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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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In the presentation thermal management of electric traction drives is discussed and capabilities of NREL's Advanced Power Electronics and Electric Machines group is reviewed. Emphasis is made on jet impingement cooling technique of electric machines with driveline fluids and experimental measurements of associated heat transfer coefficients.
ComStock is a DOE platform, with NREL as the lead developer, that models the U.S. commercial building stock using OpenStudio/EnergyPlus to perform physics-based building energy modeling simulations. The ASHRAE Epidemic Taskforce (ASHRAE-ETF) has released several COVID-19 mitigation strategies for commercial buildings. ComStock was used to analyze the impact of four strategies on the existing commercial building stock. These strategies are upgrading to MERV-13 filters, disabling demand control ventilation (DCV), increasing minimum outdoor air to 100%, and HVAC flushing mode operation. Results show the impact of each measure on energy consumption, electric consumption, gas consumption and peak electric.
Recent advances in deterministic unit commitment, both formulaic and algorithmic, along with modern algorithmic approaches for stochastic programming, have enabled the solution of stochastic unit commitment problems with hundreds of scenarios on large-scale transmission networks. In this presentation, we will give an overview of these methods, including lazy transmission constraint generation, lower-bounding techniques, and heuristics, all of which can be executed in concert with customized decomposition approaches for optimization under uncertainty. We demonstrate the effectiveness of these techniques on the TAMU Texas7K synthetic transmission network, leveraging realistic high-resolution forecasts based on NREL renewable resource availability data. The software leveraged for these demonstrations is available via the open-source software packages EGRET (for electrical grid optimization) and mpi-sppy (for optimization under uncertainty).
While deep learning tools, coupled with the emerging machinery of topological data analysis, are proven to deliver various performance gains in a broad range of applications, from image classification to biosurveillance to blockchain fraud detection, their utility in areas of high societal importance such as power system modeling and, particularly, resilience quantification in the energy sector yet remain untapped. To provide fast acting synthetic regulation and contingency reserve services to the grid while having minimal disruptions on customer quality of service, we propose a new topologybased system that depends on neural network architecture for impact metrics classification and prediction in power systems. This novel topology-based system allows one to evaluate the impact of three power system contingency types, namely, in conjunction with transmission lines, transformers, and transmission lines combined with transformers. We show that the proposed new neural network architecture equipped with local topological measures facilitates both more accurate classification of unserved load as well as the amount of unserved load. In addition, we are able to learn complex relationships between electrical properties and local topological measurements on the simulated response to contingencies for NREL-SIIP power system.
We discuss the value of collaborative, immersive visualization for the exploration of scientific datasets and review techniques and tools that have been developed and deployed at the National Renewable Energy Laboratory (NREL). We believe that collaborative visualizations linking statistical interfaces and graphics on laptops and high-performance computing (HPC) with 3D visualizations on immersive displays (head-mounted displays and large-scale immersive environments) enable scientific workflows that further rapid exploration of large, high-dimensional datasets by teams of analysts. We present a framework, PlottyVR, that blends statistical tools, general-purpose programming environments, and simulation with 3D visualizations. To contextualize this framework, we propose a categorization and loose taxonomy of collaborative visualization and analysis techniques. Finally, we describe how scientists and engineers have adopted this framework to investigate large, complex datasets.
This study introduces a new technique to compute direct normal irradiance (DNI) for improving the National Solar Radiation Data Base (NSRDB). A finite-surface integration algorithm is developed to compute solar radiation in differential solid angles and efficiently infer its contribution to a surface perpendicular to the solar direction. A lookup table of cloud bi-directional transmittance distribution function (BTDF) is developed by use of the discrete ordinates radiative transfer (DISORT) model for possible solar and observing directions and various cloud optical and microphysical properties. In each solar incident direction, DNI is given by the cloud BTDFs from approximately 200 differential solid angles. The simulated DNI is calibrated and evaluated using surface observations at the National Renewable Energy Laboratory's (NREL's) Solar Energy Research Laboratory (SRRL) and the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) facility.
NREL’s REopt Lite web tool helps users evaluate the economic viability of distributed photovoltaic (PV), wind, battery storage, combined heat and power, and thermal energy storage systems. REopt Lite was designed for locations within the United States; however, with appropriate adjustments, it is possible to use most of its features for international locations.
