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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Autonomous power system brassboard

The Autonomous Power System (APS) brassboard is a 20 kHz power distribution system which has been developed at NASA Lewis Research Center, Cleveland, Ohio. The brassboard exists to provide a realistic hardware platform capable of testing artificially intelligent (AI) software. The brassboard's power circuit topology is based upon a Power Distribution Control Unit (PDCU), which is a subset of an advanced development 20 kHz electrical power system (EPS) testbed, originally designed for Space Station Freedom (SSF). The APS program is designed to demonstrate the application of intelligent software as a fault detection, isolation, and recovery methodology for space power systems. This report discusses both the hardware and software elements used to construct the present configuration of the brassboard. The brassboard power components are described. These include the solid-state switches (herein referred to as switchgear), transformers, sources, and loads. Closely linked to this power portion of the brassboard is the first level of embedded control. Hardware used to implement this control and its associated software is discussed. An Ada software program, developed by Lewis Research Center's Space Station Freedom Directorate for their 20 kHz testbed, is used to control the brassboard's switchgear, as well as monitor key brassboard parameters through sensors located within these switches. The Ada code is downloaded from a PC/AT, and is resident within the 8086 microprocessor-based embedded controllers. The PC/AT is also used for smart terminal emulation, capable of controlling the switchgear as well as displaying data from them. Intelligent control is provided through use of a T1 Explorer and the Autonomous Power Expert (APEX) LISP software. Real-time load scheduling is implemented through use of a 'C' program-based scheduling engine. The methods of communication between these computers and the brassboard are explored. In order to evaluate the features of both the brassboard hardware and intelligent controlling software, fault circuits have been developed and integrated as part of the brassboard. A description of these fault circuits and their function is included. The brassboard has become an extremely useful test facility, promoting artificial intelligence (AI) applications for power distribution systems. However, there are elements of the brassboard which could be enhanced, thus improving system performance. Modifications and enhancements to improve the brassboard's operation are discussed.

Merolla, Anthony↗
DOE OSTI2022

Adaptive Fault Detection Based on Neural Networks and Multiple Sampling Points for Distribution Networks and Microgrids

Smart networks such as microgrid (MG) and active distribution networks (ADN) have been recently playing an important role in power system operation. The design and implementation of appropriate protection systems for such networks must be addressed, which imposes new technical challenges. This paper presents the implementation and validation aspects of an adaptive fault detection strategy based on neural networks (NNs) and multiple sampling points for ADN and MG. The solution is implemented on an edge device. Artificial NNs are used to derive a data-driven model that uses only local measurements to detect fault states of the network without the need for communication infrastructure. Multiple sampling points are used to derive a data-driven model, which allows the generalization considering the implementation in physical systems. The adaptive fault detector model is implemented on a Jetson Nano system, which is a single-board computer (SBC) with a small Graphic Processing Unit (GPU) intended to run machine learning loads at the edge. The proposed method is tested in a physical, real-life, low-voltage network located at Universidad del Norte, Colombia. This testing network is based on the IEEE-13 Node Test Feeder scaled down to 220 V. The validation in a simulation environment shows the accuracy and dependability above 99.6%, while the real-time tests show the accuracy and dependability of 95.5% and 100%, respectively. Without hard-to-derive parameters, the easy-to-implement embedded model highlights the potential for real-life applications.

42 ENGINEERING↗
DOE OSTI2022

De-Energized Line Testing Interface (DELTI) Report

To guarantee the safety of power system operations, it is crucial to understand a de-energized power line’s status before restoring power. It is hypothesized that the Grid Resonance Probe (GRP) and De-Energized Line Testing Interface (DELTI) can be utilized to identify a faulted distribution line. Therefore, the project team is targeting development of a methodology to identify faulted distribution lines by using the DELTI system. In this R&D task, two field tests on Plum Island have been conducted, including DELTI tests with multiple configurations and fault scenarios. This report provides the analysis results of distribution line fault identification from the two field tests. In the remainder of this report, Section 1 is the introduction of the DELTI system, Section 2 provides the analyses of the two field tests in June and October of 2021, respectively, Section 3 discusses the existing line fault detection devices on market and how they compare to DELTI and Section 4 includes the lessons learned and recommendations for future work.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Device Access Abstractions for Resilient Information Architecture Platform for Smart Grid

