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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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The poster showcases NREL team's accomplishments in supporting Electric Drive Technologies (EDT) consortium members in a fifth year of a six-year project funded by DOE Vehicle Technologies Office.
The integration of power electronics-based interfaces presents challenges due to the absence of detailed models and the high computational complexity. Generic models used in system studies lack accuracy in capturing converter dynamics. This paper proposes a data-driven approach developed from experimental setup data. This approach enhances accuracy in photovoltaic inverter modeling. We used two types of PV inverters in the experiment. The recorded experimental data undergo processing through a machine learning model. Results from the model trained through machine learning is also presented.
The rapid increase in data center energy demand, driven by AI and large-scale data processing, poses significant challenges to global energy infrastructure. Data centers require substantial and reliable energy for continuous operations and high-performance computing. Current electrical grids face issues such as transmission bottlenecks and aging infrastructure, making it difficult to meet these demands. Integrating inverter-based-resources (IBRs) like solar and wind presents both opportunities and challenges due to their intermittent nature. Small Modular Reactors (SMRs) offer a promising solution with their enhanced safety, modularity, reliability, and scalability, providing consistent base load power ideal for data center operations. This study presents a comprehensive techno-economic assessment of powering data center load demand using a combination of SMRs and IBRs with grid-connected and islanded mode. This study utilized Idaho National Laboratory’s (INL) HPC data center hourly load profiles and Xendee microgrid optimization platform to conduct the analysis. In this configuration, SMRs serves as the primary base load power source, consistently providing a steady supply of electricity necessary to meet the minimum load demand of the data center with support from the IBRs. Key performance indicators such as Levelized Cost of Electricity (LCOE), Net Present Value (NPV) has been calculated to assess the economic feasibility. The findings from this research will underscore the strategic benefits of integrating SMR plant with DERs – particularly for critical infrastructure load such as data centers.
This guide was developed through the U.S. Department of Energy (DOE) Energy Transitions Initiative Partnership Project (ETIPP) technical assistance (TA) projects for Nikolski and St. George. Both communities had wind turbine projects that failed due to integration and maintenance issues. Due to these failures, Nikolski and St. George sought help to investigate renewable energy alternatives and associated integration strategies, with a focus on technologies that could be easily maintained within the community. The primary objective of this guide was to interview subject matter experts and document lessons learned to address potential renewable energy and storage integration issues in remote Alaskan communities. This guide is intended to provide information to rural Alaskan communities considering renewables with the purpose of sharing best practices and case studies to facilitate the successful implementation of future renewable energy projects.
A reliable power supply is the foundation of modern society, enabling technologies used to function within a society. Residential systems are places where the end users directly consume power, enabling technologies to sustain life. With the emergence of behind-the-meter resources, the end-users have some control over power supply reliability. The intermittency and variability of these resources impact residential system reliability. In this work, we study the reliability performance of a grid-supplemented residential system with behind-the-meter Distributed Energy Resources(DER) subject to various system parameters and geospatial variables. We propose a multistate reliability model for the behind-the-meter microinverter-based Photo Voltaic (PV) system and integrated inverter-based energy storage (ES) system. A sequential Monte Carlo method is then presented to evaluate the reliability indices for the residential system with behind-the-meter DERs as the main supply and the grid as the backup. The sequential Monte Carlo method is used to analyze the reliability performance of the residential model at the top 100 populous counties of the United States, where actual load and solar irradiance data at the counties is used. In the analysis, the sensitivity of indices to system parameters such as DER size and the sensitivity of the indices to climate zone and gross horizontal irradiation (GHI), which affects the load conditions and the PV output of the residential system, is performed. The analysis results show that the system parameters and the geospatial variables significantly impact the residential system’s reliability. The insights from this analysis will be of immense value to the distribution system planners to provide zone-specific guidelines for DER system sizing and toward the evolution of utility business models. Finally, the methodology developed can be used to extend the analysis to other locations.
A second-harmonic, dispersion interferometer is used to image large-area (≃5 cm 2 ) plasma-jet and gas-jet density profiles. Achromatic telescopes magnify the diameters of the primary-laser beam (1064 nm) and its second-harmonic (532 nm) before probing the sample and de-magnify the beam diameters after the sample, where the primary beam transfers its phase change to a second, second-harmonic beam, allowing the sample’s dispersive-phase change to be measured between two, orthogonally polarized second harmonic beams. The telescopes produce an azimuthally symmetric, dispersive-phase shift in the sample + background phase-change image and in the background phase-change image, which is removed by digital subtraction. The interferometer’s performance was verified using standard-optical components as dispersive elements (BK7 lenses and wedge plates), resolving a minimum, phase-change sensitivity of ΔΦ min ≳ 15 mrad and spatial resolution of Δx res ≃ 100 μm. The phase change produced by unknown-density objects (a pulsed-plasma-jet and a pulsed-gas-jet) was measured, and their data were used to recover the original, 2D density profiles using an inverse Abel transform: peak-number density, N gas ≃ 6 × 10 20 cm –3 and N e ≃ 5 × 10 16 cm –3 ; line-integrated density, ∫N gas dl ~ 2 × 10 19 cm –2 and ∫N e dl ~ 1 × 10 16 cm –2 . The techniques and methods developed here are scalable to even larger probe-beam diameters and frame-capture rates, leading to a diagnostic capability that is well-suited for applications involving the real-time measurement of density.
