems. At the same time, burdensome local permitting processes and local variation in requirements may pose challenges to PV deployment. In this article, we explore new data on the durations between key steps in the PV permitting process in the United States. The data suggest that a typical customer can expect to wait around 25–100 days from permit application until an installed system passes inspection. Permit durations vary significantly across jurisdictions, due in part to differences in local permitting policies. However, permit durations vary as significantly within jurisdictions as across them, in part due to significant variation across installers, suggesting that installer strategies and practices play an important role in permitting timelines. Permit durations have declined over time, reflecting progress from permit streamlining policies and jurisdiction learning-by-doing, though durations have stabilized in recent years. The data suggest that typical PV customers still face long and uncertain permitting timelines in the United States.

O'Shaughnessy, E↗
DOE OSTI2023

Observations and Lessons Learned From Installing Residential Roofing-Integrated Photovoltaics

Building-sited solar photovoltaics (PV) could play a key role in decarbonizing the building sector either through racked and mounted PV or through Building-integrated PV (BIPV). BIPV is installed into the building envelope itself, with solar cells and/or modules forming the outer layer of a building structure, thus transforming a single-purpose structure into one that serves the dual purposes of the building envelope and electricity. BIPV can be applied to building roofs, facades, awnings, pergolas, windows, skylights, balustrades, and other external surfaces. Given BIPV products vary widely, the focus of this research is residential roofing integrated PV (RIPV), where solar is incorporated into or otherwise replaces the roofing material. Previous research suggests that residential RIPV could reduce customer acquisition, labor, supply chain, and equipment costs. These products have yet to realize these cost savings and deployment remains significantly less than conventional rooftop PV as a relative share of the addressable market in the US. One potential barrier to broader residential roofing integrated PV deployment may be higher costs relative to conventional rooftop PV, primarily because the design and installation of these products is still evolving. Here, we explore residential RIPV cost-reduction opportunities by analyzing installation processes. Our study documents residential RIPV installations at 2 reroofing sites and the equivalent of 9 new construction sites in California through a methodology known as time and motion study. We also conducted interviews with subject-matter experts to identify barriers and solutions to maximize these products' market penetration. Our time and motion study breaks the RIPV installation process into four steps: 1) staging, unloading, and roof preparation; 2) fire resistant underlayment(s) (synthetic material laid between roof shingles and roof deck); 3) flashings and PV installation; and 4) wiring and monitoring. We measure the time required for each step in terms of worker-hours, representing an hour of labor from a single worker. We further normalize process time by dividing worker-hours by kilowatt (kW) of system capacity. The most time-intensive step was flashings and PV installation, taking around 2.4 worker-hours per kW on average and accounting for around 60% of the process time for an average installation. The total installation process took on average about 6.4 and 3.5 worker-hours per kW at the reroofing sites and new construction sites, respectively. For comparison, a previous time and motion study documented a time of 6.9 worker-hours per kW for conventional rooftop PV. The shorter RIPV installation times are consistent with previous studies suggesting that RIPV could be installed faster than conventional rooftop PV. The time and motion results and feedback from interviewees provide insights into potential residential RIPV cost reduction opportunities. Several interviewees suggested that these products would be more efficient if PV installation was more fully integrated into the roofing/construction industries, which currently use separate supply chains and skillsets. Further integration could reduce supply chain delays and labor force redundancies. Future research could explore specific ways to integrate these industries to help realize the cost savings potential of RIPV.

14 SOLAR ENERGY↗
DOE OSTI2026

Addressing the split incentive challenge for rooftop solar PV and battery energy storage in multifamily rental buildings (CRADA 638 Final Report)

This project advances the understanding of how roof solar PV systems and battery energy storage systems (BESS) can be effectively deployed in multifamily residential buildings, a sector that has historically faced barriers due to misaligned incentives between landlords and tenants. By leveraging high-resolution building stock data and simulation tools, the research demonstrates how energy consumption patterns vary across building types, climates, and occupant characteristics, and how these variations influence the optimal sizing and operation of distributed energy resources. A key contribution is the development of a publicly accessible, web-based tool named RESIDE (Residential Energy Systems & Infrastructure Data Evaluation) that allows users to explore building energy use and evaluate solar and battery configurations without requiring specialized expertise. This significantly lowers the barrier to entry for stakeholders such as property owners, utilities, and policymakers. From a technical perspective, the project shows that integrating rooftop solar PV with battery energy storage can substantially reduce electricity costs and peak demand through strategies such as energy arbitrage and peak shaving. The modeling framework incorporates real-world constraints, including time-of-use electricity pricing and battery degradation, providing realistic and actionable insights. Economically, the results indicate that properly sized systems can deliver meaningful cost savings, improving the feasibility of energy investments in multifamily housing. More broadly, the project benefits the public by supporting the transition to affordable and reliable energy, particularly in rental multifamily housing where adoption has traditionally lagged.