An open application platform distributes the intelligence and control capability to local endpoints (or nodes) reducing total network traffic, improving speed of local actions by avoiding latency, and improving reliability by reducing dependencies on numerous devices and communication interfaces. The platform must be multi-tasking and able to host multiple applications running simultaneously. Given such a system, the core functions of power grid control systems include grid state determination, low level control, fault intelligence and reconfiguration, outage intelligence, power quality measurement, remote asset monitoring, configuration management, power and energy management (including local distributed energy resources, such as wind, solar and energy storage) can be eventually distributed. However, making this move requires extensive regression testing of systems to prove out new technologies, such as phasor measurement units (PMU). Additionally, as the complexity of the systems increase with the inclusion of new functionality (especially at the distribution and consumer levels), hidden coupling issues becomes a challenge with possible N-way interactions known and not known by device and application developers. Therefore, it is very important to provide core abstractions that ensure uniform operational semantics across such interactions. Here in this paper, we describe the pattern for abstracting device interactions we have developed for the RIAPS platform in the context of a microgrid control application we have developed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Development of a Converter-Based Transmission Line Emulator with Three-Phase Short-Circuit Fault Emulation Capability

A transmission line emulator has been developed to flexibly represent interconnected ac lines under normal operating conditions in a voltage source converter (VSC)-based power system emulation platform. As the most serious short-circuit fault condition, the three-phase short-circuit fault emulation is essential for power system studies. Here, this paper proposes a model to realize a three-phase short-circuit fault emulation at different locations along a single transmission line or one of several parallel-connected transmission lines. At the same time, a combination method is proposed to eliminate the undesired transients caused by the current reference step changes while switching between the fault state and the normal state. Experiment results verify the developed transmission line three-phase short-circuit fault emulation capability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1988

Artificial intelligence approaches in space power systems automation at Marshall Space Flight Center

Various applications of AI to spacecraft electrical power systems are described. Particular attention is given to NICBES (nickel-cadmium battery expert system which is interfaced with the Hubble Space Telescope electrical power system test bed); the SSES; the three cooperating AI systems in the Space Station module power management and distribution system test bed; and I-DARE, the intelligent data reduction expert. It is found that the utilization of AI approaches permits comprehensive fault management and dynamic rescheduling capabilities for the electrical power system.

Weeks, David J.↗
DOE OSTI2021

Reliability Barriers to Enhanced Solar PV Deployment: Selected Research Findings - State Outreach Technical Sessions

This presentation provides summaries of three reports selected from a body of work that examines potential reliability challenges related to planning future power systems with higher solar photovoltaic (PV) penetrations in the western United States. The three topics covered are 1) Power system flexibility requirements and supply; 2) Resource adequacy and the capacity credit of solar; 3) Simulating distributed energy resource responses to transmission system-level faults considering IEEE 1547 performance categories on three major WECC transmission paths. The full reports and related resources are available at the project website, https://www.westernenergyboard.org/western-interstate-energy-board/barrier-mitigation-to-enhanced-distributed-solar-photovoltaic/. This presentation is targeted toward a technical audience. A companion policy presentation provides higher-level summaries of the same material.

distributed energy resource↗
DOE OSTI2021

Reliability Barriers to Enhanced Solar PV Deployment: Selected Research Findings - State Outreach Policy Sessions

This presentation provides high-level summaries of three reports selected from a body of work that examines potential reliability challenges related to planning future power systems with higher solar photovoltaic (PV) penetrations in the western United States. The three topics covered are 1) Power system flexibility requirements and supply; 2) Resource adequacy and the capacity credit of solar; 3) Simulating distributed energy resource responses to transmission system-level faults considering IEEE 1547 performance categories on three major WECC transmission paths. The full reports and related resources are available at the project website, https://www.westernenergyboard.org/western-interstate-energy-board/barrier-mitigation-to-enhanced-distributed-solar-photovoltaic/. This presentation is targeted toward policy decision makers. A companion technical presentation provides more in-depth summaries of the same material.

distributed energy resource↗
DOE OSTI2018

The influence of power spinning and annealing temperature on microstructures and properties of Cu-Sn alloy

Highlights: • The strengthening effect of power spinning is mainly achieved by strengthening fine grains and dislocations. • Twins formed by the aggregation and overlapping of stacking faults grow and widen • In power spinning of Cu-Sn alloy, plastic deformation is primarily powered by dislocation sliding. - Abstract: Electron back scatter diffraction pattern (EBSD), metallographic microscope (OM) and transmission electron microscope (TEM) are used to analyze the microstructural state of the Cu-Sn alloy before and after power spinning and annealing. The results show that after power spinning, the α phase grains are refined and gradually evolve into small and fine α{sub II} and deformed α{sub III} crystal grains, with an average grain size of about 2.2 μm. Work hardening results in massive network-like subgrain boundaries distributed in power spinning microstructure. Annealing at 400 °C contributes to the formation of dislocation cells and stacking faults, and high-angle grain boundaries (HABS) start to migrate and slide. After the formation of less defective equiaxed grains at 500 °C, twins continue to grow and widen based through continuous accumulation of stacking faults. Further testing of mechanical properties reveals that power spinning is conducive to the improvement of mechanical properties of Cu-Sn alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2018

