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At least 685 records · Page 38

All sources NASA NTRS DOE OSTI

NASA NTRS1999

Refractive Secondary Concentrators for Solar Thermal Applications

The NASA Glenn Research Center is developing technologies that utilize solar energy for various space applications including electrical power conversion, thermal propulsion, and furnaces. Common to all of these applications is the need for highly efficient, solar concentration systems. An effort is underway to develop the innovative single crystal refractive secondary concentrator, which uses refraction and total internal reflection to efficiently concentrate and direct solar energy. The refractive secondary offers very high throughput efficiencies (greater than 90%), and when used in combination with advanced primary concentrators, enables very high concentration ratios (10,0(X) to 1) and very high temperatures (greater than 2000 K). Presented is an overview of the refractive secondary concentrator development effort at the NASA Glenn Research Center, including optical design and analysis techniques, thermal modeling capabilities, crystal materials characterization testing, optical coatings evaluation, and component testing. Also presented is a discussion of potential future activity and technical issues yet to be resolved. Much of the work performed to date has been in support of the NASA Marshall Space Flight Center's Solar Thermal Propulsion Program. The many benefits of a refractive secondary concentrator that enable efficient, high temperature thermal propulsion system designs, apply equally well to other solar applications including furnaces and power generation systems such as solar dynamics, concentrated thermal photovoltaics, and thermionics.

Wong, Wayne A.↗

NASA NTRS2001

Laser Induced Aluminum Surface Breakdown Model

Laser powered propulsion systems involve complex fluid dynamics, thermodynamics and radiative transfer processes. Based on an unstructured grid., pressure-based computational aerothermodynamics, platform, several sub-nio"'dels describing such underlying physics as laser ray tracing and focusing, thermal non-equilibrium, plasma radiation and air spark ignition have been developed. This proposed work shall extend the numerical platform and existing sub-models to include the aluminum wall surface Inverse Bremsstrahlung (113) effect from which surface ablation and free-electron generation can be initiated without relying on the air spark ignition sub-model. The following tasks will be performed to accomplish the research objectives.

Chen, Yen-Sen↗

NASA NTRS2002

Laser Induced Aluminum Surface Breakdown Model

Laser powered propulsion systems involve complex fluid dynamics, thermodynamics and radiative transfer processes. Based on an unstructured grid, pressure-based computational aerothermodynamics; platform, several sub-models describing such underlying physics as laser ray tracing and focusing, thermal non-equilibrium, plasma radiation and air spark ignition have been developed. This proposed work shall extend the numerical platform and existing sub-models to include the aluminum wall surface Inverse Bremsstrahlung (IB) effect from which surface ablation and free-electron generation can be initiated without relying on the air spark ignition sub-model. The following tasks will be performed to accomplish the research objectives.

Chen, Yen-Sen↗

DOE OSTI2022

Master State Distributed Estimator (masde)

The MSE technology provides a distributed state estimation scheme for power utilities by making it a real time dynamic system, versus the static snapshot method used today. This will allow utilities to verify power grid readings and identify false data on the communication network. The prevailing method of estimation takes all the data from the system into a single load flow equation at the utilities command center. This becomes a large algorithm that is very time consuming to solve, providing the engineers only snap shots of the system. The MFD distributes an algorithm to devises that are already installed at various locations on the power grid. This allows for much faster computer times because the algorithms contain magnitudes less data. When each distributed estimator completes its calculation, it sends the results back to the master device to check against all other distributed estimators.

Reen, DylanW.↗

DOE OSTI2022

A Data-Driven Algorithm for Enabling Delay Tolerance in Resilient Microgrid Controls Using Dynamic Mode Decomposition

The increased implementation of smart grid technologies in the power distribution grid presents unique opportunities that enable resiliency, but also brings challenges motivating needs for novel solutions and mitigation techniques. The bi-directional power and data flow allow for the grid to operate with increased resiliency, which is the ability to avoid discontinuity of service to end-use loads during extreme events. However, in applications where control of the distribution grid or microgrid relies on communication networks, the degradation of communication systems in the form of loss or high latency can cause maloperation and result in loss of end-use loads. Here this paper presents a novel framework to enable delay tolerance of centralized microgrid control schemes to mitigate communication system latency impacts and guarantee successful control action. We demonstrate the delay tolerance on a control scheme that operates a battery energy storage system (BESS) to offset the sudden loss of generation and maintain system frequency. During periods of severely degraded communication system performance, the proposed delay-tolerant algorithm compensates for the latency by utilizing a data-driven model generated at the device level using dynamic mode decomposition (DMD) to determine the performance of the communications. The DMD technique predicts the system’s frequency using device-level terminal measurements and provides updated control signals. The HELICS cosimulation platform evaluates the cyber-physical interaction of the power system model in GridLAB-D, the centralized control agent in Python, and the discrete network model in NS-3. The framework is tested and validated on the IEEE-123 node system modified to represent a networked remote microgrid model, and the results show an improvement in the dynamic performance