14 SOLAR ENERGY↗
DOE OSTI2022

Rooftop Solar PV Quality and Safety in Developing Countries - Key Issues and Potential Solutions

To scale solar photovoltaic (PV) deployment in developing countries, the technology must be safe and reliable, meeting both customer and utility expectations. However, challenges exist in achieving these goals. Because PV systems are novel and complex, the majority of consumers are unable to distinguish between low- and high-quality systems; many may invest based on price alone. Suboptimal PV system performance and safety incidents can have downstream impacts on the solar industry and customer adoption because of unmet expectations and negative publicity. Rooftop solar system components vary in quality, and inadequate training could lead to poor installation practices. And even if inspection checklists, certification procedures, and standards are available, they may not be widely used in countries if they are not mandatory, the workforce is not aware of them, or installers lack the technical capacity to comply. Despite the numerous solar quality and safety challenges developing countries may face, lessons learned and best practices from around the world can address them.

14 SOLAR ENERGY↗
DOE OSTI2021

Estimating Spatial Distribution Impacts of Rooftops Solar PV on Dynamic Hosting Capacity Evaluation for a Real Distribution Feeder

This paper models the sensitivity of dynamic hosting capacity analysis to the spatial distribution of distributed PV scenarios, random, close and far from substation deployments, at various penetration levels on a real distribution feeder, in a quasi-static time series (QSTS) power flow simulation using high resolution time-aware metrics. These spatial distribution scenarios were chosen to capture a wide range of potential operation impacts of these deployments using a set of thermaland voltage-based metrics such as instantaneous violations and moving averages for both thermal and voltage constraints. This study uses actual load and PV data up-scaled from 1-hour time step to 1-minute resolution to fully characterize the interaction between the daily changes in load and PV output, and their impacts on distribution system operations.

distribution system↗
DOE OSTI2021

U.S. Solar Photovoltaic System and Energy Storage Cost Benchmarks: Q1 2021

Based on our bottom-up modeling, the Q1 2021 PV and energy storage cost benchmarks are: $\$2.65$ per watt DC (WDC) (or $\$3.05$/WAC) for residential PV systems, 1.56/WDC (or $\$1.79$/WAC) for commercial rooftop PV systems, $\$1.64$/WDC (or $\$1.88$/WAC) for commercial ground-mount PV systems, $\$0.83$/WDC (or $\$1.13$/WAC) for fixed-tilt utility-scale PV systems, $\$0.89$/WDC (or $\$1.20$/WAC) for one-axis-tracking utility-scale PV systems, $\$30,326$-$\$33,618$ for a 7.15-kWDC residential PV system with 5 kW/12.5 kWh nameplate of storage, $\$2.04$ - $\$2.10$ million for a 1-MWDC commercial ground-mount PV system colocated with 600 kW/2.4 MWhusable of storage, $\$166$ - $\$167$ million for a 100-MWDC one-axis tracker PV system colocated with 60 MW/240 MWhusable of storage. Between 2020 and 2021, there were 3.3% ($\$0.0$9/W), 10.7% ($\$0.19$/W), and 12.3% ($\$0.13$/W) reductions (in 2020 USD) in the residential, commercial rooftop, and utility-scale (one-axis) PV system cost benchmarks respectively. Balance of system (BOS) costs have either increased or remained flat across sectors, year-on-year, unlike in previous benchmark reports, which generally have reported declining BOS costs. The increase in BOS cost has been offset by a 17% reduction in module cost. Overall, modeled PV installed costs across the three sectors have declined compared to our Q1 2020 system costs.

14 SOLAR ENERGY↗
DOE OSTI2020

Grid Integration of Small-Scale Photovoltaic Systems in Secondary Distribution Network—A Review

The relative share of renewable energy, specifically the solar photovoltaic (PV), is increasing exponentially in the world electric energy sector. This is a cumulative result of reduction in the cost of solar panels, improvement in the panel efficiency, and advancement in the associated power electronics. Among different types of PV plants, installation of small-scale rooftop PV is growing rapidly due to direct end-user benefits and lucrative governmental incentives. There are various standards developed in regards to grid integration of PVs and other distributed generations (DGs). Different power converter topologies are developed to interface the PV panel with the utility grid. To keep up with the stringent regulations imposed by the standards, various control strategies and grid synchronization methods have been developed. This review article amalgamates and summarizes all of the aforementioned aspects of a grid-integrated PV system including various standards, power stage architectures, grid synchronization methods, operation under extreme events, and control methodologies, pertaining to small-scale PV plants. This article will help freshman researchers to gain some familiarity with the topic and introduce them to some of the key issues encountered in this field.

