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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 541 records · Page 30

Design considerations for space radiators based on the liquid sheet (LSR) concept

This study is directed at performing a comparative examination of LSR characteristics as they affect the basic design of low earth orbit solar dynamic conversion systems. The power systems considered were based on the closed Brayton (CBC) and the free piston Stirling (FPS) cycles, each with a power output of 2 kWe and using previously tested silicone oil (Dow-Corning Me2) as the radiator working fluid. Conclusions indicate that, due to its ability for direct cold end cooling, an LSR based heat rejection subsystem is far more compatible with a Stirling space power system than with a CBC, which requires LSR coupling by means of an intermediate gas/liquid heat exchanger and adjustment of cycle operating conditions.

Juhasz, Albert J.↗

Oscillating-flow loss test results in rectangular heat exchanger passages

Test results of oscillating flow losses in rectangular heat exchanger passages of various aspect ratios are given. This work was performed in support of the design of a free-piston Stirling engine (FPSE) for a dynamic space power conversion system. Oscillating flow loss testing was performed using an oscillating flow rig, which was based on a variable stroke and variable frequency linear drive motor. Tests were run over a range of oscillating flow parameters encompassing the flow regimes of the proposed engine design. Test results are presented in both tabular and graphical form and are compared against analytical predictions.

Wood, J. Gary↗

Propulsion Control Technology Development Needs to Address NASA Aeronautics Research Mission Goals for Thrusts 3a and 4

The Commercial Aero-Propulsion Control Working Group (CAPCWG), consisting of propulsion control technology leads from The Boeing Company, GE Aviation, Honeywell, Pratt & Whitney, Rolls-Royce, and NASA (National Aeronautics and Space Administration) Glenn Research Center, has been working together over the past year to identify propulsion control technology areas of common interest that we believe are critical to achieving the challenging NASA Aeronautics Research goals for Thrust 3a: Ultra-Efficient Commercial Vehicles - Subsonic Transports, and Thrust 4: Transition to Alternative Propulsion and Energy. This paper describes the various propulsion control technology development areas identified by CAPCWG as most critical for NASA to invest in. For Thrust 3a these are: i) Integrated On-Board Model Based Engine Control and Health Management; ii) Flexible and Modular Networked Control Hardware and Software Architecture; iii) Intelligent Air/Fuel Control for Low Emissions Combustion; and iv) Active Clearance Control. For Thrust 4a, the focus is on Hybrid Electric Propulsion (HEP) for single aisle commercial aircraft. The specific technology development areas include: i) Integrated Power and Propulsion System Dynamic Modeling for Control; ii) Control Architectures for HEP; iii) HEP Control Verification and Validation; and iv) Engine/Airplane Control Integration. For each of the technology areas, the discussion includes: problem to be solved and how it relates to NASA goals, and the challenges to be addressed in reducing risk.

Propulsion Control↗

SP-100 Dynamic Power and Lithium-Propellant MPD Nuclear Electric Propulsion Technology Requirements

The objective of this study was to evaluate the requirements (including system integration, design, test requirements, and schedule) for the propulsion and power conversion systems of a nuclear electric propulsion (NEP) vehicle using an SP-100 reactor with a dynamic power conversion system, Li-propellant magnetoplasmadynamic (MPD) thrusters, Li-propellant storage and feed systems, and the power conditioning electronics required to convert the power output from the power system to the form (voltage, current) needed by the thrusters. Potassium-Rankine power conversion systems have the potential for the greatest mission benefit in terms of minimum mass and volume (as compared to Brayton or Stirling power conversion systems), but they require the most development.

Murray, Kathy H.↗

Space station electrical power distribution analysis using a load flow approach

The space station's electrical power system will evolve and grow in a manner much similar to the present terrestrial electrical power system utilities. The initial baseline reference configuration will contain more than 50 nodes or busses, inverters, transformers, overcurrent protection devices, distribution lines, solar arrays, and/or solar dynamic power generating sources. The system is designed to manage and distribute 75 KW of power single phase or three phase at 20 KHz, and grow to a level of 300 KW steady state, and must be capable of operating at a peak of 450 KW for 5 to 10 min. In order to plan far into the future and keep pace with load growth, a load flow power system analysis approach must be developed and utilized. This method is a well known energy assessment and management tool that is widely used throughout the Electrical Power Utility Industry. The results of a comprehensive evaluation and assessment of an Electrical Distribution System Analysis Program (EDSA) is discussed. Its potential use as an analysis and design tool for the 20 KHz space station electrical power system is addressed.

