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At least 55 records · Page 3

Bifurcation Analysis of DC Electric Power Systems for Deep Space Exploration Spacecraft

Electric power system reliability is a crucial factor in the application of both manned and unmanned spacecraft that could alter the success of space exploration missions. Understanding the behavior of these electric systems is essential to determine the safe operating conditions, and subsequently, prevent undesired conditions which may cause system-wide blackouts, leaving the spacecraft in a vulnerable position. This study will use bifurcation analysis to determine the behavior of DC spacecraft electric power systems and identify the major causes of voltage instability.

Bifurcation Analysis

Isotope heat source simulator for testing of space power systems

A reliable isotope heat source simulator was designed for use in a Brayton power system. This simulator is composed of an electrically heated tungsten wire which is wound around a boron nitride core and enclosed in a graphite jacket. Simulator testing was performed at the expected operating temperature of the Brayton power system. Endurance testing for 5012 hours was followed by cycling the simulator temperature. The integrity of this simulator was maintained throughout testing. Alumina beads served as a diffusion barrier to prevent interaction between the tungsten heater and boron nitride core. The simulator was designed to maintain a surface temperature of 1311 to 1366 K (1900 to 2000 F) with a power input of approximately 400 watts. The design concept and the materials used in the simulator make possible man different geometries. This flexibility increases its potential use.

Prok, G. M.

Two-stage Stochastic Generalized Disjunctive Programming (GDP) Model for Proactive Planning and Reactive Operations of Resilient Power Systems under Disruptions

In this work, we propose a Generalized Disjunctive Programming (GDP) model that optimizes both long-term capacity planning (such as the number and size of dispatchable/renewable generators, batteries, and transmission lines) and hourly operation (such as on/off schedules of dispatchable generators, power output from each generator, and power flow) to maximize power system reliability while minimizing total cost and CO2 emissions.

Cho, Seolhee

Measurement Adequacy for Monitoring Data Center Oscillations

Artificial intelligence (AI) training data centers with periodic load profiles can induce sustained grid oscillations across a wide frequency range, making accurate monitoring essential for reliable power system operation. This report evaluates the adequacy of existing measurement systems for monitoring such oscillations, focusing on phasor measurement units (PMUs) and point-on-wave (POW) measurement systems. The analysis shows that while PMUs are highly effective for monitoring low-frequency electromechanical oscillations, they have inherent limitations in accurately representing higher-frequency oscillations due to constraints imposed by reporting rates and the bandwidth of phasor estimation filters. Even when configured with higher reporting rates, the filtering inherent in the phasor estimation process can significantly attenuate oscillation magnitudes, potentially leading to underestimation of oscillatory behavior. This has important implications for compliance and performance monitoring of large loads. To address the limitations associated with PMU-based monitoring, the report examines the use of high-resolution POW measurements, which can capture oscillations across a broader frequency range. However, continuous POW monitoring introduces practical challenges related to large data volumes, communication bandwidth, and real-time data processing. For this reason, the report also discusses emerging approaches that use POW measurements as a complementary capability alongside PMUs to improve observability of oscillations from large data center loads.

47 OTHER INSTRUMENTATION

The use of plasma ashers and Monte Carlo modeling for the projection of atomic oxygen durability of protected polymers in low Earth orbit

The results of ground laboratory and in-space exposure of polymeric materials to atomic oxygen has enabled the development of a Monte Carlo computational model which simulates the oxidation processes of both environments. The cost effective projection of long-term low-Earth-orbital durability of protected polymeric materials such as SiO(x)-coated polyimide Kapton photovoltaic array blankets will require ground-based testing to assure power system reliability. Although silicon dioxide thin film protective coatings can greatly extend the useful life of polymeric materials in ground-based testing, the projection of in-space durability based on these results can be made more reliable through the use of modeling which simulates the mechanistic properties of atomic oxygen interaction, and replicates test results in both environments. Techniques to project long-term performance of protected materials, such as the Space Station Freedom solar array blankets, are developed based on ground laboratory experiments, in-space experiments, and computational modeling.

Banks, Bruce A.

Advance Power Technology Experiment for the Starshine 3 Satellite

The Starshine 3 satellite will carry several power technology demonstrations. Since Starshine 3 is primarily a passive experiment and does not need electrical power to successfully complete its mission, the requirement for a highly reliable power system is greatly reduced. This creates an excellent opportunity to test new power technologies. Several government and commercial interests have teamed up to provide Starshine 3 with a small power system using state-of-the-art components. Starshine 3 will also fly novel integrated microelectronic power supplies (IWS) for evaluation.

