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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Design of a Geothermal Power Plant With Solar Thermal Topping Cycle: Preprint

Geothermal power plants are a reliable source of low-carbon power generation. However, modern electricity markets comprise relatively large proportions of variable renewable energy generation that may require power plants to dispatch energy flexibly. The power output, efficiency, and dispatch flexibility of a geothermal plant can be enhanced by integrating solar thermal energy into the system, as well as possibly compensating against ambient temperature variations. Concentrating Solar Thermal (CST) can generate temperatures much higher than conventional geothermal systems. Using a solar topping cycle is one way to efficiently convert high-temperature solar heat to electricity while also adding lower-temperature heat to the geothermal power cycle, thereby increasing its power output and possibly its efficiency. A hybrid power cycle design is proposed and is simulated using SimTech IPSEpro process modelling software. The design configuration depends upon the expected temperature of the geothermal resource and the quantity of solar heat added at the design point. These design considerations are described and expected performance is calculated. The solar heat addition varies throughout the day and year, therefore off-design models are necessary to assess the impact of solar availability (and ambient temperature) on the power plant performance. Off-design models are developed and combined with hourly weather data to facilitate an evaluation of annual system performance.

concentrating solar power↗
DOE OSTI2024

Stacked-Die SiC Half-Bridge Module with Minimum Loop Inductance

Minimizing parasitic inductance of power modules is needed to advance their electrical performance. Innovation in the past decade has driven down the inductance of SiC half-bridge power modules to around 1–2 nH by using multilayer, embedded, and hybrid structures. Further reduction becomes difficult, mainly limited by the excessive interconnects required for the planar placement of vertical conducting chips. To address this, a vertically stacked-die approach is proposed in this paper, taking advantage of the vertical conducting nature of the SiC chips. With ceramic decoupling capacitors integrated, 0.48 nH overall loop inductance is achieved and validated by experimental measurement. This paper also discusses potential approaches to further reduce the inductance.

Ribeiro, Pedro↗
DOE OSTI2022

Analysis of Reactive Power Load Modeling Techniques for PV Impact Studies [Slides]

The increasing availability of advanced metering infrastructure (AMI) data has led to significant improvements in load modeling accuracy. However, since many AMI devices were installed to facilitate billing practices, few utilities record or store reactive power demand measurements from their AMI. When reactive power measurements are unavailable, simplifying assumptions are often applied for load modeling purposes, such as applying constant power factors to the loads. The objective of this work is to quantify the impact that reactive power load modeling practices can have on distribution system analysis, with a particular focus on evaluating the behaviors of distributed photovoltaic (PV) systems with advanced inverter capabilities. Quasi-static time-series simulations were conducted after applying a variety of reactive power load modeling approaches, and the results were compared to a baseline scenario in which real and reactive power measurements were available at all customer locations on the circuit. Overall, it was observed that applying constant power factors to loads can lead to significant errors when evaluating customer voltage profiles, but that performing per-phase time-series reactive power allocation can be utilized to reduce these errors by about 6x, on average, resulting in more accurate evaluations of advanced inverter functions.

14 SOLAR ENERGY↗
DOE OSTI2021

CO2 Electrolyzer to Produce Formic Acid at Industry Relevant Current Density

Electrochemical CO2 reduction reaction (CO2RR) to produce formic acid has attracted great interest recently since formic acid can be used as a feedstock for biorefineries. Over the past decade, much effort has been devoted to the prospects of electrochemical CO2 conversion to formic acid. However, issues including low current density, low selectivity, low energy efficiency, poor long-term stability, and production of formate salts instead of formic acid remain as the great challenges for the development and commercialization of this technology. Recently, Dioxide Materials (DM) has developed an electrolyzer technology that can directly convert CO2 to pure formic acid with a three-compartment CO2 electrolyzer. In this work, DM will present our recent effort on improving the electrolyzer performance operating at industry relevant current density (200 mA/cm2). We have demonstrated 200 mA/cm² with 80% Faradaic efficiency for 1000 hours of operation. The effects of CO2 concentration and impurities in the flue gas on the electrolyzer performance will be discussed, as will ongoing efforts to test the device at a coal fired power plant. The long-term (1000 h) performance of the electrolyzer will also be presented.

