Results for “power system data” — Page 16

NASA NTRS2001

Low Temperature Testing of a Radiation Hardened CMOS 8-Bit Flash Analog-to-Digital (A/D) Converter

Power processing electronic systems, data acquiring probes, and signal conditioning circuits are required to operate reliably under harsh environments in many of NASA:s missions. The environment of the space mission as well as the operational requirements of some of the electronic systems, such as infrared-based satellite or telescopic observation stations where cryogenics are involved, dictate the utilization of electronics that can operate efficiently and reliably at low temperatures. In this work, radiation-hard CMOS 8-bit flash A/D converters were characterized in terms of voltage conversion and offset in the temperature range of +25 to -190 C. Static and dynamic supply currents, ladder resistance, and gain and offset errors were also obtained in the temperature range of +125 to -190 C. The effect of thermal cycling on these properties for a total of ten cycles between +80 and - 150 C was also determined. The experimental procedure along with the data obtained are reported and discussed in this paper.

Gerber, Scott S.↗

NASA NTRS2009

The Fastrack Suborbital Platform for Microgravity Applications

The FASTRACK suborbital experiment platform has been developed to provide a capability for utilizing 2.5-5 minute microgravity flight opportunities anticipated from the commercial suborbital fleet (currently in development) for science investigations, technology development and hardware testing. It also provides "express rack" functionality to deliver payloads to ISS. FASTRACK fits within a 24" x 24" x 36" (61 cm x 61 cm x 91.4 cm) envelope and is capable of supporting either two single Middeck Locker Equivalents (MLE) or one double MLE configuration. Its overall mass is 300 lbs (136 kg), of which 160 lbs (72 kg) is reserved for experiments. FASTRACK operates using 28 VDC power or batteries. A support drawer located at the bottom of the structure contains all ancillary electrical equipment (including batteries, a conditioned power system and a data collection system) as well as a front panel that contains all switches (including remote cut-off), breakers and warning LEDs.

Levine, H. G.↗

NASA NTRS2016

Launch Pad in a Box

NASA Kennedy Space Center (KSC) is developing a new deployable launch system capability to support a small class of launch vehicles for NASA and commercial space companies to test and launch their vehicles. The deployable launch pad concept was first demonstrated on a smaller scale at KSC in 2012 in support of NASA Johnson Space Center's Morpheus Lander Project. The main objective of the Morpheus Project was to test a prototype planetary lander as a vertical takeoff and landing test-bed for advanced spacecraft technologies using a hazard field that KSC had constructed at the Shuttle Landing Facility (SLF). A steel pad for launch or landing was constructed using a modular design that allowed it to be reconfigurable and expandable. A steel flame trench was designed as an optional module that could be easily inserted in place of any modular steel plate component. The concept of a transportable modular launch and landing pad may also be applicable to planetary surfaces where the effects of rocket exhaust plume on surface regolith is problematic for hardware on the surface that may either be damaged by direct impact of high speed dust particles, or impaired by the accumulation of dust (e.g., solar array panels and thermal radiators). During the Morpheus free flight campaign in 2013-14, KSC performed two studies related to rocket plume effects. One study compared four different thermal ablatives that were applied to the interior of a steel flame trench that KSC had designed and built. The second study monitored the erosion of a concrete landing pad following each landing of the Morpheus vehicle on the same pad located in the hazard field. All surfaces of a portable flame trench that could be directly exposed to hot gas during launch of the Morpheus vehicle were coated with four types of ablatives. All ablative products had been tested by NASA KSC and/or the manufacturer. The ablative thicknesses were measured periodically following the twelve Morpheus free flight tests. The thermal energy from the Morpheus rocket exhaust plume was only found to be sufficient to cause appreciable ablation of one of the four ablatives that were tested. The rocket exhaust plume did cause spalling of concrete during each descent and landing on a landing pad in the hazard field. The Extended Abstract ASE Earth and Space Conference April, 2016 - Orlando, FL concrete surface was laser scanned following each Morpheus landing, and the total volume of spalled concrete that eroded between the first and final landings of the Morpheus Project's test campaign was estimated. This paper will also describe a new deployable launch system (DLS) capability that is being developed at KSC and was publicly announced in May 2015 (KSC Partnerships, 2015). The DLS is a set of multi-user Ground Support Equipment that will be used to test and launch small class launch vehicles. The system is comprised of four main elements: the Launch Stand, the Flame Deflector, the Pad Apron and the KAMAG transporter. The system elements are designed to be deployed at launch or test sites within the KSC/CCAFS boundaries. The DLS is intended to be used together with the Fluid and Electrical System of the Universal Propellant Servicing Systems and Mobile Power Data and Communications Unit.

