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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 OSTI2020

Exploring the Acceleration Mechanisms for Particle Injection and Power-law Formation during Transrelativistic Magnetic Reconnection

Magnetic reconnection in the relativistic and transrelativistic regimes is able to accelerate particles to hard power-law energy spectra f ∝ γ -p (approaching p = 1). The underlying acceleration mechanism that determines the spectral shape is currently a topic of intense investigation. By means of fully kinetic plasma simulations, we carry out a study of particle acceleration during magnetic reconnection in the transrelativistic regime of a proton–electron plasma. While earlier work in this parameter regime has focused on the effects of electric field parallel to the local magnetic field on the particle injection (from thermal energy to the lower-energy bound of the power-law spectrum), here we examine the roles of both parallel and perpendicular electric fields to gain a more complete understanding on the injection process and further development of a power-law spectrum. We show that the parallel electric field does contribute significantly to particle injection, and is more important in the initial phase of magnetic reconnection. However, as the simulation proceeds, the acceleration by the perpendicular electric field becomes more important for particle injection and completely dominates the acceleration responsible for the high-energy power-law spectrum. This holds robustly, in particular for longer reconnection times and larger systems, i.e., in simulations that are more indicative of the processes in astrophysical sources.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Deep Learning Based Frequency Stability Assessment in Power Grid with High Renewables

Frequency stability assessment is one critical aspect of power system security assessment. Traditional N-1 screening method is based on the simulations of a few typical daily and seasonal operation scenarios. However, the increasing integration of inverter-based renewables and the retirement of conventional synchronous generators result in decreasing system inertia and growing complexity of system operating conditions. Selecting a few typical operation scenarios cannot cover all operating conditions, and the time-domain simulation of all operation conditions requires tremendous time. This paper proposes a more efficient frequency stability assessment method based on deep learning. The affinity propagation clustering algorithm is used to divide the dataset into different clusters, so the selected dataset for training can cover the diversified operating conditions as much as possible. Also, feature normalization is applied to both the training dataset and testing dataset in order to remove any unnecessary bias. Especially, trained model based on full dataset normalization has bounded error in the prediction. The case study on the reduced 240-bus WECC system demonstrates that the proposed method can predict accurate frequency nadir with limited training dataset. The deep learning model using the revised feature normalization can predict more accurate frequency nadir than that using the traditional feature normalization and has very small maximum prediction error.

affinity propagation↗
NASA NTRS2006

MXER Simulation Study (Appendix B)

The task of prediction of the motion of a momentum exchange system with a 9-digit accuracy is extremely challenging, and it is relentlessly testing our ability to gain fundamental insights into the nature of the tether dynamics in this system. It has been show that the modal decomposition approach developed in the first part of this study is a very powerful and precise tool for the simulation of the dynamics of momentum exchange tethers. However, to get a prediction with required accuracy using this tool, one must have precise inputs, including the initial state, system parameters, and the environmental models. In simulations, the tether tip positioning has been observed to be quite sensitive to even small variations of the parameters involved in the calculations. It is therefore imperative that precise estimation and control algorithms be developed to compensate for the inevitable uncertainties and support high precision rendezvous.

Levin, E. M.↗
NASA NTRS1985

Inverter design for high frequency power distribution

A class of simple resonantly commutated inverters are investigated for use in a high power (100 KW - 1000 KW) high frequency (10 KHz - 20 KHz) AC power distribution system. The Mapham inverter is found to provide a unique combination of large thyristor turn-off angle and good utilization factor, much better than an alternate 'current-fed' inverter. The effects of loading the Mapham inverter entirely with rectifier loads are investigated by simulation and with an experimental 3 KW 20 KHz inverter. This inverter is found to be well suited to a power system with heavy rectifier loading.