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Analysis of Tasks in Autonomous Systems Using the EMRALD Dynamic Risk Assessment Tool

An autonomous system refers to the system that has the power and ability for self-governance in the performance of system functions. Autonomous systems have been actively pursued in a variety of domains such as automotive, aviation, maritime, medicine, and nuclear fields. As an unmanned concept employing the highest automation level, the autonomous system basically performs most of the work in normal operations or emergency situations. However, despite advances in technology, many researchers have noted these systems still require human actions. The nature of human actions on autonomous systems is different than the human actions that are considered in existing systems. Nevertheless, only a few studies have been conducted on 1) characterizing the different types of errors and risks associated with human actions interacting with autonomous systems and 2) how to evaluate human actions in the autonomous operations. As a starting point, this study aims to investigate differences of tasks in autonomous operation compared to those in existing nuclear power plant operation using the Event Modeling Risk Assessment Using Linked Diagram (EMRALD) software. In this paper, insights aspect of human error and time are derived out and discussed based on the output of the EMRALD models.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS1978

A mechanical, thermal and electrical packaging design for a prototype power management and control system for the 30 cm mercury ion thruster

A prototype electric power management and thruster control system for a 30 cm ion thruster is described. The system meets all of the requirements necessary to operate a thruster in a fully automatic mode. Power input to the system can vary over a full two to one dynamic range (200 to 400 V) for the solar array or other power source. The power management and control system is designed to protect the thruster, the flight system and itself from arcs and is fully compatible with standard spacecraft electronics. The system is easily integrated into flight systems which can operate over a thermal environment ranging from 0.3 to 5 AU. The complete power management and control system measures 45.7 cm (18 in.) x 15.2 cm (6 in.) x 114.8 cm (45.2 in.) and weighs 36.2 kg (79.7 lb). At full power the overall efficiency of the system is estimated to be 87.4 percent. Three systems are currently being built and a full schedule of environmental and electrical testing is planned.

Sharp, G. R.↗

NASA NTRS1978

A mechanical, thermal and electrical packaging design for a prototype power management and control system for the 30 cm mercury ion thruster

A prototype Electric Power Management and Thruster Control System for a 30 cm ion thruster has been built and is ready to support a first mission application. The system meets all of the requirements necessary to operate a thruster in a fully automatic mode. Power input to the system can vary over a full two to one dynamic range (200 to 400 V) for the solar array or other power source. The Power Management and Control system is designed to protect the thruster, the flight system and itself from arcs and is fully compatible with standard spacecraft electronics. The system is designed to be easily integrated into flight systems which can operate over a thermal environment ranging from 0.3 to 5 AU. The complete Power Management and Control system measures 45.7 cm x 15.2 cm x 114.8 cm and weighs 36.2 kg. At full power the overall efficiency of the system is estimated to be 87.4 percent. Three systems are currently being built and a full schedule of environmental and electrical testing is planned.

Sharp, G. R.↗

DOE OSTI2020

Dynamic Distribution System Restoration Strategy for Resilience Enhancement: Preprint

In electric power distribution systems, distributed energy re-sources (DERs) can act as controllable power sources and support utility operators to minimize power outages after ex-treme weather events (e.g., hurricane, earthquake, wildfire) and thus help enhance the grid's resilience. Meanwhile, the influ-ences of extreme events and the capabilities of DERs are dy-namic and difficult to predict. Hence, the desired distribution system restoration strategy should be able to evolve according to real-time fault/disturbance information and the availabil-ity of DERs. In this paper, we propose a new dynamic distribu-tion system restoration strategy to enhance system resilience against potential hazards. An efficient reconfiguration algo-rithm is developed to eliminate the use of integer variables to relieve the computational burden. Model predictive control is implemented to adjust the system topology and DER opera-tion setpoints based on the updated fault information and DER forecasts. The effectiveness of the proposed restoration model in enhancing distribution system resilience is validated through an IEEE 123-bus test system. Simulation results also validate that the proposed restoration model can mitigate the occurrence of unexpected events and the fluctuations of DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Knowledge-Informed Uncertainty-Aware Machine Learning for Time Series Forecasting of Dynamical Engineered Systems