GMLC Southeast Regional Consortium: Technology Driven Improvements to Power Grid Resiliency

Recognizing that electric grid challenges can differ by geographical regions across the US, the Department of Energy (DOE) created a pioneer regional partnership to provide technical assistance to stakeholders facing grid modernization challenges. The southeast regional teams will transfer technologies developed under DOE auspices to stakeholders for testing, evaluation, and market validation. Regional members will help define critical challenges and pave the way for transition of technologies to the commercial sector. Using the depth and expertise at Oak Ridge National Laboratory, Savannah River National Laboratory, University of Tennessee’s CURENT, CAPER and the Clemson 20 MVA Electrical Grid Laboratory—along with critical industry partners, such as Duke Energy, TVA, Southern Company, EPB, and Santee Cooper—the Southeast Regional Consortium team will conduct collaborative research to advance the state of the grid in the Southeast region and improve power system resiliency to enhance responsiveness, enable faster restoration of power, and increase distributed energy resource (DER) concentrations. This report provides details of the technical research and demonstration projects accomplished by Oak Ridge National Laboratory (ORNL) as part of the Southeast Regional Consortium. Specifically, ORNL analyzed the application of optical current and voltage measurements impedance relays which would enable step distance protection to be deployed on distribution systems. This would improve the precision of determining the geographic location of faults, increase network topology flexibility, and allow bi-directional power flow. Next, ORNL deployed time sensitive networking technology on the EPB fiberoptic data network to study the impact of increased sensor traffic on existing supervisory control and data acquisition data. The deterministic latency and high bandwidth were demonstrated by remotely inspecting a substation using a drone with full HD streaming video operated at the EPB Control Center. Finally, a new application-based communication and control system developed at ORNL call CSEISMIC was tested for future deployment on the EPB Control Center microgrid using a hardware-in-the-loop testbed that was also developed at ORNL. The controller was able to successfully optimize ancillary service when the microgrid is connected to the distribution network. The seamless islanding, resynchronization, and reconnection of the microgrid was also demonstrated through the testing.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

1-D Convolutional Graph Convolutional Networks for Fault Detection in Distributed Energy Systems

This paper presents a 1-D convolutional and graph convolutional networks for fault detection in microgrids. The combination of 1-D convolutional neural networks (1D-CNN) and graph convolutional networks (GCN) helps extract both spatial-temporal correlations from the voltage measurements in microgrids. The fault detection scheme includes fault event detection, fault type and phase classification, and fault location. There are five neural network model training to handle these tasks. Transfer learning and fine-tuning are applied to reduce training efforts. The combined 1-D convolutional and graph convolutional networks (1D-CGCN) is compared with the traditional ANN structure on the Potsdam 13-bus microgrid dataset. The accuracy of 99.5%, 98.4%, 99.2%, and 95.5% are achieved in fault event detection, fault type classification, fault phase identification, and fault location respectively. The detailed confusion matrices of fault type and fault phase classification are provided for validation.

deep neural network↗
DOE OSTI2022

Performance and power modeling and prediction using MuMMI and 10 machine learning methods

Energy-efficient scientific applications require insight into how high performance computing system features impact the applications' power and performance. This insight can result from the development of performance and power models. Here, in this article, we use the modeling and prediction tool MuMMI (Multiple Metrics Modeling Infrastructure) and 10 machine learning methods to model and predict performance and power consumption and compare their prediction error rates. We use an algorithm-based fault-tolerant linear algebra code and a multilevel checkpointing fault-tolerant heat distribution code to conduct our modeling and prediction study on the Cray XC40 Theta and IBM BG/Q Mira at Argonne National Laboratory and the Intel Haswell cluster Shepard at Sandia National Laboratories. Our experimental results show that the prediction error rates in performance and power using MuMMI are less than 10% for most cases. By utilizing the models for runtime, node power, CPU power, and memory power, we identify the most significant performance counters for potential application optimizations, and we predict theoretical outcomes of the optimizations. Based on two collected datasets, we analyze and compare the prediction accuracy in performance and power consumption using MuMMI and 10 machine learning methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A Power-Hardware-in-the-Loop (PHIL) Evaluation of Service Restoration With Networked Microgrids