Ablatives Testing↗

NASA NTRS2016

Launch Pad in a Box

NASA Kennedy Space Center (KSC) is developing a new deployable launch system capability to support a small class of launch vehicles for NASA and commercial space companies to test and launch their vehicles. The deployable launch pad concept was first demonstrated on a smaller scale at KSC in 2012 in support of NASA Johnson Space Center's Morpheus Lander Project. The main objective of the Morpheus Project was to test a prototype planetary lander as a vertical takeoff and landing test-bed for advanced spacecraft technologies using a hazard field that KSC had constructed at the Shuttle Landing Facility (SLF). A steel pad for launch or landing was constructed using a modular design that allowed it to be reconfigurable and expandable. A steel flame trench was designed as an optional module that could be easily inserted in place of any modular steel plate component. The concept of a transportable modular launch and landing pad may also be applicable to planetary surfaces where the effects of rocket exhaust plume on surface regolith is problematic for hardware on the surface that may either be damaged by direct impact of high speed dust particles, or impaired by the accumulation of dust (e.g., solar array panels and thermal radiators). During the Morpheus free flight campaign in 2013-14, KSC performed two studies related to rocket plume effects. One study compared four different thermal ablatives that were applied to the interior of a steel flame trench that KSC had designed and built. The second study monitored the erosion of a concrete landing pad following each landing of the Morpheus vehicle on the same pad located in the hazard field. All surfaces of a portable flame trench that could be directly exposed to hot gas during launch of the Morpheus vehicle were coated with four types of ablatives. All ablative products had been tested by NASA KSC and/or the manufacturer. The ablative thicknesses were measured periodically following the twelve Morpheus free flight tests. The thermal energy from the Morpheus rocket exhaust plume was only found to be sufficient to cause appreciable ablation of one of the four ablatives that were tested. The rocket exhaust plume did cause spalling of concrete during each descent and landing on a landing pad in the hazard field. The Extended Abstract ASE Earth and Space Conference April, 2016 - Orlando, FL concrete surface was laser scanned following each Morpheus landing, and the total volume of spalled concrete that eroded between the first and final landings of the Morpheus Project's test campaign was estimated. This paper will also describe a new deployable launch system (DLS) capability that is being developed at KSC and was publicly announced in May 2015 (KSC Partnerships, 2015). The DLS is a set of multi-user Ground Support Equipment that will be used to test and launch small class launch vehicles. The system is comprised of four main elements: the Launch Stand, the Flame Deflector, the Pad Apron and the KAMAG transporter. The system elements are designed to be deployed at launch or test sites within the KSC/CCAFS boundaries. The DLS is intended to be used together with the Fluid and Electrical System of the Universal Propellant Servicing Systems and Mobile Power Data and Communications Unit

Mobile Launch Pad Development↗

DOE OSTI2023

Feeder Power Disaggregation: A Data-Efficient Matrix Completion Approach

This paper presents a data-driven algorithm for the feeder power disaggregation problem in distribution systems. Leveraging spatio-temporal power patterns in residential homes, residential power is discomposed into three components: sparse-switching loads, periodic loads, and photovoltaic (PV) generation, which are characterized through the design of two sparse matrices and a low-rank matrix. The matrix completion process is data-efficient because of the matrix sparsity and low rankness, along with the use of power system models. The proposed approach is tested using real-world residential data set on a 33-bus distribution system, demonstrating accurate power disaggregation with efficient matrix completion.

distribution system↗

NASA NTRS1971

Reconfigurable G and C computer study for space station use. Volume 7, appendix 5 - D-200 computer family. Appendix 6 - System error analysis. Appendix 7 - Reliability derivation for candidate computers. Appendix 8 - Power converter design data. Appendix 9 - Data transmission medium design Final report, 29 Dec. 1969 - 31 Jan. 1971

D-200 computer family, system error analysis, reliability derivation, and power converter design for reconfigurable guidance and control computer - Vol. 7