King, R. J.↗
DOE OSTI2020

Investigating the Impact of Power-Take-Off System Parameters and Control Law on a Rotational Wave Energy Converter’s Peak-to-Average Power Ratio Reduction

Due to the irregular nature of real waves, the power captured in a wave energy converter (WEC) system is highly variable. This is an important barrier to the effective use of WECs. To address this challenge, this study focuses on a rotational WEC power-take-off system in which high-speed and high-efficiency generators along with a torque/power smoothing inertia element can be effectively utilized. In the first phase of this study, the U.S. Department of Energy’s reference model 3 (WEC-Sim RM3; two-body point absorber), along with a slider-crank WEC, were integrated for linear to rotational conversion. Relative motion between the float and spar in RM3 was the driving force for this slider-crank WEC, which is connected to a motor/generator set through a gearbox. RM3 geometry was scaled down by 25 times to work within the limits of the physical motor/generator set used in the experimentation. Once the integration in a hardware-in-the-loop simulation environment was successfully completed, data on the peak-to-average power ratio was collected for various wave conditions including regular and irregular waves. The control algorithm designed to keep the system in resonance with waves was able to maintain relatively high speed depending on the specific gear ratio and wave period. Initial results with hardware-in-the-loop simulations reveal that gear ratio and crank radius have a strong impact on the peak-to-average power ratio. In addition, it was found that output power from the generator was maximized at a larger gear ratio, as the crank radius was increased.

50 EE - Wind and Water Power Program - Water (EE-4↗
NASA NTRS1994

Simulating Rain Fade In A Communication System

Automated, computer-controlled assembly of electronic equipment developed for use in simulation testing of downlink portion of Earth/satellite microwave digital communication system. Designed to show effects upon performance of system of rain-induced fading in received signal and increases in transmitted power meant to compensate for rain-induced fading. Design of communication system improved iteratively in response to results of simulations, leading eventually to design ensuring clear, uninterrupted transmission of digital signals.

Shalkhauser, Kurt A.↗
NASA NTRS1984

Electrical System Technology Working Group (WG) Report

The technology needs for space power systems (military, public, commercial) were assessed for the period 1995 to 2005 in the area of power management and distribution, components, circuits, subsystems, controls and autonomy, modeling and simulation. There was general agreement that the military requirements for pulse power would be the dominant factor in the growth of power systems. However, the growth of conventional power to the 100 to 250kw range would be in the public sector, with low Earth orbit needs being the driver toward large 100kw systems. An overall philosophy for large power system development is also described.

Silverman, S.↗
DOE OSTI2023

Frequency Resilience Enhancement for Power Systems with High Penetration of Grid-Forming Inverters

Abstract—Grid following inverter-based renewable generation has replaced conventional generation in recent years, resulting in lower system inertia. The frequency resilience in such a lower inertia system is critical for emergency mitigation. In this paper, we propose a resilience metric based on frequency recovery to quantitatively represent system resilience in terms of the rate of change of frequency. Application of grid-forming converters provides a means to improve system resilience by providing virtual inertia. An under-frequency load shedding strategy is applied to further support frequency recovery in cases with high penetration of grid-forming inverters. Case studies are designed and performed in a modified IEEE 9-bus test system using the PSCAD/EMTDC platform. Simulation results demonstrate the validity of the proposed resilience metric and the effectiveness of the strategy for reducing frequency excursion in inverter-based power systems. citation: J. Gui, H. Lei, T. R. McJunkin and B. K. Johnson, "Frequency Resilience Enhancement for Power Systems with High Penetration of Grid-Forming Inverters," 2023 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington, DC, USA, 2023, pp. 1-5, doi: 10.1109/ISGT51731.2023.10066357.