Emanuel, Ervin M.↗

Adding power of artificial intelligence to situational awareness of large interconnections dominated by inverter‐based resources

Abstract Large‐scale power systems exhibit more complex dynamics due to the increasing integration of inverter‐based resources (IBRs). Therefore, there is an urgent need to enhance the situational awareness capability for better monitoring and control of power grids dominated by IBRs. As a pioneering Wide‐Area Measurement System, FNET/GridEye has developed and implemented various advanced applications based on the collected synchrophasor measurements to enhance the situational awareness capability of large‐scale power grids. This study provides an overview of the latest progress of FNET/GridEye. The sensors, communication, and data servers are upgraded to handle ultra‐high density synchrophasor and point‐on‐wave data to monitor system dynamics with more details. More importantly, several artificial intelligence (AI)‐based advanced applications are introduced, including AI‐based inertia estimation, AI‐based disturbance size and location estimation, AI‐based system stability assessment, and AI‐based data authentication.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Development of an advanced photovoltaic concentrator system for space applications

Recent studies indicate that significant increases in system performance (increased efficiency and reduced system mass) are possible for high power space based systems by incorporating technological developments with photovoltaic power systems. The Advanced Photovoltaic Concentrator Program is an effort to take advantage of recent advancements in refractive optical elements. By using a domed Fresnel lens concentrator and a prismatic cell cover, to eliminate metallization losses, dramatic reductions in the required area and mass over current space photovoltaic systems are possible. The advanced concentrator concept also has significant advantages when compared to solar dynamic Organic Rankine Cycle power systems in Low Earth Orbit applications where energy storage is required. The program is currently involved in the selection of a material for the optical element that will survive the space environment and a demonstration of the system performance of the panel design.

Piszczor, Michael F., Jr.↗

Development of an advanced photovoltaic concentrator system for space applications

Recent studies indicate that significant increases in system performance (increased efficiency and reduced system mass) are possible for high power space based systems by incorporating technological developments with photovoltaic power systems. The Advanced Photovoltaic Concentrator Program is an effort to take advantage of recent advancements in refractive optical elements. By using a domed Fresnel lens concentrator and a prismatic cell cover, to eliminate metallization losses, dramatic reductions in the required area and mass over current space photovoltaic systems are possible. The advanced concentrator concept also has significant advantages when compared to solar dynamic Organic Rankine Cycle power systems in Low Earth Orbit applications where energy storage is required. The program is currently involved in the selection of a material for the optical element that will survive the space environment and a demonstration of the system performance of the panel design.

Piszczor, Michael F., Jr.↗

Representation and Impact of Water Head on Power System Planning and Operation

Representing water head information in power system model files, can provide a more realistic model of the system and thereby inform operation and planning personnel in the decision-making process. This article describes a procedure for modifying the power system model files (steady-state and dynamic) to represent water head information. Additionally, the impact of representing the water head on power system reliability studies including contingency analysis, cascading failure analysis and dynamic frequency response analysis has been investigated, using the modified power system models. This paper considers the detailed Western Electricity Coordination Council model during summer and winter conditions as the test system for the impact analysis. Results show that under reduced water head: 1) the number of critical voltage and branch flow violations increases; 2) chances of cascading failure and island formation increases; and 3) frequency nadir decreases as compared to those of the base cases where the water head information is not represented.

13 - HYDRO ENERGY↗

A Scalable Transmission and Distribution Co-simulation Platform for IBR-heavy Power Systems

The integration of Inverter-Based Resources (IBRs) into power systems, including both transmission and distribution networks, poses challenges for studying grid dynamic behaviours under various operating conditions and system events. This paper addresses the urgent need to investigate the influence of IBRs on grid dynamics, and their potential to enhance power system reliability and resilience. We propose a flexible, scalable transmission and distribution co-simulation platform, using opensource tools only for assessing the impact of grid-following (GFL) and grid-forming (GFM) IBRs on dynamic stability at various renewable penetration levels (up to 100%). This platform enables researchers to explore different contingencies at transmission, distribution, or both, providing a comprehensive evaluation of grid status. A series of case studies, including both small and large T&D systems with varying GFL/GFM configurations and contingencies, have been conducted. The results not only robustly validate our co-simulation framework, but also provide invaluable insights for effective IBR management in the power grid.