14 SOLAR ENERGY↗
DOE OSTI2024

Automated analysis of unlabeled PV data with Solar Data Tools software: Overview and feature updates

Distributed rooftop PV systems: ubiquitous, yet commonly have unlabeled data Difficult or impossible to form a performance index We developed Solar Data Tools (SDT), an open-source Python library for analyzing PV power (and irradiance) time-series data SDT enables analysis of unlabeled PV data—no model, no meteorological data, no performance index required Takes a statistical signal processing approach Data processing steps are largely pre-defined and automatic regardless of system type—from utility tracking systems to multi-pitch rooftop systems

Meyers-Im, Bennet E↗
DOE OSTI2023

Frequency Response Analysis to Monitor and Identify Changes in the Impedance of a Photovoltaic Panel Measured Online using a Power Optimizer

Photovoltaic (PV) cells are generally modeled as a current source due to photocurrent, p-n junction diodes with parasitic resistance, capacitance, and inductance. This paper proposes online frequency response analysis (FRA) to measure the impedance of a PV panel using an existing panel-level power optimizer in a PV system. The algorithm will actively perturb a small signal into a 300 W rooftop PV panel and compute its small signal impedance. The technology discussed is easy to incorporate, requires no additional hardware, doesn't alter the stability of the system, and is implemented at a steady-state point. The power optimizer initially stabilizes at an operating point and then perturbs the PV current via FRA and computes PV panel impedance. The relative standard deviation test conducted indoors under 300 W/m 2 illumination on a PV panel shows a less than 5% error rate in PV panel impedance magnitude and phase is measured using a power optimizer.

14 SOLAR ENERGY↗
DOE OSTI2023

Next Generation Integrated PV Products Cost and Workflow Analysis (Final Report)

Residential photovoltaic (PV) costs have fallen consistently for over a decade (Ardani et al. 2018). DOE has subsequently developed a new residential PV cost target for 2030 of $0.05/kilowatt hour (SETO 2023). Ardani et al. (2018) conclude that integrated roofing and PV (RIPV) products may be key to achieving the residential target for both new construction and retrofit residential PV. In RIPV, the PV product is incorporated into or replaces the roofing material. RIPV systems can use conventional crystalline or thin-film technologies, may be aesthetically attractive alternatives to traditional racked and mounted PV systems, and may increase building property values (Cook et al. 2023). These products also have the potential to provide customer acquisition, labor, and equipment cost savings over traditional, racked and mounted residential rooftop PV and several companies have recently introduced integrated roofing and PV (RIPV) products (Cook et al. 2023). In 2022, Tesla was the market leader, representing 94% of RIPV capacity installed in 2022 through its Solar Roof offering, while GAF Energy and its Timberline Solar product was second capturing 3% (Feldman et al. 2023). In this project, NREL analyzed three research questions: (1) How do current RIPV products compare to racked and mounted PV in terms of costs, install times and processes? (2) How are RIPV products installed and are there opportunities for cost savings? (3) What are the key barriers to expanding market opportunities for integrating solar and roofing products? In this project, we explored residential RIPV cost reduction opportunities by analyzing installation processes. Our study documented residential RIPV installations at two reroofing sites (20.52 kilowatts) and the equivalent of nine new construction sites (71.75 kW) in California through a methodology known as time and motion study. We also conducted 15 interviews with subject-matter experts to identify barriers and solutions to maximize these products' market penetration.

14 SOLAR ENERGY↗
DOE OSTI2021

A Data-Driven Method for Estimating Behind-the-Meter Photovoltaic Generation in Hawaii

Due to the increasing penetration of distributed behind-the-meter photovoltaic (PV) systems and the installed utility revenue metering limited to monitoring only the net power import/export of the household, it is increasingly challenging for utilities to effectively plan and operate the grid. This paper proposes a methodology that estimates behind-the-meter PV generation using a selected subset of monitored PV systems. It is a data-driven approach, and the PV output is estimated utilizing a statistic regression model. A Minimum Redundancy Maximum Relevance (MRMR) algorithm is applied to preselect the optimal subset of the monitored PV systems. The performance of this approach is compared with a spatial interpolation method and a model-based approach. The proposed method is validated using high-resolution meter data recorded from 18 residential rooftop PV systems located on the island of Maui, Hawaii.

Data-driven modeling↗