Source record↗

DOE OSTI2021

Data source authentication of synchrophasor measurement devices based on 1D-CNN and GRU

Synchrophasor measurement devices (SMDs) have been widely deployed to support real-time monitoring and control of power systems. In the meantime, data spoofing has emerged in recent years. Therefore, it is of great importance to study data authentication algorithms for detecting and defending the data spoofing effectively. Here, a one-dimensional convolutional neural network (1D-CNN) is utilized to extract temporal signatures hidden in frequency, voltage angle and amplitude data; then the gated recurrent unit (GRU) employs these temporal signatures for data source authentication. In case studies, the performances of different algorithms are tested in large-scale power systems with numerous SMDs for the first time, and comparisons among different algorithms show that the proposed algorithm can achieve a higher accuracy of data source authentication with a shorter time window.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Spatiotemporal Super-Resolution with Generative Machine Learning for Creating Renewable Energy Resource Data Under Climate Change Scenarios

As we plan for a future with higher penetrations of renewables and increasing electrification, it becomes more important to understand how the electricity grid will operate under a variety of weather events. We must also consider that the weather our future grid will experience will be different and possibly more extreme than the historical weather that we have extensive data for. We can use data from global climate models (GCMs) to help understand how our climate may change over the next several decades, but there is often a significant gap between the low-resolution GCM data and the high-resolution weather data required to study power systems under specific weather events. Therefore, our objective in this work is to develop tools that can bridge this gap by using low-resolution GCM data to create realistic high-resolution weather datasets that can be used to study renewable energy generation and electricity demand. To accomplish this objective, we have developed a set of generative machine learning models that can rapidly downscale GCM daily average output data at an approximate grid resolution of 100km to hourly data at an approximate 4 km grid resolution. The models can be used to create high resolution data from nearly any GCM included in the Coupled Model Intercomparison Project (CMIP) Phase 5 or 6. Our methods include all datasets regularly used to study the integration of wind and solar power plants as well as changes in electricity demand due to heating and cooling loads. These models and datasets enable power systems modelers to study climate change-influenced weather events and their impact on the grid. We have downscaled and validated wind, solar, temperature, and humidity data with very promising results. The generative machine learning methods are computationally efficient and produce data that has similar statistical characteristics to current state-of-the-art historical datasets. We have trained initial generative models and produced an initial dataset collectively referred to as Sup3rCC: Super-Resolved Renewable Energy Resource Data with Climate Change Impacts. The data covers a (mostly) historical period from 2015-2025 and a future period from 2050-2059. We have also taken hypothetical high-electrification load data and scaled the heating and cooling loads with respect to the 2050-2059 high-resolution Sup3rCC meteorology. The results show how future levels of renewable energy generation and electrified load may be impacted by climate change, setting the stage for capacity expansion models to consider a dynamic climate through model years.

climate change↗

DOE OSTI2020

Adaptive Neuro Fuzzy Inference System for Cyber-Intrusion Detection in a Smart Grid

The evolution of the power grid has brought increasing deployment of advance metering infrastructure, penetration of intelligent electronic devices, and integration of physical power system components with information and communications technologies. With the fast-expanding connectivity, cyber vulnerabilities arise due to the use of internet-based communication systems. These systems are targets of cyber-intrusions which attempt to disturb the normal power system functions. Traditional intrusion detection algorithms have been developed without an explicit model of the cyber components. In this paper, an algorithm to detect false data injections in the power system is proposed considering both cyber and physical models of the power system. The algorithm is based on an Adaptive Neuro Fuzzy Inference System (ANFIS) which collects information from state variables of the cyber-physical system to meet the performance requirements of the grid. Simulations of the proposed approach using the IEEE 13-bus test system validate the effectiveness of this artificial intelligence-based algorithm.