Yang, Hongzhou↗
DOE OSTI2026

Modeling Material Interfaces with the Six-Equation Model in FLEXO

FLEXO is a multiphysics code developed at Sandia National Laboratories for predictive simulation of pulsed power target physics with extended magnetohydrodynamics modeling. Given this application space, FLEXO must be able to perform high-fidelity simulations of pulsed-power systems that include multiple materials. This work presents the augmentation of FLEXO with a six-equation model for multimaterial flow. We design and analyze discretizations of the six-equation model, emphasizing desirable properties for robust multimaterial simulation. We also present solution limiting, bounds preservation, and pressure equilibration/relaxation techniques that enhance the robustness of the overall multimaterial scheme. We present a suite of test problems to document these new capabilities of the FLEXO code.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Monitoring Operational States of a Nuclear Reactor Using Seismoacoustic Signatures and Machine Learning

Monitoring nuclear reactors is an important safety and security task with growing requirements. We explore the possibility of using seismic and acoustic data for inferring the power level of an operating reactor. Continuous data recorded at a single seismoacoustic station that is located about 50 m away from a research reactor was visualized and analyzed. The data show a clear correlation between seismoacoustic features and reactor main operational states. We designed a workflow that includes two machine learning (ML) models to classify the reactor operational states (OFF, transition, and ON) and estimate reactor power levels (10%, 30%, 50%, 70%, and 90%). We applied and compared five ML algorithms for the reactor OFF-transition-ON and four approaches for the power level classification. We also compared the performance of ML models trained with seismic-only, acoustic-only, and both types of data. Five-fold cross validations were implemented to assure a thorough evaluation of the model performances. Additionally, the results show the extreme boosting gradient algorithm worked best for the first model, whereas random forests performed best for the second model. Combining seismic and acoustic data leads to better performance than using a single type of data. Seismic data contributed more than acoustic data for both models. We reached an accuracy of 0.98 for reactor OFF and ON. The accuracies for the transition state and power levels are less optimal with a minimum accuracy of 0.66. However, our results suggest seismic and acoustic data contain useful information about the transition state as well as power levels. Seismic and acoustic data could be integrated with other observations to improve monitoring performance.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Thermopile Energy Harvesting for Subsurface Wellbore Sensors (Final Report)

Robust in situ power harvesting underlies all efforts to enable downhole autonomous sensors for real-time and long-term monitoring of CO 2 plume movement and permeance, wellbore health, and induced seismicity. This project evaluated the potential use of downhole thermopile arrays, known as thermoelectric generators (TEGs), as power sources to charge sensors for in situ real-time, long-term data capture and transmission. Real-time downhole monitoring will enable “Big Data” techniques and machine learning, using massive amounts of continuous data from embedded sensors, to quantify short- and long-term stability and safety of enhanced oil recovery and/or commercial-scale geologic CO 2 storage. This project evaluated possible placement of the TEGs at two different wellbore locations: on the outside of the casing; or on the production tubing. TEGs convert heat flux to electrical power, and in the borehole environment, would convert heat flux into or out of the borehole into power for downhole sensors. Such heat flux would be driven by pumping of cold or hot fluids into the borehole—for instance, injecting supercritical CO 2 —creating a thermal pulse that could power the downhole sensors. Hence, wireless power generation could be accomplished with in situ TEG energy harvesting. This final report summarizes the project’s efforts that accomplished the creation of a fully operational thermopile field unit, including selection of materials, laboratory benchtop experiments and thermal-hydrologic modeling for design and optimization of the field-scale power generation test unit. Finally, the report describes the field unit that has been built and presents results of performance and survivability testing. The performance and survivability testing evaluated the following: 1) downhole power generation in response to a thermal gradient produced by pumping a heated fluid down a borehole and through the field unit; and 2) component survivability and operation at elevated temperature and pressure conditions representative of field conditions. The performance and survivability testing show that TEG arrays are viable for generating ample energy to power downhole sensors, although it is important to note that developing or connecting to sensors was beyond the scope of this project. This project’s accomplishments thus traversed from a low Technical Readiness Level (TRL) on fundamental concepts of the application and modeling to TRL-5 via testing of the fully integrated field unit for power generation in relevant environments. A fully issued United States Patent covers the wellbore power harvesting technology and applications developed by this project.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