14 SOLAR ENERGY↗
DOE OSTI2023

A Novel LCC-CLCC Resonant Tuning Network for Light-Load Conditions in Wireless Power Transfer Systems

In wireless power transfer (WPT) systems, voltage and current distortions are observed at the vehicle side rectifier when power flow is from grid to vehicle (G2V) under light load conditions. These distortions can increase switching losses and decrease the overall efficiency of the WPT system. To address this issue, this paper proposes adding a higher value inductor in series with the original LCC tuning network at the vehicle side. However, increasing the series inductance causes the input impedance and phase angle to move away from the resonant frequency. To solve this problem, a capacitor is added in series to tune out the difference between the original and modified inductor values. This series tuning capacitor also improves the power factor and brings the input impedance and phase angle back to the resonant frequency. The traditional LCC-LCC and proposed LCC-CLCC WPT systems are compared and analyzed analytically, and simulated in a MATLAB/Simulink environment to verify parameters such as efficiency and power transfer capacity. An experimental prototype is implemented and compared with the simulation. The obtained results confirm the validity of the proposed method.

Harave, Sudarshan↗
DOE OSTI2021

CARPE DIEM: Coupled Algorithms for Robust Partitioning of Equations for the Dynamic Interactions of Evolving Materials

From aircraft design to non-proliferation, technical and policy decisions are becoming increasingly reliant on simulation of complex, real-world, multi-physics systems involving multiple interacting domains. As the power of computers has grown, deficiencies associated with traditional low-order-accurate mechanisms for inter-domain coupling have become increasingly apparent. The CARPE DIEM project addressed such deficiencies in the context of fluid-structure interaction (FSI) by developing new algorithms and simulation techniques that are based on a novel and rigorous mathematical approach and that are designed for efficiency on modern high-performance computing platforms.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Predictive modeling of a subcritical pulverized-coal power plant for optimization: Parameter estimation, validation, and application

As renewable power generation deployment increases, fossil fuel plants are increasingly required to operate more flexibly. Many coal-fired power plants were originally designed to operate at base load and do not operate optimally at partial load. Predictive first-principles plant-wide models can be employed to identify opportunities for flexibility improvements and diagnose low-load operating issues. This paper describes the application of the Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES) to model and optimize flexible power plant operations. The key benefits of using IDAES are that it provides an open-source, fully equation-oriented modeling framework for efficient modular model construction, reuse, and customization, together with a mathematical optimization framework leveraging powerful, state-of-the-art solvers. The process systems engineering workflow from predictive process simulation to parameter estimation, model validation, and plant optimization is applicable to a variety of existing and next-generation energy systems as well as other chemical and environmental processes. Here, to demonstrate this capability, a physics-based, steady-state model was developed to improve full- and part-load performance of the Escalante Generating Station, a 245 MWe (net) subcritical pulverized coal-fired power plant owned and operated by Tri-State Generation and Transmission Association. Specifically, sixty-nine model parameters were simultaneously estimated from several months of operating data enabling prediction of flow rates, temperatures, pressures, and steam quality throughout the plant. The validated model was leveraged by Escalante to reduce the minimum operating load from 90 MW to 50 MW by diagnosing a low-load water-hammer issue, enabling coal usage and emissions reductions during periods of low power demand. Additionally, opportunities for heat rate reduction (i.e., efficiency improvement) through a steeper sliding-pressure approach to load-following and optimization of other boiler operating variables were also identified and quantified. For example, a potential efficiency improvement of 0.7 percentage points was observed at half-load operation.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

An Online Search Method for Representative Risky Fault Chains Based on Reinforcement Learning and Knowledge Transfer

In the analysis of cascading outages and blackouts in power systems, risky cascading fault chains should be accurately identified in order to do further block or alleviate blackouts. However, the huge computational burden makes online analysis difficult. In this paper, an online search method for representative risky fault chains based on reinforcement learning and knowledge transfer is proposed. This method aims at promoting efficiency by exploiting similarities of adjacent power flow snapshots in operations. After the “representative risky fault chain” is defined, a framework of tree search based on Markov Decision Process and Q-learning is constructed. The knowledge in past runs is accumulated offline and then applied online, with a mechanism of knowledge transition and extension. The proposed learning based approach is verified on an illustrative 39-bus system with different loading levels, and simulations are carried out on a realworld 1000-bus power grid in China to show the effectiveness and efficiency of the proposed approach.

