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At least 811 records · Page 45

All sources NASA NTRS DOE OSTI

NASA NTRS2020

Electrical Modeling and Thermal Analysis Toolbox (EMTAT) User’s Guide

A simulation toolbox has been developed to model the electrical portions of Electrified Aircraft Propulsion (EAP) systems, including self-heating of electrical systems. Dynamic models of EAP systems often include turbomachinery, an electrical power system, and a thermal management system. These portions of the propulsion system can operate on timescales covering six orders of magnitude, which poses a challenging modeling task. Assumptions and approximations are made in an effort to capture the dynamics relevant to engine, electrical system, and thermal system interactions, while still allowing for fast simulations. These assumptions and approximations enable the electrical component models to run at the time scale of the turbomachinery, neglecting the very high frequency electrical dynamics, while demonstrating representative behavior of the end-to-end system. Thus the models execute in an acceptable time frame for what would otherwise be an extremely stiff simulation. The resulting simulations of EAP systems are appropriate for system-level control design and analysis. The objective of this User's Guide is to present an overview of the usage of the Electrical Modeling and Thermal Analysis Toolbox (EMTAT). It will describe some of the approximations made to accommodate rapid execution, and some of the design tools that allow matching the model to component specifications. This paper will describe the basic usage of the software toolbox, and also provide an example of EAP system modeling using EMTAT.

Mark E. Bell↗

DOE OSTI2023

Deep Reinforcement Learning for Resilient Power and Energy Systems: Progress, Prospects, and Future Avenues

In recent years, deep reinforcement learning (DRL) has garnered substantial attention in the context of enhancing resilience in power and energy systems. Resilience, characterized by the ability to withstand, absorb, and quickly recover from natural disasters and human-induced disruptions, has become paramount in ensuring the stability and dependability of critical infrastructure. This comprehensive review delves into the latest advancements and applications of DRL in enhancing the resilience of power and energy systems, highlighting significant contributions and key insights. The exploration commences with a concise elucidation of the fundamental principles of DRL, highlighting the intricate interplay among reinforcement learning (RL), deep learning, and the emergence of DRL. Furthermore, it categorizes and describes various DRL algorithms, laying a robust foundation for comprehending the applicability of DRL. The linkage between DRL and power system resilience is forged through a systematic classification of DRL applications into five pivotal dimensions: dynamic response, recovery and restoration, energy management and control, communications and cybersecurity, and resilience planning and metrics development. This structured categorization facilitates a methodical exploration of how DRL methodologies can effectively tackle critical challenges within the domain of power and energy system resilience. The review meticulously examines the inherent challenges and limitations entailed in integrating DRL into power and energy system resilience, shedding light on practical challenges and potential pitfalls. Additionally, it offers insights into promising avenues for future research, with the aim of inspiring innovative solutions and further progress in this vital domain.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2008

Low Power, Wide Dynamic Range Carbon Nanotube Vacuum Gauges

This slide presentation presents carbon nanotube vacuum pressure sensor gauges that operate at low power and exhibit a wide-dynamic range based on microelectromechanical systems (MEMS) technology. The fabrication facility, and the formation process are shown. Pressure sensitivity was found to increase rapidly as the bias power was increased. In addition, by etching part of the thermal SiO2 beneath the tubes and minimizing heat conduction through the substrate, pressure sensitivity was extended toward lower pressures. Results are compared to a conventional thin film meander resistor, which was fabricated and whose pressure response was also measured for comparative purposes.

JEOL E-beam aligner↗

DOE OSTI2020

Data-Driven Security Assessment of Power Grids Based on Machine Learning Approach: Preprint

Data-driven security assessment provides key indicators on power system stability using simulations on scheduling models, as opposed to dynamic simulations that are more time-consuming. This paper investigates data-driven security assessment of power grids based on machine learning. Multivariate random forest regression is used as the machine learning algorithm due to its high robustness to the input data. Three stability issues are analyzed using the proposed machine learning tool, including transient stability, frequency stability and small signal stability. The estimation values from machine learning tool are compared with those from dynamic simulations. Results show that the proposed machine learning tool can effectively predict the stability margins for the three stability metrics.