Adaptive Neuro Fuzzy Inference System (ANFIS), cyb↗

DOE OSTI2021

Extracting Resilience Metrics From Distribution Utility Data Using Outage and Restore Process Statistics

Resilience curves track the accumulation and restoration of outages during an event on an electric distribution grid. We show that a resilience curve generated from utility data can always be decomposed into an outage process and a restore process and that these processes generally overlap in time. We use many events in real utility data to characterize the statistics of these processes, and derive formulas based on these statistics for resilience metrics such as restore duration, customer hours not served, and outage and restore rates. The formulas express the mean value of these metrics as a function of the number of outages in the event. We also give a formula for the variability of restore duration, which allows us to predict a maximum restore duration with 95% confidence. Overall, we give a simple and general way to decompose resilience curves into outage and restore processes and then show how to use these processes to extract resilience metrics from standard distribution system data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2015

DebriSat: The New Hypervelocity Impact Test for Satellite Breakup Fragment Characterization

To replicate a hyper-velocity fragmentation event using modern-day spacecraft materials and construction techniques to better improve the existing DoD and NASA breakup models: DebriSat is intended to be representative of modern LEO satellites. Major design decisions were reviewed and approved by Aerospace subject matter experts from different disciplines. DebriSat includes 7 major subsystems. Attitude determination and control system (ADCS), command and data handling (C&DH), electrical power system (EPS), payload, propulsion, telemetry tracking and command (TT&C), and thermal management. To reduce cost, most components are emulated based on existing design of flight hardware and fabricated with the same materials. center dotA key laboratory-based test, Satellite Orbital debris Characterization Impact Test (SOCIT), supporting the development of the DoD and NASA satellite breakup models was conducted at AEDC in 1992. Breakup models based on SOCIT have supported many applications and matched on-orbit events reasonably well over the years.

Cowardin, Heather↗

NASA NTRS2015

Characterization of Orbital Debris Via Hyper-Velocity Ground-Based Tests

To replicate a hyper-velocity fragmentation event using modern-day spacecraft materials and construction techniques to better improve the existing DoD and NASA breakup models. DebriSat is intended to be representative of modern LEO satellites.Major design decisions were reviewed and approved by Aerospace subject matter experts from different disciplines. DebriSat includes 7 major subsystems. Attitude determination and control system (ADCS), command and data handling (C&DH), electrical power system (EPS), payload, propulsion, telemetry tracking and command (TT&C), and thermal management. To reduce cost, most components are emulated based on existing design of flight hardware and fabricated with the same materials. A key laboratory-based test, Satellite Orbital debris Characterization Impact Test (SOCIT), supporting the development of the DoD and NASA satellite breakup models was conducted at AEDC in 1992 .Breakup models based on SOCIT have supported many applications and matched on-orbit events reasonably well over the years.

Cowardin, Heather↗

DOE OSTI2023

A Reproducible Validation of Algorithms for Estimating Array Tilt and Azimuth from Photovoltaic Power Time Series

In this research, we assess the viability of four different, publicly available algorithms for estimating the azimuth and tilt parameters of solar photovoltaic systems using only the associated AC power time series data and site latitude-longitude coordinates. In this work, we curated a benchmarking data set of 44 fixed-tilt systems, comprising 275 measured AC power inverter data streams, with known azimuth and tilt parameters. Additionally, we isolated test cases in the data set with real- world issues, including shading and clipping, to determine how algorithm performance varies based on the presence of these phenomena. Using this data set for benchmarking, we evaluated the estimated vs. actual system characteristics for each algorithm, as well as the associated algorithm execution time using a standardized benchmarking process. The two highest performing algorithms were the Solar Data Tools and the PVWatts 5- based methods, which both achieved a median absolute error of approximately 5 and 1 degrees for azimuth and tilt, respectively. During run time analysis, the SDT method was approximately 5 times faster than the PVWatts 5-based method, with the median execution time for a stream varying between 6 and 8 seconds vs. a median run time of 31 seconds for the PVWatts 5-based method.

azimuth↗

DOE OSTI2023

A Reproducible Validation of Algorithms for Estimating Array Tilt and Azimuth from Photovoltaic Power Time Series

In this research, we assess the viability of four different, publicly available algorithms for estimating the azimuth and tilt parameters of solar photovoltaic systems using only the associated AC power time series data and site latitude-longitude coordinates. In this work, we curated a benchmarking data set of 44 fixed-tilt systems, comprising 275 measured AC power inverter data streams, with known azimuth and tilt parameters. Additionally, we isolated test cases in the data set with real-world issues, including shading and clipping, to determine how algorithm performance varies based on the presence of these phenomena. Using this data set for benchmarking, we evaluated the estimated vs. actual system characteristics for each algorithm, as well as the associated algorithm execution time using a standardized benchmarking process. The two highest performing algorithms were the Solar Data Tools and the PVWatts 5-based methods, which both achieved a median absolute error of approximately 5 and 1 degrees for azimuth and tilt, respectively. During run time analysis, the SDT method was approximately 5 times faster than the PVWatts 5-based method, with the median execution time for a stream varying between 6 and 8 seconds vs. a median run time of 31 seconds for the PVWatts 5-based method.