A High Power Density and High Efficiency Traction Drive Based on a Segmented Inverter and an Axial and Radial Flux Hybrid Machine

Eaton Corporation and Oak Ridge National Laboratory (ORNL) collaborated to develop a high performance traction drive system aimed at increasing power density and overall efficiency. The system integrates Eaton’s hybrid flux motor—combining radial and axial flux paths to convert end-winding and structural elements into torque-producing components—with ORNL’s high-power-density segmented inverter. This motor design achieves higher torque density within the same footprint as traditional radial flux machines by effectively utilizing end turns. ORNL’s segmented inverter reduces the DC bus capacitor requirement by over 50% compared to standard voltage source inverters (VSIs), achieving power densities exceeding 100 kVA/L. The dual-module architecture also enables six-phase operation, aligning with Eaton’s motor design. Together, the motor and inverter offer a compact, efficient traction drive system with the potential for significant reductions in system weight and improvements in powertrain efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Cost and Performance Estimates for State-of-the-Art and Advanced 1×1 H-Class Natural Gas-Fired Power Plants

As an extension of NETL's Fossil Energy Baseline for Electricity Generating Units Volume 1: Coal and Natural Gas to Electricity (FEB Rev 4a, this study develops cost and performance estimates for analogous NGCC cases using a state-of-the-art 2023 vintage H-Class CT in a 1×1 configuration, where a single combustion turbine and heat recovery steam generator are coupled to a single steam turbine on a common shaft. These 1×1 H-Class cases are used to develop cost and performance estimates of X-Class 1×1 NGCC cases with advanced performance characteristics, analogous to NETL’s cost and performance projections report.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

A Novel Multi-Agent Deep Reinforcement Learning-enabled Distributed Power Allocation Scheme for mmWave Cellular Networks

We consider the power allocation problem over shared spectrum for millimeter-Wave (mmWave) cellular downlink. Existing approaches usually find sub-optimal solutions by solving a non-convex optimization which leads to scalability issues due to centralized control. Therefore, distributed and adaptive approaches are desirable. Recently, model-free Deep Reinforcement Learning (DRL) has achieved success in such wireless resource management tasks. By modeling the radio environment as a Markov Decision Process (MDP) with the base stations (BSs) being the agents, power allocation can be automated at the agent level with comparable throughput performance to conventional centralized schemes. The multi-agent setting presents new challenges as the radio environment is impacted by the joint actions of the agents and is no longer stationary from any individual agent’s perspective. Existing literature bypasses this non-stationarity violation by ignoring it which may cause performance degradation. To tackle this issue, we propose a distributed continuous power allocation scheme based on a modified version of multi-agent Deep Deterministic Policy Gradient (MADDPG) that is tailored for the distributed multiple-agent setting. The proposed scheme employs a centralized-training distributed-execution framework where Q-functions are trained over subsets of BSs while each BS determines its transmit power based only on its own local observation. It admits constant per-BS communication and computation complexity and is thus scalable to large networks. Numerical evaluation shows that the proposed scheme adapts well to a wide range of interference conditions and can achieve comparable or better performance than several state-of-the-art non-learning approaches.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