grid management↗

Analyzing Gas Turbine-Generator Performance of the Hybrid Power System

We report kinetic energy available from the turbomachinery may boost short-term ramp rates during load shifting between generator and fuel cell that may be exploited to optimize the performance of turbine-fuel cell hybrid systems during load following. The paper starts with modeling a gas turbine, gearbox, and generator sitting on the rigid shafts as a two-mass model primarily for estimating the rotational inertia available from the turbogenerator. The gas turbine and its environment impose constraints of available space allowances, measurements from high-speed rotating parts, lack of accessibility to the shaft of measure, making replacements and/or required installation adjustments of the torque transducer difficult. It is demonstrated that in the absence of torque measurement, the data containing only a slow excursion of the rotor motion in response to a slight load change is sufficient to determine inertia and damping coefficients from the model. Furthermore, the generator’s reactive power capability was investigated because it serves as an asset in integrated hybrid systems to meet dynamic reactive power demands, reducing the burden on the fuel cell’s power electronics control in generating reactive power.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Guest Editorial: Special Issue on recent advancements in electric power system planning with high-penetration of renewable energy resources and dynamic loads

The goal of this Special Issue is to present the state-of-the-art methodologies developed for expansion planning of all segments of the modern power systems, characterized by separated businesses, high penetration of renewable resources and new load types, as well as by application of technologically advanced solutions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Identification of a Delay Attack in the Secondary Control of Grid-Tied Inverter Systems

This work is developed for the identification of a denial-of-service cyberattack on the secondary controller of inverter systems which is connected to the power grid. The identification is made through the dynamic response of the reactive power (Q) of the system under attack. By observing the dynamic characteristic of Q, it is possible to correlate the attack with the nominal response of the hierarchical controller. The article shows that the occurrence of the attack can be identified through a supervisory control that runs a model in parallel. The article argues that after an early identification of the attack, a local controller can take action to mitigate its effects on the system’s response.

Roig Greidanus, Mateo D.↗

Machine Learning Derived Dynamic Operating Reserve Requirements in High-Renewable Power Systems

Accurately forecasting wind and solar power output poses challenges for deeply decarbonized electricity systems. Grid operators must commit resources to provide reserves to ensure reliable operations in the face of forecast errors, a process which can increase fuel consumption and emissions. We apply neural network-based machine learning to expand the usefulness of median point forecast data by creating probabilistic distributions of short-term uncertainty in demand, wind, and solar forecasts that adapt to prevailing grid conditions. Machine learning derived estimates of forecast errors compare favorably to estimates based on incumbent methods. Reserves derived from machine learning are usually smaller than values derived using incumbent methods, which enables fuel savings during most hours. Machine learning reserves are generally larger than incumbent reserves during times of higher forecast error, potentially improving system reliability. Performance is tested using multi-stage production simulation modeling of the California Independent System Operator (CAISO) system. Machine learning reserves provide production cost and greenhouse gas (GHG) emission reductions of approximately 0.3% relative to historical 2019 requirements. Savings in the 2030 timeframe are highly dependent on battery storage capacity. At lower levels of battery capacity, savings of 0.4% from machine learning reserves are shown. Significant quantities of battery storage are expected to be added to meet California's resource adequacy needs and GHG reduction targets. Addition of these batteries saturate reserve needs and results in minimal within-hour balancing costs in 2030.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Efficient learning of power grid voltage control strategies via model-based deep reinforcement learning

Here this article proposes a model-based deep reinforcement learning (DRL) method to design emergency control strategies for short-term voltage stability problems in power systems. Recent advances show promising results for model-free DRL-based methods in power systems control problems. But in power systems applications, these model-free methods have certain issues related to training time (clock time) and sample efficiency; both are critical for making state-of-the-art DRL algorithms practically applicable. DRL-agent learns an optimal policy via a trial-and-error method while interacting with the real-world environment. It is also desirable to minimize the direct interaction of the DRL agent with the real-world power grid due to its safety-critical nature. Additionally, the state-of-the-art DRL-based policies are mostly trained using a physics-based grid simulator where dynamic simulation is computationally intensive, lowering the training efficiency. We propose a novel model-based DRL framework where a deep neural network (DNN)-based dynamic surrogate model (SM), instead of a real-world power grid or physics-based simulation, is utilized within the policy learning framework, making the process faster and more sample efficient. However, having stable training in model-based DRL is challenging because of the complex system dynamics of large-scale power systems. We addressed these issues by incorporating imitation learning to have a warm start in policy learning, reward-shaping, and multi-step loss in surrogate model training. Finally, we achieved 97.5% reduction in samples and 87.7% reduction in training time for an application to the IEEE 300-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multi-Timescale Integrated Dynamics and Scheduling for Solar (MIDAS-Solar) (Final Technical Report)