Under the Advanced Research for Integrated Energy Systems (ARIES) initiative, NREL will build out hydrogen system capabilities at the Flatirons campus. The hydrogen infrastructure at the Flatirons campus will include a research-ready megawatt-scale electrolyzer with hydrogen compression and storage, and a fuel cell system. This hardware will support H2@Scale goals by enabling integrated systems R&D (e.g., to demonstrate grid services, energy storage, renewable hydrogen production, and innovative end-use applications). The system will be coupled with the controllable grid interface at the Flatirons campus and will be designed with flexibility to provide a testbed for integrated electrolyzer R&D, hydrogen utilization R&D, and to study the science of scaling for hydrogen energy systems.
This webinar, presented by Paul Denholm and Will Frazier, incorporates material from two publications of the NREL Storage Futures Study: "The Four Phases of Storage Deployment: A Framework for the Expanding Role of Storage in the U.S. Power System" (https://www.nrel.gov/docs/fy21osti/77480.pdf) and "Storage Futures Study: Economic Potential of Diurnal Storage in the U.S. Power Sector" (https://www.nrel.gov/docs/fy21osti/77449.pdf).
This fact sheet discusses the opportunity space for NREL's computational science capabilities to address national clean energy objectives. Achieving a carbon-free power sector by 2035 as a step towards a decarbonized U.S. energy economy in 2050 will require major advances in power generation, autonomous energy systems, transportation, and buildings/communities. Development of integrated modeling approaches for complex energy systems will be essential for deployment. Success requires developments in optimization and control theory, complemented by machine learning (ML) and artificial intelligence (AI), all of which in turn need targeted investments in breadth and scale of computing. This document defines an opportunity space where: embracing computing can link established research and development (R&D) to a decarbonization agenda; pursuing emerging approaches can accelerate the pace of technology advancement across the portfolio; and leading by example could reduce the carbon footprint of computing worldwide.
As the perovskite technology is ramping up into commercialization, reliable and accurate power rating of large-size perovskite modules becomes a prominent aspect for its future deployment in the PV market. It is known that the performance calibration of perovskite PV devices is very challenging due to its complex dynamic response during a conventional current-voltage (IV) measurement. PV researchers have previously proposed several steady-state performance calibration methods to reliably extract PV efficiencies, but mostly focus on small area research-type cells. In this paper, we emphasize the importance of reliable performance calibration on large-size perovskite modules. Extending the NREL Cell and Module Performance (CMP) group’s steady-state performance calibration protocol (i.e., Asymptotic PMAX Scan) for perovskite cells to modules, we justify the necessity of reporting steady-state efficiencies for perovskite cells and discuss the challenges of applying this protocol to modules. We also present our protocol for Maximum Power Point Tracking (MPPT), which is a technique often used for performance calibration of perovskite cells and modules, and show a comparison between MPPT and Asymptotic PMAX. Using MPPT we demonstrate the interplay between metastability and degradation in perovskite modules, and emphasize the necessity to develop preconditioning protocols for stabilizing these devices. Our aim is to promote development of consensus protocols for performance calibration of perovskite modules, and to advance their credible power ratings, which will be beneficial to the growth of perovskite technology in the PV market.
This growing number of smart devices that support DERs can increase the number of access points outside a utility’s administrative domain, which can increase the potential for cyberattack. With the integration of DERs at federal sites, the cybersecurity vulnerabilities of DER systems must be understood and addressed. This presentation covers two NREL tools available. The Distributed Energy Resource Cybersecurity Framework (DER-CF) is a web-based holistic tool for evaluating cybersecurity posture including governance, physical security and technical management. The Distributed Energy Resource Risk Manager (DER-RM) extends the DER-CF by applying it to the NIST risk management framework process. It will be downloadable application that runs locally and documents all the major requirements for achieving Authority to Operate the DER.
This fact sheet summarizes the National Renewable Energy Laboratory’s (NREL’s) State, Local, and Tribal Technical Support Services Agreement contract mechanism. The service extends the benefits of national laboratory expertise to state and local energy project decision makers and planners charting the course to a clean energy future.
Increased deployment of wind and solar raises new questions for power system planners regarding the future mix of generation technologies, optimal siting of generation capacity, trade-offs between generation and transmission investments, and system flexibility needs. The National Renewable Energy Laboratory (NREL) is working with Tamil Nadu Generation and Distribution Company (TANGEDCO) to answer the following questions: How much—and what type—of generation and transmission investments are needed to serve future demand at least cost? How can variable resources such as wind and solar be considered in the planning process? What are the key drivers (e.g., policies, technology costs, fuel constraints) for investments?