Blackout↗
DOE OSTI2021

Hybrid Analytics Solution to Improve Coal Power Plant Operations

This project focused on developing advanced methods for thermal performance monitoring of a coal-fueled power plant. The specific goal was to develop and demonstrate a new thermal performance monitoring approach using a hybrid model that integrates a physics-based heat balance model with a machine learning-based pattern recognition model. The hybrid model enables increased accuracy and scope of the thermal analysis and an improved ability to monitor and detect changes in plant operation. This new approach takes full advantage of the individual model capabilities and creates an important new set of capabilities not previously possible using the two types of models separately. Using the heat balance model, a rich set of derived parameters (virtual sensors) are calculated from the measured plant operating data at each time point. The combined measured and derived data values are used by machine learning algorithms to create pattern recognition models over the range of normal unit operation. To create the monitoring models, historical data from normal operation of the plant is first processed by the heat balance model to compute the derived parameter data. The result is a greatly expanded set of normal operating data that can be used as input to create the pattern recognition model. Once the models are calibrated for normal operation, the hybrid model is suitable for use in continuous online monitoring. During online monitoring, new plant operating data is processed first by the heat balance model and then by the pattern recognition model. Results from the pattern recognition model quantify the deviation of each measured or derived parameter from its expected value in normal operation. The hybrid models can detect abnormal changes in plant operating data with very high accuracy and sensitivity. When abnormal behavior is detected, alerts are generated automatically for evaluation by the plant monitoring staff. The new hybrid solution product was developed and verified in the performance of the project. The hybrid solution was tested first in a simulation environment that mimicked the plant data systems and infrastructure used by U.S. power generating plants and utilities. The hybrid solution was then deployed for real-time, online monitoring of an operating coal-fueled power plant at a field test site. Field testing demonstrated that all hybrid solution development objectives were accomplished. The project work was based on combining the capabilities of two existing software products to create the new hybrid solution product. One of these was the existing MapEx® heat balance product and the other was the existing SureSense® advanced pattern recognition product. Each of these separate products was assessed to be at a Technology Readiness Level (TRL) of 9 at the start of the effort. The hybrid solution product was assessed to be at a TRL of 2 at the start of the project based on early feasibility work by the project team. At completion of the field testing performed in the project, the hybrid solution product was assessed to be at a TRL of 7. The project team expects that the hybrid solution product will be deployed commercially and will achieve a TRL of 9 within one year after completion of the project.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Non-Stationary Power System Forced Oscillation Analysis using Synchrosqueezing Transform

Non-stationary forced oscillations (FOs) have been observed in power system operations. However, most detection methods assume that the frequency of FOs is stationary. In this paper, we present a methodology for the analysis of nonstationary FOs. Firstly, Fourier synchrosqueezing transform (FSST) is used to provide a concentrated time-frequency representation of the signals that allows identification and retrieval of non-stationary signal components. To continue, the Dissipating Energy Flow (DEF) method is applied to the extracted components to locate the source of forced oscillations. The methodology is tested using simulated as well as real PMU data. In conclusion, the results show that the proposed FSST-based signal decomposition provides a systematic framework for the application of DEF Method to non-stationary FOs.

42 ENGINEERING↗
NASA NTRS2007

Progress in Technology Validation of the Next Ion Propulsion System

The NASA's Evolutionary Xenon Thruster (NEXT) ion propulsion system has been in advanced technology development under the NASA In-Space Propulsion Technology project. The highest fidelity hardware planned has now been completed by the government/industry team, including a flight prototype model (PM) thruster, an engineering model (EM) power processing unit, EM propellant management assemblies, a breadboard gimbal, and control unit simulators. Subsystem and system level technology validation testing is in progress. To achieve the objective Technology Readiness Level 6, environmental testing is being conducted to qualification levels in ground facilities simulating the space environment. Additional tests have been conducted to characterize the performance range and life capability of the NEXT thruster. This paper presents the status and results of technology validation testing accomplished to date, the validated subsystem and system capabilities, and the plans for completion of this phase of NEXT development.