Jenkins, Phillip

Advance Power Technology Demonstration on Starshine 3

The Starshine 3 satellite will carry several power technology demonstrations. Since Starshine 3 is primarily a passive experiment and does not need electrical power to successfully complete its mission, the requirement for a highly reliable power system is greatly reduced. This creates an excellent opportunity to test new power technologies. Several government and commercial interests have teamed up to provide Starshine 3 with a small power system using state-of-the-art components. Starshine 3 will also fly novel integrated microelectronic power supplies (IMPS) for evaluation.

Jenkins, Phillip

LAF-Net: A Deep Residual and Cross-Attention Framework for Day-Ahead Load Forecasting: Preprint

Accurate day-ahead load forecasting is essential for reliable power system operations and market efficiency. System operators such as the Midcontinent Independent System Operator (MISO) rely on forecasts from multiple vendors, yet combining them effectively remains a persistent challenge due to vendor-specific biases. This paper presents a novel LSTM-Attention Fusion Network with Error Representation (LAF-Net) that enhances day-ahead hourly load forecasting through deep residual learning and multi-modal cross-attention. The proposed model builds a historical error memory from past vendor performance and dynamically queries it with future hour context to generate adaptive, hour-specific trust weights for each vendor. A bounded residual correction further refines forecasts by mitigating systematic and temporally localized errors. Tested on real MISO LBA data with multi-vendor forecasts, LAF-Net consistently outperforms the best vendor baseline across all 38 LBAs, achieving more than a 40% reduction in system-level mean absolute error (MAE) during peak load hours relative to the best vendor baseline.

24 POWER TRANSMISSION AND DISTRIBUTION

Reliability models for Space Station power system

This paper presents a methodology for the reliability evaluation of Space Station power system. The two options considered are the photovoltaic system and the solar dynamic system. Reliability models for both of these options are described along with the methodology for calculating the reliability indices.

Singh, C.

Space Station Freedom power - A reliability, availability, and maintainability assessment of the proposed Space Station Freedom electric power system

A preliminary reliability, availability, and maintainability (RAM) analysis of the proposed Space Station Freedom electric power system (EPS) was performed using the unit reliability, availability, and maintainability (UNIRAM) analysis methodology. Orbital replacement units (ORUs) having the most significant impact on EPS availability measures were identified. Also, the sensitivity of the EPS to variations in ORU RAM data was evaluated for each ORU. Estimates were made of average EPS power output levels and availability of power to the core area of the space station. The results of assessments of the availability of EPS power and power to load distribution points in the space stations are given. Some highlights of continuing studies being performed to understand EPS availability considerations are presented.

Turnquist, S. R.

Three approaches to reliability analysis

It is noted that current reliability analysis tools differ not only in their solution techniques, but also in their approach to model abstraction. The analyst must be satisfied with the constraints that are intrinsic to any combination of solution technique and model abstraction. To get a better idea of the nature of these constraints, three reliability analysis tools (HARP, ASSIST/SURE, and CAME) were used to model portions of the Integrated Airframe/Propulsion Control System architecture. When presented with the example problem, all three tools failed to produce correct results. In all cases, either the tool or the model had to be modified. It is suggested that most of the difficulty is rooted in the large model size and long computational times which are characteristic of Markov model solutions.

Mesh networks

Deep Reinforcement Learning Based Control of Wind Turbines for Fast Frequency Response

In order to fulfill vital auxiliary grid services, such as load regulation, spin and non-spin reserve provision, and frequency support during emergencies, there is often a requirement for certain wind farms to operate in de-loaded modes. Leveraging the swift response capabilities of wind farms, this study demonstrates that reserving power in de-loaded modes can significantly enhance power grid stability and reliability during system contingencies. Controlling wind farms optimally for frequency support is intricate due to the nonlinearity of models and controllers and the complexity of wind farm interactions with power systems. Here, to address this challenge, this paper introduces a novel approach that integrates wind turbines into reinforcement learning-based solutions for frequency response. This innovative methodology utilizes the state-of-the-art reinforcement learning algorithm known as the surrogate-gradient-based evolutionary strategy. The proposed learning-based algorithm provides continuous control of wind farm output to rapidly stabilize system frequency and prevent unnecessary trips of under-frequency load shedding relays. To facilitate efficient training, parallel computing techniques are employed. The proposed methodology is evaluated on a modified IEEE-39 bus system, and simulation results reveal its efficacy in reliably supporting power system frequency and preventing the need for unnecessary load shedding.