This paper describes the power-hardware-in-the- loop (PHIL) evaluation of the feasibility of service restoration solutions determined by the PowerModelsONM.jl tool. This tool incorporates microgrids and the networking of microgrids into its determination of an optimal service restoration solution. The paper presents PHIL simulation results for a case study based on a real distribution feeder with multiple microgrids, showcas- ing the effectiveness of networked microgrids in aiding system restoration after an outage. The study leverages high-fidelity, real- time electromagnetic transient models to ensure accuracy in the simulation results. This work is the final output from the Resilient Operation of Networked Microgrids (RONM) project funded by the U.S. Department of Energy Office of Electricity Microgrid Program and led by Los Alamos National Laboratory. RONM focused on the application of PowerModelsONM.jl to enhance the resilience of distribution systems.

fault location isolation and service restoration (↗
DOE OSTI2023

Novel Hybrid Current Limiter for Grid-Forming Inverter Control During Unbalanced Faults: Preprint

Grid-forming (GFM) inverter controls have illustrated many desirable features to enable bulk integration of renewable sources into the future power grid. However, the performance of GFM inverters during unbalanced faults remains under-explored. In this paper, a novel current-limiting method is proposed for GFM inverters to handle unbalanced fault conditions while providing voltage support to the main grid. The proposed current limiter combines concepts of dynamic virtual-impedance and current-reference saturation limiting, all built-up in the stationary reference frame to achieve improved current-limiting performance under unbalanced load/fault conditions. System-wide full-order transient simulations with multiple GFM inverters demonstrate the potential of the method and benchmark the performance against state-of-the-art current limiters. Simulation results portray improved voltage balancing performance of the proposed method compared to both current-reference saturation and virtual-impedance limiting.

controller anti windup↗
DOE OSTI2019

Coherency-Based Detection Algorithm for Synchrophasor Cyberattacks

The wide area monitoring system (WAMS) is critical for power system situational awareness, but represents a growing cybersecurity vulnerability. Malicious adversaries may seek to compromise one or more PMUs in order to effect control decisions that unnecessarily disrupt typical grid operations. One example of a particularly pernicious attack vector is the spoofing or replaying of a fault event using one or more compromised PMUs. This work documents the development and validation of a coherency-based cyberattack detection algorithm that integrates a sliding-window singular value decomposition (SVD) with physics-based partitioning analysis to achieve accurate classification of events. Special consideration is given to discerning a sophisticated fault-replay or fault spoofing attack from actual faults. A software-based cybersecurity testbed has been developed for rigorous testing of the algorithm. The algorithm is further validated using simulated synchrophasor datasets obtained from a MinniWECC 63-bus test system. Results show that the algorithm can successfully detect fault-replay attacks even when over half of the PMUs are compromised.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1975

Research study on multi-KW-DC distribution system

A detailed definition of the HVDC test facility and the equipment required to implement the test program are provided. The basic elements of the test facility are illustrated, and consist of: the power source, conventional and digital supervision and control equipment, power distribution harness and simulated loads. The regulated dc power supplies provide steady-state power up to 36 KW at 120 VDC. Power for simulated line faults will be obtained from two banks of 90 ampere-hour lead-acid batteries. The relative merits of conventional and multiplexed power control will be demonstrated by the Supervision and Monitor Unit (SMU) and the Automatically Controlled Electrical Systems (ACES) hardware. The distribution harness is supported by a metal duct which is bonded to all component structures and functions as the system ground plane. The load banks contain passive resistance and reactance loads, solid state power controllers and active pulse width modulated loads. The HVDC test facility is designed to simulate a power distribution system for large aerospace vehicles.

Berkery, E. A.↗
DOE OSTI2024

IBR Black Model Lessons Learned (C45)

Blackbox modelling for SC analysis is a possible solution. Accuracy can be acceptable even without having vendor control diagrams. Blackbox modelling is not as user friendly as a generic model. Is an NDA required to share a vendor Blackbox model for SC analysis? Difference in VRT detection and injection logics. Angle rotation is not addressed. Current limitation logic during unbalanced faults is not clear.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1987

An overview of the artificial intelligence and expert systems component of RICIS

Artificial Intelligence and Expert Systems are the important component of RICIS (Research Institute and Information Systems) research program. For space applications, a number of problem areas that should be able to make good use of the above tools include: resource allocation and management, control and monitoring, environmental control and life support, power distribution, communications scheduling, orbit and attitude maintenance, redundancy management, intelligent man-machine interfaces and fault detection, isolation and recovery.

Feagin, Terry↗