The high complexity and multiscale nature of many engineered systems—such as those in nuclear power plants—make representing and forecasting their dynamic behavior challenging. Physics-based models can be overly complex and computationally intractable, whereas machine learning (ML) tools are often data-hungry and prone to unphysical solutions. This study proposes a knowledge-informed ML-aided hybrid residual modeling approach that offers accurate and efficient time series forecasting for the operation of dynamical engineered systems. Hybrid residual modeling entails a baseline solution from domain knowledge and known physics expressions about the system dynamics integrated with an ML model to capture undiscovered information from the mismatch (i.e., residuals) between true states from measurements and baseline-predicted outputs. This study further quantifies the ML model uncertainty to provide trustworthy solutions. Real-time operational data from thermal-hydraulic flow loops of the cryogenic moderator system in Oak Ridge National Laboratory’s Spallation Neutron Source facility were used to demonstrate the potential of knowledge-informed uncertainty-aware ML in real-world applications. The state variables of the cryogenic helium loop were modeled with (1) first principles–based system identification (sysID), (2) long short-term memory (LSTM) neural network, and (3) hybrid sysID (baseline) + LSTM (residual). The superior predictive capability of the sysID+LSTM model versus stand-alone sysID and LSTM is confirmed by average performance metrics and individual data points across different prediction horizons. By creating a robust representation of the underlying physical system, the widely applicable hybrid residual modeling approach will enable the future development of digital twins for performance prediction, prognostics, and operation control.

Zhao, Xingang↗

NASA NTRSDate not supplied

Tutorial: Electrified Aircraft Propulsion Approaches for Modeling and Electrical Hardware-in-the-Loop Testing

This tutorial session outlines capabilities made available by the National Aeronautics and Space Administration for testing electrified aircraft propulsion (EAP) hardware and software prior to using turbomachinery. Removing these components from the experimentation process until necessary significantly reduces the development and testing costs and safety risks. Three facilities, the NASA Electric Aircraft Testbed (NEAT) and the Hybrid Propulsion Emulation Rig (HyPER) are unique facilities that provide the following capabilities: (i) the verification of megawatt-scale electrical and electromechanical system components at altitude, (ii) the verification of EAP control systems on sub-scale representative electromechanical architectures. The importance, operation, and specifications of each facility is described with detail. Provided examples of past testing showcase the abilities of each facility. Simple and complex methods for replicating the steady state and dynamical mechanical loading on the electrical power system are discussed

Electrified Aircraft Propulsion↗

DOE OSTI2021

Modelling a Heaving Point-Absorber with a Closed-Loop Control System Using the DualSPHysics Code

The present work addresses the need for an efficient, versatile, accurate and open-source numerical tool to be used during the design stage of wave energy converters (WECs). The device considered here is the heaving point-absorber developed and tested by Sandia National Laboratories. The smoothed particle hydrodynamics (SPH) method, as implemented in DualSPHysics, is proposed since its meshless approach presents some important advantages when simulating floating devices. The dynamics of the power take-off system are also modelled by coupling DualSPHysics with the multi-physics library Project Chrono. A satisfactory matching between experimental and numerical results is obtained for: (i) the heave response of the device when forced via its actuator; (ii) the vertical forces acting on the fixed device under regular waves and; (iii) the heave response of the WEC under the action of both regular waves and the actuator force. This proves the ability of the numerical approach proposed to simulate accurately the fluid–structure interaction along with the WEC’s closed-loop control system. In addition, radiation models built from the experimental and WAMIT results are compared with DualSPHysics by plotting the intrinsic impedance in the frequency domain, showing that the SPH method can be also employed for system identification.

42 ENGINEERING↗

NASA NTRSDate not supplied

Stirling Power Conversion for Lunar Applications

NASA is developing Stirling power convertors for use in nuclear power systems that would provide electricity to users on the lunar surface. NASA’s Radioisotope Power Systems (RPS) Program is maturing advanced dynamic convertor technologies that would increase the efficiency beyond the heritage systems for missions to the Moon and other solar system bodies of interest. Development efforts have focus on Stirling and Brayton designs that meet reliability and robustness requirements for operation in the lunar environment. GRC is also maturing low power convertors in the range of 1-40 watts to power micro-spacecraft or a network of distributed probes and include basic demonstration of in-house designs for convertors and controllers. In addition to RPS applications, conceptual fission systems have been demonstrated using Stirling convertors in multiple electrically heated tests and one test heated by a nuclear reactor. The Stirling convertors used in these fission system concepts include 100 We convertors to enable a 1 kWe system, 1 kWe convertors to enable a 10 kWe system, and 6 kWe convertors to enable a 40 kWe system. The maturation of Stirling power convertors for nuclear applications includes verification of performance in relevant environments and validation of the design with a focus on high reliability and robustness. Over 1 million hours of testing has been accumulated on dozens of convertors since 1999 in the Stirling Research Laboratory at the NASA Glenn Research Center located in Cleveland Ohio, where the longest running convertor is the work record holder at 137,000 hours, or 15.5 years. These maturation efforts have been instrumental in increasing the technology readiness level of Stirling technologies for space applications.