An international team led by NREL analyzed the favorability of two alternative liquid receiver designs for a 700+ °C receiver under the Gen3 CSP Liquid Pathway project. The competing liquid heat transfer fluids were a ternary chloride salt and liquid-metal sodium. The team applied a facilitated analytic hierarchy process (AHP) to arrive at a recommended alternative and set a path forward for the project. The AHP criteria were formulated, weighted, and scored by the project leadership team and technical advisory committee consisting of energy industry and CSP experts. The six-month process culminated with a two-day workshop where the sodium alternative was deemed to have both a significantly higher benefit (19.3%) and a lower LCOE (11.4%), with only a slightly higher risk (~3%) than the salt alternative. Consequently, a sodium-receiver design was selected for the Liquid Pathway project, where it will be used to charge a two-tank chloride salt thermal energy storage system.
Heterogeneous catalysts are a key enabler of the transition towards a sustainable, bio-based economy for fuels and chemicals. However, the harsh conditions in many biomass conversion processes lead to nanoparticle sintering, support collapse, and metal leaching in conventional PGM catalysts. Next-generation catalysts must be developed to address these stability challenges. This presentation will discuss ongoing work between the Catalytic Carbon Transformation and Scale-Up Center at NREL and various industrial partners to develop scalable and cost-effective atomic layer deposition (ALD) coatings for improving the performance of biomass conversion catalysts. The substantial focus will be devoted to the benefits of TiO2 ALD coatings on supported Pd hydrogenation catalysts. Ten cycles of TiO2 ALD were found to dramatically improve the activity of a conventional Pd/Al2O3 catalyst towards aromatic hydrogenation, despite partial coverage of the Pd sites by the ALD layer. Subsequent advanced characterization and atomic-scale computational modeling revealed that the ALD coating weakened the adsorption strength of hydrogenation surface intermediates, leading to higher reaction rates. Reaction testing after exposure to sulfur impurities, high temperature oxidation, and hydrothermal treatment demonstrated the improved stability of the ALD-coated catalyst. Additionally, the ALD synthesis process was found to be scalable over two orders of magnitude with minimal deviation in synthesized catalyst properties. These results were contextualized with cost models of industrial ALD coating and aromatic hydrogenation processes to further refine the value proposition of ALD coatings. Given the demonstrated improvements in hydrogenation, TiO2 ALD coatings have also been applied to supported Pt catalysts for use in other biomass conversion reactions, such as hydrodeoxygenation for the production of sustainable aviation fuel (SAF) and the oxidation of glucose to bio-derived gluconic acid.
Renewable energy systems continue to be one of the fastest growing segments of the energy industry. This paper focuses on the understanding of how photovoltaic (PV) technology behaves under dc arc conditions. Emphasis is placed on the electrical safety aspect of DC arc flash incident energy evaluation. Because of the fast proliferation of PV systems and the lack of formal equivalent calculation guidelines such as IEEE 1584 for AC systems, it has been necessary to rely on different equations and models presented by various researchers over the last few years. This paper discusses the behavior of PV systems under arc conditions and presents the results of available methods to estimate the dc arc flash incident energy. This paper provides a comparative analysis of a proposed arc-flash incident energy calculation method against different laboratory tests including those performed by NREL. Detailed explanations are provided regarding the effect of PV module I-V and P-V curves under arcing conditions. Examples of the application of the proposed calculation method to the test measurements are included.
The locatable mineral industry is shifting toward improving environmental performance and becoming more sustainable, with numerous mining companies shifting to renewable energy technologies to power mine operations and at least one company pledging net-zero emissions by 2050. One potential electricity source to help achieve improved environmental performance and decarbonization within the mining industry is geothermal energy. As part of a study into potential collaboration between the geothermal and locatable mineral industries (focused on the portion of the Basin and Range Province within Nevada), the National Renewable Energy Laboratory (NREL) with support from the U.S. Department of Energy (DOE) Geothermal Technologies Office (GTO), investigated data, economic, and regulatory factors that may contribute to or inhibit synergies between the two industries. The objectives of the study included analyzing: The type and quality of data collected by the locatable mineral industry to determine feasibility for geothermal resource exploration; The regulatory pathways and potential barriers that could prevent development of geothermal resources discovered via a mining claim (and vice versa); The historical development of geothermal resources discovered via mineral exploration data; The value propositions for both the locatable mineral and the geothermal industries to collaborate.
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