Increasing power densities of electric vehicle traction drive systems necessitates combining the electric motor and the power electronics into one unit. A compact, integrated traction drive unit with fewer components also drives production costs down, enabling wider adoption of electric vehicles. However, the integration of power electronics in the electric machine is associated with challenges of designing an effective thermal management solution for the combined traction drive system. This paper focuses on the thermal management approach selected for Oak Ridge National Laboratory’s outer-rotor-motor-based integrated traction drive and evaluates its potential performance. The outer-rotor-motor configuration provided an opportunity for integration of the six-phase inverter in the available space in the central cavity of the internal stator. A cylindrical inverter enclosure with integrated coolant (water-ethylene glycol) channels in its walls was designed to enable heat removal from the power electronics. Numerical thermal-fluid modeling and initial channel/fin optimization results for the cylindrical heat sink are presented here. As permanent magnets are integrated in a high-speed (20 000 RPM) outer rotor, forced air convection provides cooling for the magnets. The magnets were segmented axially to mitigate the eddy current losses. Heat generated in the stator windings and laminations is removed by water-ethylene glycol coolant circulating in interpolar T-shape ceramic heat exchangers inserted between windings. General design concepts and numerical thermal-fluid simulations illustrating the electric motor thermal management solution are also presented.
The project team completed work to expand upon American Axle & Manufacturing’s (AAM) baseline technology and develop a high-speed, AC induction electric drive unit (EDU) with total direct-oil-cooling and integrated power electronics. The project accelerated advancements in EDU technology by allowing AAM to build upon the progress made in developing the underlying baseline technologies. The following seven improvements to AAM’s baseline technology were implemented in this research and development program: 1) Increased speed (30k RPM) AC induction motor, 2) Silver-sintering of discrete silicon carbide (SiC) metal-oxide-semiconductor field-effect transistors (MOSFET) to heat sinks, 3) Electrically insulated rotor bars, 4) Optimized lamination steel, 5) EDU-integrated 650VDC inverter package, 6) Over-molded stator with molded liners, and 7) 650VDC power-dense stator design. The successful development of the technology resulted in a meaningful cost reduction for EDU systems in the market. Coupled with falling battery system costs, lower EDU costs will likely accelerate the market acceptance and related production scaling of battery electric vehicles. The objective of this project was to research, develop, and test a Heavy Rare Earth (HRE)-free 3-In-1 electric drive unit (EDU) that has class leading power density and cost. The key technologies to be developed were anticipated to meet or exceed the Department of Energy (DOE) targets of a cost ≤ $\$$7/kilowatt (kW), power density ≥ 12 kW/liter, and operating voltage ≥ 600 VDC.
Vertical temperature profiles are derived from radiation measurements by inverting the integral equation of radiative transfer. Because of the nonuniqueness of the solution, the particular temperature profile obtained depends on the numerical inversion technique used and the type of auxiliary information incorporated in the solution. The choice of an inversion algorithm depends on many factors; including the speed and size of computer, the availability of representative statistics, and the accuracy of initial data. Results are presented for a numerical study comparing two contrasting inversion methods: the statistical-matrix inversion method and the nonstatistical-iterative method. These were found to be the most applicable to the problem of determining atmospheric temperature profiles. Tradeoffs between the two methods are discussed.
Considerations of the geometry appropriate to observations of the zodiacal light made from out of the ecliptic plane yield the general inversion of the brightness integral. The brightness per unit volume of interplanetary space can thus be determined in the immediate neighborhood of the spacecraft in directions confined to a unique viewing plane which depends upon the spacecraft's trajectory. The implementation of this technique guarantees the maximum information content of optical observations made from future deep-space probes including the 'Out-of-Ecliptic' mission scheduled for launch in 1983.
Equations written in terms of generalized Riemann variables are presently integrated by inverting six bidiagonal matrices and two tridiagonal matrices, using an implicit Euler solver that is based on the lambda-formulation. The solution is found on a C-grid whose boundaries are very close to the airfoil. The fast solver is then applied to the computation of several flowfields on a NACA 0012 airfoil at various Mach number and alpha values, yielding results that are primarily concerned with transonic flows. The effects of grid fineness and boundary distances are analyzed; the code is found to be robust and accurate, as well as fast.