S. Wilson↗

DOE OSTI2024

Stability-Constrained Learning for Frequency Regulation in Power Grids With Variable Inertia

The increasing penetration of converter-based renewable generation has resulted in faster frequency dynamics, and low and variable inertia. As a result, there is a need for frequency control methods that are able to stabilize a disturbance in the power system at timescales comparable to the fast converter dynamics. This paper proposes a combined linear and neural network controller for inverter-based primary frequency control that is stable at time-varying levels of inertia. We model the time-variance in inertia via a switched affine hybrid system model. We derive stability certificates for the proposed controller via a quadratic candidate Lyapunov function. We test the proposed control on a 12-bus 3-area test network, and compare its performance with a base case linear controller, optimized linear controller, and finite-horizon Linear Quadratic Regulator (LQR). Our proposed controller achieves faster mean settling time and over 50% reduction in average control cost across 100 inertia scenarios compared to the optimized linear controller. Unlike LQR which requires complete knowledge of the inertia trajectories and system dynamics over the entire control time horizon, our proposed controller is real-time tractable, and achieves comparable performance to LQR.

data-driven control↗

DOE OSTI2023

Accelerating Transitions to Zero Carbon Power Systems

As power systems evolve, becoming increasingly renewable, distributed, dynamic, and digital, managing them becomes ever more challenging and complex. System operators serve as the "air traffic controllers" for electricity grids, working to balance supply and demand, manage evolving electricity markets, and ensure the safety and reliability of electricity systems. To adapt to the rapidly changing energy landscape and support the transition to modern, zero carbon power systems, system operators must develop and adopt new technologies, approaches, and frameworks. The Global Power System Transformation (G-PST) Consortium is a network of system operators, research institutions, and industry partners working to accelerate and scale the technical solutions required to transform our world's power systems. By developing and sharing robust models and tools, research and demonstration results, knowledge, and innovation, the G-PST Consortium is empowering system operators to transition to 100% renewable energy while ensuring the reliability, safety, and cost-effectiveness of grid operations.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗

NASA NTRS1990

Preliminary designs for 25 kWe advanced Stirling conversion systems for dish electric applications

Under the Department of Energy's (DOE) Solar Thermal Technology Program, Sandia National Laboratories is evaluating heat engines for terrestrial Solar Distributed Heat Receivers. The Stirling engine has been identified by Sandia as one of the most promising engines for terrestrial applications. The Stirling engine also has the potential to meet DOE's performance and cost goals. The NASA Lewis Research Center is conducting Stirling engine technology development activities directed toward a dynamic power source for space applications. Space power systems requirements include high reliability, very long life, low vibration and high efficiency. The free-piston Stirling engine has the potential for future high power space conversion systems, either nuclear or solar powered. Although both applications appear to be quite different, their requirements complement each other. Preliminary designs feature a free-piston Stirling engine, a liquid metal heat transport system, and a means to provide nominally 25 kW electric power to a utility grid while meeting DOE's performance and long term cost goals. The Cummins design incorporates a linear alternator to provide the electrical output, while the STC design generates electrical power indirectly through a hydraulic pump/motor coupled to an induction generator. Both designs for the ASCS's will use technology which can reasonably be expected to be available in the early 1990's

Shaltens, Richard K.↗

NASA NTRS1990

Preliminary designs for 25 kWe advanced Stirling conversion systems for dish electric applications

Shaltens, Richard K.↗

DOE OSTI2025

Consensus-Based Control and Optimization of Power System Inertia

The integration of distributed energy resources (DERs), such as solar, wind, and energy storage systems, into power grids through inverter-based resources reduces power system inertia, leading to faster frequency dynamics and potential grid instability. To address this challenge, this paper proposes a distributed, consensus-based approach for the real-time control and optimization of inertia sources (synchronous generators and/or DERs) during system disturbances, enhancing both system stability and economic performance. The distributed control and optimization approach assumes each inertia source exchanges information solely with its neighbor ones, making it easily scalable to large power grid networks. The impacts of the communication connectivity among the inertia sources as well as their generation capacity limits on the distributed approach are investigated. We also demonstrate the approach’s robustness in scenarios involving communication time delays and packet losses, validating its effectiveness through numerical simulations on a 4-bus test system and a two-area 8-bus test system.

Power system inertia↗