algorithm validation↗

DOE OSTI2025

Selection of Global Climate Model Data for Downscaling With Generative Machine Learning and Use in the Power Planning for Alignment of Climate and Energy Systems Project

The range of results from climate models and scenarios is important to the understanding of uncertainty in power planning analysis. A U.S. Department of Energy-funded analytic project called Power Planning for Alignment of Climate and Energy Systems is developing data and analytic methods to reflect the effects of climate change on key variables for power system planning, as part of the Grid Modernization Lab Consortium. This project will select and prepare global climate model results for use in power system planning models. A related report (Evaluation of Global Climate Models for Use in Energy Analysis) assesses the performance of various global climate models from the Coupled Model Intercomparison Project Phase 6 data archive for their historical skill with respect to energy system performance and for their future projections under multiple climate change scenarios. Building from that report, we describe the selection of a climate scenario (Shared Socioeconomic Pathway [SSP] 2-4.5) and five climate models: TaiESM1, EC-Earth3-CC, GFDL-CM4, EC-Earth3-Veg, and MPI-ESM1-2-HR. We describe the model selection criteria, which were based on the quality of the match between model results under historical conditions and on the representation of the range of future values for several variables. These results will be downscaled via an open-source generative machine learning method called Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Survey of Use Cases and Scenarios on the Open Energy Data Initiative Solar Systems Integration (OEDI SI) Platform

The Open Energy Data Initiative Solar Systems Integration (OEDI SI) Data and Modeling Platform offers a comprehensive set of use cases tailored for power systems analysis. Each use case is centered around a specific power system analysis problem, supported by composite input data and reference algorithms. These composite input datasets are meticulously assembled using OEDI SI's data preprocessing tools, which integrate raw data from various sources. The primary objectives of the OEDI SI Platform include facilitating access to composite input data through widely accepted input/output formats and verified results. This accessibility enables power system network researchers and developers to validate their algorithms and showcase their applications' capabilities to the broader community. Moreover, the platform strives to promote reproducible, robust, replicable, and generalizable solar systems integration research.

14 SOLAR ENERGY↗

DOE OSTI2025

Optimization-Based Data-Driven Approach for Detecting Fault Location in Power Systems

In grids with large penetration of converterinterfaced resources (CIRs), measurements of voltage, current, and line parameters can fluctuate significantly during fault conditions. These fluctuations, combined with complex network topologies and extensive system branching, make accurate fault location challenging. Faults, such as short circuits, can cause prolonged outages with serious socio-economic impacts, highlighting the need for rapid fault identification to minimize downtime. However, current fault detection methods—such as relays and digital fault recorders—often relay information too slowly, impeding swift corrective action. Given the limited availability of high-resolution phasor measurement units, this paper introduces an optimization-based observer to estimate fault locations, grid line parameters, and voltages using local CIR measurements. To preserve the confidentiality of CIRs and enhance estimation accuracy, this study uses a black-box model of CIRs. This bottom-up, event-driven approach can enhances protection and control systems through optimized and real-time fault detection. Simulation results show that the optimization-based data-driven observer can accurately detect fault locations and estimate grid states and parameters, providing valuable insights for utilities and operators in grid applications.

Subedi, Sunil [ORNL] (ORCID:000000034069090X)↗

DOE OSTI2023

Online Output-Based Inertia Estimation of Modern Power Systems

The overall inertia of modern power systems is drastically impacted by the penetration level of converter-based resources (CBRs). The intermittent output of CBRs and their dependence on the weather conditions affirm the need for a realtime inertia estimation approach. This can help the transmission system operators(TSOs) to be continuously aware of the changes in the system inertia and to take suitable control actions. This paper is a step forward to a totally data-driven framework for power system inertia estimation using the available measurements from the phasor measurement units (PMUs). This inertia estimation is done based on the spectral analysis of the so-called Koopman linear operator. Koopman operator considers the relationship between the system's inertia and its dynamical response to slight disturbances in the load. Simulation results show that Koopman operator can approximate the system behavior in a reconstructed linear space hence inertia constant is estimated accurately.

data-driven↗