UNCERTAINTIES FOR IN-REACTOR TESTING OF TRITIUM LOADED GETTERS WITH TEMPERATURE CONTROL

The fourth experiment in TPBAR Materials Irradiation Separate-Effects Test (TMIST) series (TMIST-4) is planned to experimentally determine the effect of neutron irradiation on the equilibrium vapor pressure of tritium over a tritium loaded Nickel-Plated Zirconium (NPZ) getter in a simulated TPBAR service environment. This pressure will be used to estimate the tritium permeation rate. In the thermal design in the TMIST-4, two evaluations are required. 1) The cladding temperature is calculated to estimate the feasibility of detecting potential irradiation enhancement of the partial pressure for an NPZ getter. This work is required to obtain a precise cladding temperature for measurement of a low tritium partial pressure. This work has been completed and indicated that the required/target cladding temperatures based on the TMIST-4 test plan can be satisfied under the test condition range by modifying the capsule component shapes and inserting a thermally conductive metal sleeve. 2) The evaluation of uncertainties associated with the test design and operation is performed. This includes fabrication tolerances, and power and nuclear operating conditions. These factors will impact the component temperatures inside capsules and resulting the tritium partial pressure. The tritium permeation rate is a function of temperature and tritium partial pressure. The prediction of tritium permeation rates affects the feasibility of obtaining measurement resolutions required to reach reasonable conclusion for potential irradiation enhanced performance. This work will investigate the uncertainties.

TTP, TPBAR, TMIST-4, TPBAR Materials Irradiation S↗
DOE OSTI2026

Testing and Expertise for Marine Energy (TEAMER) Program Support (CRADA Final Report)

Virginia Tech (VT) had previously developed a 50 kW AC to DC power converter that is specifically designed to improve the performance and efficiency of wave energy converters (WECs). Through this CRADA, NLR will test the VT power converter via a coupled dynamometer and power electronics test platform. The NLR test platform will be comprised of (1) a rotary dynamometer that will drive a VT provided gearbox and generator, (2) one or more DC regenerative power supplies that provide input power to and take power from the VT supplied power electronics, and (3) a data acquisition system for measurement. NLR will work with VT to develop a test plan, set up the test platform and integrate the test article, perform the testing, and assist in the data analysis.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

A Framework for Error-Bounded Approximate Computing, with an Application to Dot Products

Approximate computing techniques, which trade off the computation accuracy of an algorithm for better performance and energy efficiency, have been successful in reducing computation and power costs in several domains. However, error sensitive applications in high-performance computing are unable to benefit from existing approximate computing strategies that are not developed with guaranteed error bounds. While approximate computing techniques can be developed for individual high-performance computing applications by domain specialists, this often requires additional theoretical analysis and potentially extensive software modification. Hence, the development of low-level error-bounded approximate computing strategies that can be introduced into any high-performance computing application without requiring additional analysis or significant software alterations is desirable. In this paper, we provide a contribution in this direction by proposing a general framework for designing error-bounded approximate computing strategies and apply it to the dot product kernel to develop \bf qdot---an error-bounded approximate dot product kernel. Following the introduction of qdot, here we perform a theoretical analysis that yields a deterministic bound on the relative approximation error introduced by qdot. Empirical tests are performed to illustrate the tightness of the derived error bound and to demonstrate the effectiveness of qdot on a synthetic dataset, as well as two scientific benchmarks---the conjugate gradient (CG) and power methods. In some instances, using qdot for the dot products in CG can result in many components being quantized to half precision without increasing the iteration count required for convergence to the same solution as CG using a double precision dot product.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Conceptual design of a high reactive-power ferroelectric fast reactive tuner