Gao, Wei [Argonne National Laboratory (ANL), Argon

Reliability Issues in Stirling Radioisotope Power Systems

Stirling power conversion is a potential candidate for use in a Radioisotope Power System (RPS) for space science missions because it offers a multifold increase in the conversion efficiency of heat to electric power and reduced requirement of radioactive material. Reliability of an RPS that utilizes Stirling power conversion technology is important in order to ascertain long term successful performance. Owing to long life time requirement (14 years), it is difficult to perform long-term tests that encompass all the uncertainties involved in the design variables of components and subsystems comprising the RPS. The requirement for uninterrupted performance reliability and related issues are discussed, and some of the critical areas of concern are identified. An overview of the current on-going efforts to understand component life, design variables at the component and system levels, and related sources and nature of uncertainties are also discussed. Current status of the 110 watt Stirling Radioisotope Generator (SRG110) reliability efforts is described. Additionally, an approach showing the use of past experience on other successfully used power systems to develop a reliability plan for the SRG110 design is outlined.

Shah, Ashwin R.

Reliability Issues in Stirling Radioisotope Power Systems

Stirling power conversion is a potential candidate for use in a Radioisotope Power System (RPS) for space science missions because it offers a multifold increase in the conversion efficiency of heat to electric power and reduced requirement of radioactive material. Reliability of an RPS that utilizes Stirling power conversion technology is important in order to ascertain long term successful performance. Owing to long life time requirement (14 years), it is difficult to perform long-term tests that encompass all the uncertainties involved in the design variables of components and subsystems comprising the RPS. The requirement for uninterrupted performance reliability and related issues are discussed, and some of the critical areas of concern are identified. An overview of the current on-going efforts to understand component life, design variables at the component and system levels, and related sources and nature of uncertainties are also discussed. Current status of the 110 watt Stirling Radioisotope Generator (SRG110) reliability efforts is described. Additionally, an approach showing the use of past experience on other successfully used power systems to develop a reliability plan for the SRG110 design is outlined.

Schreiber, Jeffrey

Fault Diagnosis of Power Systems Using Intelligent Systems

The power system operator's need for a reliable power delivery system calls for a real-time or near-real-time Al-based fault diagnosis tool. Such a tool will allow NASA ground controllers to re-establish a normal or near-normal degraded operating state of the EPS (a DC power system) for Space Station Alpha by isolating the faulted branches and loads of the system. And after isolation, re-energizing those branches and loads that have been found not to have any faults in them. A proposed solution involves using the Fault Diagnosis Intelligent System (FDIS) to perform near-real time fault diagnosis of Alpha's EPS by downloading power transient telemetry at fault-time from onboard data loggers. The FDIS uses an ANN clustering algorithm augmented with a wavelet transform feature extractor. This combination enables this system to perform pattern recognition of the power transient signatures to diagnose the fault type and its location down to the orbital replaceable unit. FDIS has been tested using a simulation of the LeRC Testbed Space Station Freedom configuration including the topology from the DDCU's to the electrical loads attached to the TPDU's. FDIS will work in conjunction with the Power Management Load Scheduler to determine what the state of the system was at the time of the fault condition. This information is used to activate the appropriate diagnostic section, and to refine if necessary the solution obtained. In the latter case, if the FDIS reports back that it is equally likely that the faulty device as 'start tracker #1' and 'time generation unit,' then based on a priori knowledge of the system's state, the refined solution would be 'star tracker #1' located in cabinet ITAS2. It is concluded from the present studies that artificial intelligence diagnostic abilities are improved with the addition of the wavelet transform, and that when such a system such as FDIS is coupled to the Power Management Load Scheduler, a faulty device can be located and isolated from the rest of the system. The benefit of these studies provides NASA with the ability to quickly restore the operating status of a space station from a critical state to a safe degraded mode, thereby saving costs in experimentation rescheduling, fault diagnostics, and prevention of loss-of-life.

Momoh, James A.