14 SOLAR ENERGY↗

DOE OSTI2025

Resilient Distributed Frequency Regulation of Renewable Generators under Communication Interruptions

Modern power systems (MPSs) face significant challenges due to the high penetration of renewable energy sources (RESs) and new types of loads such as electric vehicles (EVs). Traditional load frequency control (LFC) methods struggle with the intermittent, stochastic nature of RESs, the near-zero inertia of power-electronics-based generators, and the mobility of controllable loads and battery systems. This paper introduces a novel resilient distributed frequency regulation method to address these issues. The proposed method employs a state space model to represent the dynamic behavior of participating power sources while accounting for stochastic switching processes to model structural and parameter variations caused by disruptions such as generator connection/disconnection, communication interruptions, and physical faults. By integrating these dynamic and stochastic components, the method treats power grids as a comprehensive stochastic hybrid system. Our method enhances conventional frequency control by incorporating local stability control, neighborhood control decoupling, and coordination feedback. Theoretical analyses establish the stability, convergence, and resilience of the proposed method, and its effectiveness is validated through case studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2021

Revolutionary Vertical Lift Technology (RVLT) Side-By-Side Hybrid Concept Vehicle Powertrain Dynamic Model

The Side-by-Side (SBS) Hybrid is one of several Revolutionary Vertical Lift Technology (RVLT) concept aircraft identified by NASA to investigate Urban Air Mobility (UAM) requirements. This paper presents a dynamic model of the SBS Hybrid powertrain built using the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) and the Electrical Modeling and Thermal Analysis Toolbox (EMTAT). The model consists of the rotors, electrical power system, and turboshaft engines connected through freewheeling clutches, gearboxes, and multiple shafts. This research effort models the complex behavior of the powertrain, including the operation of the freewheeling clutches and electrical power system at the simulation time scale of the shaft dynamics. Several simulations highlight the key features present in the model and demonstrate its operation.

Powertrain↗

NASA NTRS2021

Revolutionary Vertical Lift Technology (RVLT) Side-By-Side Hybrid Concept Vehicle Powertrain Dynamic Model

powertrain↗

DOE OSTI2020

A Nonlinear Regression Method for Composite Protection Modeling of Induction Motor Loads

Protection equipment are used to prevent damages to induction motor loads by isolating those from the power network in the event of severe faults. Modeling the response of induction motor loads and their protection is vital for power system planning and operation, especially in understanding system's response moments after a fault has occurred. This article proposes an optimization based framework to generate composite protection models for commercial building motor loads. Introducing a mathematical abstraction, the task of finding a suitable (simplified) model of the composite protection scheme is formulated as a nonlinear regression problem. Numerical examples are provided to illustrate the application of the framework.

Kundu, Soumya↗

NASA NTRS1989

Evolutionary growth for Space Station Freedom electrical power system

Over an operational lifetime of at least 30 yr, Space Station Freedom will encounter increased space station user requirements and advancing technologies. The space station electrical power system is designed with the flexibility to accommodate these emerging technologies and expert systems and is being designed with the necessary software hooks and hardware scars to accommodate increased growth demand. The electrical power system is planned to grow from the initial 75 kW up to 300 kW. The Phase 1 station will utilize photovoltaic arrays to produce the electrical power; however, for growth to 300 kW, solar dynamic power modules will be utilized. Pairs of 25 kW solar dynamic power modules will be added to the station to reach the power growth level. The addition of solar dynamic power in the growth phase places constraints in the initial space station systems such as guidance navigation and control, external thermal, truss structural stiffness, computational capabilities and storage which must be planned-in in order to facilitate the addition of the solar dynamic modules.

Marshall, Matthew F.↗

NASA NTRS1989

Evolutionary growth for Space Station Freedom electrical power system

Over an operational lifetime of at least 30 yr, Space Station Freedom will encounter increased Space Station user requirements and advancing technologies. The Space Station electrical power system is designed with the flexibility to accommodate these emerging technologies and expert systems and is being designed with the necessary software hooks and hardware scars to accommodate increased growth demand. The electrical power system is planned to grow from the initial 75 kW up to 300 kW. The Phase 1 station will utilize photovoltaic arrays to produce the electrical power; however, for growth to 300 kW, solar dynamic power modules will be utilized. Pairs of 25 kW solar dynamic power modules will be added to the station to reach the power growth level. The addition of solar dynamic power in the growth phase places constraints in the initial Space Station systems such as guidance, navigation, and control, external thermal, truss structural stiffness, computational capabilities and storage, which must be planned-in, in order to facilitate the addition of the solar dynamic modules.

Marshall, Matthew Fisk↗

NASA NTRSDate not supplied

NTAC Augmented Nuclear and Advanced Propulsion

Currently, there are two types of nuclear propulsion: Nuclear Thermal Propulsion (NTP) and Nuclear Electric Propulsion (NEP). Common to both types, a nuclear reactor generates heat energy to raise the temperature of propellant, or the generated heat energy is converted into electric power. The electricity generated powers propulsion systems, such as a Hall thruster, magnetoplasma dynamic (MPD) thruster, or variable specific impulse magnetoplasma rocket (VASIMR). Customarily, only the thermal energy output from nuclear reaction is considered for NTP and NEP systems. However, the nuclear fission reaction can also generate ~7 MeV of prompt gamma rays. Therefore, most designers of NTP and NEP systems incorporate safety features to shield against this radiation. An optimized design approach would be to integrate a Nuclear Thermionic Avalanche Cell (NTAC) within the NTP or NEP structure for converting this radiation energy into additional electric power, while also shielding gamma rays. Consequently, this study addresses several combinations of NTP and NEP structures with NTAC devices in order to achieve that goal.