We present a novel design of a ferroelectric fast reactive tuner (FE-FRT) capable of modulating mega-VAR reactive power on a submicrosecond timescale. The high reactive power capability of our design extends the range of applications of reactive tuners to numerous applications. We present a detailed analytical model of the performance of a megawatt-class reactive power device and benchmark it against finite-element method eigenmode and frequency domain electromagnetic simulations. We introduce new features, including an annulus design for the ferroelectric capacitors and capacitive window coupling to the cavity. We consider thermal design issues and nonlinear effects in the ferroelectric. The model covers several configurations, allowing control of the frequency of superconducting and normal-conducting cavities in a variety of applications and frequencies. We calculate that the FE-FRT designed should be capable of handling around 0.45 MVAR of reactive power with around 3 kW of resistive losses, providing a frequency tuning range of 8 kHz in an example of 400 MHz cavity geometry. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Soft Actor Critic Based Volt-VAR Co-optimization in Active Distribution Grids

Modern distribution networks are undergoing several technical challenges, such as voltage fluctuations, because of high penetration of distributed energy resources (DERs). This paper proposes a deep reinforcement learning (DRL)-based Volt VAR co-optimization technique for reducing voltage fluctuations as well as power loss under high penetration of DERs. In addition, the proposed approach minimizes the operational cost of the grid. A stochastic policy optimization based soft actor critic (SAC) agent is proposed to configure the optimal set-points of the reactive power outputs of the inverters. The performance of the proposed model is verified on the modified IEEE 34- and 123-bus systems and compared with a base case scenario with no reactive supply by inverters, and a local droop control approach. The results demonstrate that the proposed framework outperforms the conventional droop control method in improving the voltage profile, minimizing the network power loss, and reducing grid operational cost.

—Distribution grids, deep reinforcement learning, ↗
DOE OSTI2020

Annual Technology Baseline: The 2020 Electricity Update

Consistent cost and performance data for various electricity generation technologies can be difficult to find and may change frequently for certain technologies. With the Annual Technology Baseline (ATB), the National Renewable Energy Laboratory annually provides an organized and centralized set of such cost and performance data. The ATB uses the best information from the Department of Energy national laboratories' renewable energy analysts. The ATB has been reviewed by experts and it includes the following electricity generation technologies: land-based wind, offshore wind, utility-scale solar photovoltaics (PV), commercial-scale solar PV, residential-scale solar PV, concentrating solar power, geothermal power, hydropower, utility-scale battery storage. EIA data for coal, natural gas, nuclear, and conventional biopower are included for reference. This webinar presentation introduces the 2020 update to the ATB Electricity data and documentation.

capacity factor↗
DOE OSTI2022

Frequency Restoration of Grid-Forming Inverters in Pulse Load and Plug-in Events

This article presents a restoration technique using grid-forming inverters in an islanded microgrid during pulse load and plug-in events. In a microgrid powered by droop-controlled inverters, frequency is the variable that is accessible to all inverters for adjusting their power contributions. The problem is that the microgrid frequency deviates from its nominal value after a load change. The presented method enables the inverters to restore the frequency to the nominal value and regulate their bus voltage amplitudes. The frequency and voltage restorations are performed without communication while achieving the desired power-sharing between grid-forming inverters. The restoration is activated after detecting any active or reactive power changes. In this article, the dynamic model of an inverter equipped with enabled restoration paths is developed to verify the stability of the inverter controller under various conditions. The frequency and voltage restorations are examined during pulse load and plug-in events. Furthermore, this study is performed using a laboratory-scale islanded microgrid powered by two 208 V, 60 Hz, 5 kVA inverters.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Real-Time Modal Analysis of Electric Power Grids - The Need for Dynamic State Estimation

We articulate the reason why dynamic state estimation is needed to push the boundaries of the modal analysis of electric power grids in real-time operation. Then, we demonstrate how to unravel linear and nonlinear modes by using the extended dynamic mode decomposition along with estimates of the synchronous generators’ rotor angles and rotor speed deviations from nominal speed. The estimated modes are associated with electromechanical oscillations that take place continuously in electric power grids because of imbalances between power generation and demand. The numerical simulations are performed on a synthetic, albeit realistic, 2,000-bus network that was designed to resemble the electric power grid of Texas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