Benson, Scott W.↗
NASA NTRS2008

Technology Readiness of the NEXT Ion Propulsion System

The NASA's Evolutionary Xenon Thruster (NEXT) ion propulsion system has been in advanced technology development under the NASA In-Space Propulsion Technology project. The highest fidelity hardware planned has now been completed by the government/industry team, including: a flight prototype model (PM) thruster, an engineering model (EM) power processing unit, EM propellant management assemblies, a breadboard gimbal, and control unit simulators. Subsystem and system level technology validation testing is in progress. To achieve the objective Technology Readiness Level 6, environmental testing is being conducted to qualification levels in ground facilities simulating the space environment. Additional tests have been conducted to characterize the performance range and life capability of the NEXT thruster. This paper presents the status and results of technology validation testing accomplished to date, the validated subsystem and system capabilities, and the plans for completion of this phase of NEXT development. The next round of competed planetary science mission announcements of opportunity, and directed mission decisions, are anticipated to occur in 2008 and 2009. Progress to date, and the success of on-going technology validation, indicate that the NEXT ion propulsion system will be a primary candidate for mission consideration in these upcoming opportunities.

Benson, Scott W.↗
NASA NTRS2018

The SPACE Computer Code for Analyzing the International Space Station Electrical Power System: Past, Present, and Future

The System Power Analysis for Capability Evaluation (SPACE) computer code was initially developed by NASA in 1988 to assess the Space Station Freedom electric power system and later adapted to support contractor electrical power system capability analyses for the International Space Station (ISS). Over time, the code has supported many efforts such as ISS redesign activities in the early 1990s, assessment of time-phased loads against power system operating limits for future ISS assembly flights (including Certification of Flight Readiness reviews by the ISS program office), and determining the optimum solar array gimbal positions while respecting keep-out zones which minimize both solar array contamination and structural loads. The code has been validated by comparisons with ISS on-orbit data in multiple validation episodes. Recent updates to the code include the incorporation of a Lithium-Ion battery model in addition to the Nickel Hydrogen battery model and modifications to the solar array degradation model to better match on-orbit test results. SPACE has also been extended beyond the ISS to include modeling of the Orion Multi-Purpose Crew Vehicle electrical power system (SPACE-MPCV) and Mars Surface Electrical Power Systems (MSEPS). Portions of SPACE were integrated with a trajectory code to form a Solar Electric Propulsion Simulation (SEPSim), which can be used for analyzing solar electric propulsion missions. In addition, SPACE methods and subroutines have been adapted to a multitude of other projects. This paper summarizes the initial code development and subsequent code utilization in the context of the overall ISS program development and on-orbit operations. Recent updates and results from the code are discussed, including preliminary analyses for the Orion power system.

Electrical Power System↗
DOE OSTI2024

Regional Power System Black Start with Run-of-river Hydropower Plant and Battery Energy Storage

Battery energy storage systems (BESSs) are an important asset for power systems with high integration levels of renewable energy, and they can be controlled to provide various critical services to the power grid. This paper presents the real-world experience of using a megawatt-scale BESS with grid-following (GFL) and grid-forming (GFM) controls and a run-of-river (ROR) hydropower plant to restore a regional power system. To demonstrate this, we carry out power-hardware-in-the-loop experiments integrating an actual GFL- or GFM-controlled BESS and a load bank. Both the simulation and experimental results presented in this paper show the different roles of GFL- or GFM-controlled BESS in power system black starts. The results provide further insight for system operators on how GFL- or GFM-controlled BESS can enhance grid stability and how an ROR hydropower plant can be converted into a black-start-capable unit with the support of a small-capacity BESS. The results show that an ROR hydropower plant combined with a BESS has the potential of becoming one of enabling elements to perform bottom-up black-start schemes as opposed to conventional bottom-down method, thus enhancing the system resiliency and robustness.

24 POWER TRANSMISSION AND DISTRIBUTION↗