NTAC↗

DOE OSTI2023

Data-Driven Scalable Emulation of Hydropower Using Real-Time Hardware-in-the-Loop

This presentation covers Motivation: (1) With the increased grid integration of inverter-based resources, hydropower plays a crucial role in maintaining the bulk power system reliability and resilience; and (2) A more dynamic response and new control designs are required to meet the grid requirements. To evaluate any modification, control-prototyping, performance validation and de-risking grid integration of hydropower, a high-fidelity environment is required. Also covers Objectives: (1) To develop data-driven emulation of hydropower using hardware-in-the-loop for different size, types of hydro plants; and (2) To characterize hardware and obtain accurate dynamic response for shaft speed, torque, and power. Provide a mechanical power interface with emulated dynamics of a hydro-turbine shaft that can be coupled to electrical generators for mechanical and electrical PHIL.

electrical↗

DOE OSTI2021

Analysis of Lobe Power Calculator and Indication System with Physics and Cycle Based Models

The Advanced Test Reactor (ATR) at INL measures reactor power through two methods, thermal and Nitrogen-16 (N-16) activity. Water power calculator (WPC) is a thermal power system that measures flow and temperature to determine the thermal quadrant powers. The N-16 system utilizes a beta chamber detector that outputs reactivity levels to calculate lobe power through an algorithm called lobe power calculation and indication system (LPCIS). The LPCIS utilizes the N-16 system and the WPC system to determine reactor core power levels. The WPC provides accurate calculations of quadrant and total reactor thermal power. With the use of WPC measurements, thermal-to-N-16 (T2N) power ratios are produced to determine if the two indication systems agree on core power. Relative magnitude equations are used to utilize N-16 coefficients and multipliers to improve the indications of the LPCIS. This is crucial for maintaining safety limits. Currently, the LPCIS system uses linear equations and matrices to calculate lobe power through multipliers and coefficients. Advancements in technology and system upgrades have assisted system engineers at INL with the objective to reach a more dynamic system. In return the system demonstrates an increase in the accuracy of power reading while maintaining safety margins. The new proposed coefficient and multiple method implements a cycle specific, and a physics-based model intended for changing coefficients during operation. This calibration experiment focuses on power splitting, outer shim and neck shim, as well as fuel burning into the RDAS weighting factors. Results show that the Physics learning method yields a smaller error margin inside of the desired power range for the data set 166-A. This proved true for both constrained and unconstrained testing. This is most likely due to the physics data fitting approach that resulted in favorable coefficients and multipliers for 166-A. Continuing to improve the physics-based model will help improve the power accuracy of the LPCIS system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2009

Diagnosis and Reconfiguration using Bayesian Networks: An Electrical Power System Case Study

Automated diagnosis and reconfiguration are important computational techniques that aim to minimize human intervention in autonomous systems. In this paper, we develop novel techniques and models in the context of diagnosis and reconfiguration reasoning using causal Bayesian networks (BNs). We take as starting point a successful diagnostic approach, using a static BN developed for a real-world electrical power system. We discuss in this paper the extension of this diagnostic approach along two dimensions, namely: (i) from a static BN to a dynamic BN; and (ii) from a diagnostic task to a reconfiguration task. More specifically, we discuss the auto-generation of a dynamic Bayesian network from a static Bayesian network. In addition, we discuss subtle, but important, differences between Bayesian networks when used for diagnosis versus reconfiguration. We discuss a novel reconfiguration agent, which models a system causally, including effects of actions through time, using a dynamic Bayesian network. Though the techniques we discuss are general, we demonstrate them in the context of electrical power systems (EPSs) for aircraft and spacecraft. EPSs are vital subsystems on-board aircraft and spacecraft, and many incidents and accidents of these vehicles have been attributed to EPS failures. We discuss a case study that provides initial but promising results for our approach in the setting of electrical power systems.

Knox, W. Bradley↗

NASA NTRS2002

A Scalable, Out-of-Band Diagnostics Architecture for International Space Station Systems Support

The computational infrastructure of the International Space Station (ISS) is a dynamic system that supports multiple vehicle subsystems such as Caution and Warning, Electrical Power Systems and Command and Data Handling (C&DH), as well as scientific payloads of varying size and complexity. The dynamic nature of the ISS configuration coupled with the increased demand for payload support places a significant burden on the inherently resource constrained computational infrastructure of the ISS. Onboard system diagnostics applications are hosted on computers that are elements of the avionics network while ground-based diagnostic applications receive only a subset of available telemetry, down-linked via S-band communications. In this paper we propose a scalable, out-of-band diagnostics architecture for ISS systems support that uses a read-only connection for C&DH data acquisition, which provides a lower cost of deployment and maintenance (versus a higher criticality readwrite connection). The diagnostics processing burden is off-loaded from the avionics network to elements of the on-board LAN that have a lower overall cost of operation and increased computational capacity. A superset of diagnostic data, richer in content than the configured telemetry, is made available to Advanced Diagnostic System (ADS) clients running on wireless handheld devices, affording the crew greater mobility for troubleshooting and providing improved insight into vehicle state. The superset of diagnostic data is made available to the ground in near real-time via an out-of band downlink, providing a high level of fidelity between vehicle state and test, training and operational facilities on the ground.