The need for a predictive budget/funging model is obvious. The current models used by the Resource Analysis Office (RAO) are used to predict the total costs of satellite projects. An effort to extend the modeling capabilities from total budget analysis to total budget and budget outlays over time analysis was conducted. A statistical based and data driven methodology was used to derive and develop the model. Th budget data for the last 18 GSFC-sponsored satellite projects were analyzed and used to build a funding model which would describe the historical spending patterns. This raw data consisted of dollars spent in that specific year and their 1989 dollar equivalent. This data was converted to the standard format used by the RAO group and placed in a database. A simple statistical analysis was performed to calculate the gross statistics associated with project length and project cost ant the conditional statistics on project length and project cost. The modeling approach used is derived form the theory of embedded statistics which states that properly analyzed data will produce the underlying generating function. The process of funding large scale projects over extended periods of time is described by Life Cycle Cost Models (LCCM). The data was analyzed to find a model in the generic form of a LCCM. The model developed is based on a Weibull function whose parameters are found by both nonlinear optimization and nonlinear regression. In order to use this model it is necessary to transform the problem from a dollar/time space to a percentage of total budget/time space. This transformation is equivalent to moving to a probability space. By using the basic rules of probability, the validity of both the optimization and the regression steps are insured. This statistically significant model is then integrated and inverted. The resulting output represents a project schedule which relates the amount of money spent to the percentage of project completion.
Grid integration of photovoltaic (PV) inverters has been increasing in the past decade. As a result of the uncertainties introduced with high penetrations of PV, better monitoring and control of the PV inverters becomes crucial for improving overall system stability. This paper focuses on the communications capability of the inverter controller and on enabling interoperability. Multiple standards are available to enable interoperability in PV inverters. In this paper, an interoperable controller, enabled by Distributed Network Protocol 3 (DNP3) communications protocols, is developed for a grid-connected, three-phase PV inverter. The DNP3 server for the PV inverter is programmed on the real-time layer of the field-programmable gate array (FPGA)-based inverter controller. Set points for advanced inverter control functions, such as volt/VAr curves, ride-through curves, are sent from a DNP3 client, a simulated distribution management system application, to the PV inverter through DNP3. This communications capability of the inverter controller is validated using a controller-hardware-in-the-loop experimental setup. The code developed to achieve the interoperability is available in the public domain through open-source software licensing. This interoperability will enable smoother grid integration of smart PV inverters with advanced grid-support functions as well as allow better monitoring and control of PV inverters for grid stability.
The percentage integration of photovoltaic (PV) inverters in the field has increased significantly in the past 5 years. Regardless of the size of the PV plants and the inverters (residential vs. commercial), it is becoming crucial that these devices have the capability to communicate with peers (other smart devices) and with components that are at a hierarchy above the inverters (e.g., supervisory control and data acquisition (SCADA) systems, distributed controllers, and data managers). This project aims to develop a standard SCADA software code for inverters’ embedded controllers that will enable interoperability with other components in the system. To achieve this, the code will be developed using two different protocols: Distributed Network Protocol 3 and International Electrotechnical Commission 61850. The developed code is aimed to be deployed in simple embedded controllers. It will be tested in the National Renewable Energy Laboratory’s (NREL’s) Energy Systems Integration Facility. The tested code will then be made available through Triangle MicroWorks’s (TMW’s) software platform. The primary objectives of this project include training the NREL team with TMW’s embedded controller libraries, developing an interoperable communication code for embedded controllers, successfully testing and deploying the code, and demonstrating the newly developed code in a conference.
Traditionally, the inverters used for distributed energy resources (DERs) including solar, energy storage and hydrogen fuel cells are grid following assets. Grid following assets track real power and reactive power setpoints decided by either a local autonomous controller or a remote controller like a microgrid controller. In the past five years, multiple challenges have increased the need for grid forming inverters that can interface to a wide variety of energy resources. These grid forming inverters are becoming critical assets for power systems to enable the replacement of existing rotational machines and provide grid services such as grid resiliency services and black-start. Hydrogen assets (fuel cells) have the potential to successfully replace rotating machines and act as voltage and frequency master by leveraging the long-duration and seasonal energy storage capabilities of hydrogen technologies. This poster presents the progress made in budget period 1 of the proposed work. We will leverage an existing ARIES platform experimental setup to run power-hardware-in-the-loop and controller-hardware-in-the-loop experiments with grid forming fuel cell inverters to develop and document the standardization requirements.
The increasing integration of Inverter-Based Resources (IBRs) into the system has brought significant focus on their role in blackstart and restoration procedures. Their advantageous features, such as low startup power requirements, operational flexibility across a wide range of power factors, rapid controllability, and the ability to energize a network at lower voltage levels necessitate a reassessment of existing restoration protocols. This paper seeks to showcase how IBRs can utilize their grid-forming capabilities to provide power to a remote generating station through detailed EMT simulation studies using data collected from an existing portion of a network.
Compact dc/dc inverter uses single integrated-circuit package containing six inverter gates that generate and amplify 100-kHz square-wave switching signal. Square-wave switching inverts 10-volt local power to isolated voltage at another desired level. Relatively high operating frequency reduces size of filter capacitors required, resulting in small package unit.
PRECISE™ is a software solution for preconfiguring solar inverter settings. It can be used by utilities and system operators to efficiently process new inverter applications at much less the time and effort, and with greater precision for settings that optimize stability and energy savings. PRECISE has received an R&D 100 award, and has been used to dramatically cut wait times and labor costs for new residential solar installations.