Fletcher, Daryl P.↗

DOE OSTI2021

Renewable energy integration and system operation challenge: control and optimization of millions of devices

The electric power infrastructure, originally designed and built on large-scale power plants, is evolving into a more resilient power generation and delivery system in which millions of smaller units of distributed energy generation resources units will be installed in sub-transmission and distribution networks. In order to control, manage and optimize the future grid, a hierarchical design is presented in this chapter which enables the distributed control on grid edge while inheriting the existing centralized control structure. This layered design of large-scale power system operation and control uses the following principle: reactive power control is treated as a primary control for voltage stability, and the real power control is primarily a grid-level control but can also be a supplementary control for voltage support in the case of insufficient reactive power control capacity. For the purpose of active control and operation at the distribution level, a recursive power network model is derived from nodal injection and branch power flow models. Based on the model, the proposed algorithms of hierarchical control, grid-edge inference and dynamic hosting allowance are developed and presented for multi-level controlled operation. And, a co-simulation architecture of integrated T&D system is presented to validate and demonstrate the feasibility and scalability of proposed algorithms.

Xu, Ying↗

NASA NTRS1994

Controllability of Free-piston Stirling Engine/linear Alternator Driving a Dynamic Load

This paper presents the dynamic behavior of a Free-Piston Stirling Engine/linear alternator (FPSE/LA) driving a single-phase fractional horse-power induction motor. The controllability and dynamic stability of the system are discussed by means of sensitivity effects of variations in system parameters, engine controller, operating conditions, and mechanical loading on the induction motor. The approach used expands on a combined mechanical and thermodynamic formulation employed in a previous paper. The application of state-space technique and frequency domain analysis enhances understanding of the dynamic interactions. Engine-alternator parametric sensitivity studies, similar to those of the previous paper, are summarized. Detailed discussions are provided for parametric variations which relate to the engine controller and system operating conditions. The results suggest that the controllability of a FPSE-based power system is enhanced by proper operating conditions and built-in controls.

Kankam, M. David↗

NASA NTRS1998

Investigation and Feasibility Assessment of TOPAZ-2 Derivations for Space Power Applications

The ability to provide continuous power at significant levels is of utmost importance for many space missions, from simple satellite operations to manned Mars missions. One of the main problems faced in delivering solar or chemical space power in the tens of kW range, is the increasingly massive nature of the power source and the costs associated with its launch, operation and maintenance. A national program had been initiated to study the feasibility of using certain advanced technologies in developing an efficient lightweight space power source. The starting point for these studies has been the Russian TOPAZ-2 space reactor system, with the ultimate goal to aid in the development of a TOPAZ-2 derivative which will be ready for flight by the year 2000. The main objective of this project has been to perform feasibility assessment and trade studies which would allow the development of an advanced space nuclear power system based on the in-core thermionic fuel element technology currently used in the Russian TOPAZ-2 reactor. Two of the important considerations in developing the concept are: (1) compliance of the current TOPAZ-2 and of any advanced designs with U.S. nuclear safety expectations, and (2) compliance of the design with the seven years lifetime requirement. The project was composed of two major phases. The initial phase of the project has concentrated on understanding the TOPAZ-2 thermionic reactor in sufficient detail to allow several follow-on tasks. The primary interest during this first phase has been given on identifying the potential of the TOPAZ-2 design for further improvements. The second phase of the project has focused on the feasibility of a TOPAZ-2 system capable of delivering 30-50 kWe. Towards the elimination of single-point failures in the load voltage regulation system an active voltage regulator has been designed to be used in conjunction with the available shunt load voltage regulator. The possible use of a dual-loop, model-based adaptive control system for load-following in the TOPAZ-2 has also been investigated. The objective of this fault-tolerant, autonomous control system is to deliver the demanded electric power at the desired voltage level, by appropriately manipulating the neutron power through the control drums. As a result, sufficient thermal power is produced to meet the required demand in the presence of dynamically changing system operating conditions and potential sensor failures. The designed controller is proposed for use in combination with the currently available shunt regulators, or as a back-up controller when other means of power system control, including some of the sensors, fail.

Parlos, Alexander G.↗