Solar photovoltaic (PV) installations have experienced unprecedented growth in the United States. PV will become not only an energy producer but also a necessary provider of ancillary services at multiple timescales. Conventional methods to simulate power systems operations - such as long-term production simulation (which typically considers schedules from hours to minutes by using an optimization framework) and short-term transient studies (which simulate dynamics from seconds to sub-seconds using state variables and differential equations) - are not sufficient for studying the multiple-timescale variation of solar generation and its impact on system reliability. Long-term system economics and short-term system dynamics are highly coupled, particularly when the penetration level of renewable generation is extremely high, because the uncertainty and variability of solar generation will impact both power system steady-state and dynamic performance. This project helps meet and exceed the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Solar Energy Technologies Office goal of systems integration by directly addressing this stability and reliability challenge for power grid planning and operation. We have developed a temporally comprehensive, closed-loop simulation model, named Multi-timescale Integrated Dynamics and Scheduling (MIDAS), that seamlessly simulates power system operations from economic scheduling (day-ahead to hours) to dynamic response analysis (seconds to sub-seconds). For schedules with very high levels of inverter-based resources (IBRs), up to and including 100%, the stability of grid controls has been evaluated through electromagnetic transient (EMT) simulations and power-hardware-in-the-loop (PHIL) simulations of key transient events at key schedule points. Specifically, MIDAS provides: 1) a closed-loop simulation framework for simulating timescales from economic scheduling to dynamic stability analysis; 2) machine learning-based stability assessment; 3) EMT modeling and analysis for large-scale power systems; 4) MIDAS PHIL test bed. We worked with Hawaii Electric Companies to apply the MIDAS study framework to a Maui grid study. The entire island's transmission system was modeled in detail - from a yearly scheduling model, to a second-level frequency dynamic model, down to a sub-second-scale EMT model to address critical stability issues. The project demonstrated how MIDAS can help system planners and operators assess system reliability and stability while the power grid is marching toward a high-renewable, high-IBR future. In this Maui grid study, we found that 100% instantaneous IBR operation is achievable in EMT simulation and PHIL testing, and grid planners and operators might need new analysis/simulation tools to assess grid reliability and stability in the scheduling stage. MIDAS will bring Maui and other systems closer to 100% clean and stable energy futures. (In this study, we examined transient stability. Other topics necessary for 100% IBR operation, such as protection and resource adequacy, were not examined.)

100% Renewables↗

Space station power system

The major requirements and guidelines that affect the space station configuration and power system are explained. The evolution of the space station power system from the NASA program development-feasibility phase through the current preliminary design phase is described. Several early station concepts are described and linked to the present concept. Trade study selections of photovoltaic system technologies are described in detail. A summary of present solar dynamic and power management and distribution systems is also given.

Baraona, Cosmo R.↗

Vibration Propagation of Gear Dynamics in a Gear-Bearing-Housing System Using Mathematical Modeling and Finite Element Analysis

Vibration and noise caused by gear dynamics at the meshing teeth propagate through power transmission components to the surrounding environment. This study is devoted to developing computational tools to investigate the vibro-acoustic propagation of gear dynamics through a gearbox using different bearings. Detailed finite element/contact mechanics and boundary element models of the gear/bearing/housing system are established to compute the system vibration and noise propagation. Both vibration and acoustic models are validated by experiments including the vibration modal testing and sound field measurements. The effectiveness of each bearing type to disrupt vibration propagation is speed-dependent. Housing plays an important role in noise radiation .It, however, has limited effects on gear dynamics. Bearings are critical components in drivetrains. Accurate modeling of rolling element bearings is essential to assess vibration and noise of drivetrain systems. This study also seeks to fully describe the vibro-acoustic propagation of gear dynamics through a power-transmission system using rolling element and fluid film wave bearings. Fluid film wave bearings, which have higher damping than rolling element bearings, could offer an energy dissipation mechanism that reduces the gearbox noise. The effectiveness of each bearing type to disrupt vibration propagation in explored using multi-body computational models. These models include gears, shafts, rolling element and fluid film wave bearings, and the housing. Radiated noise is mapped from the gearbox surface to surrounding environment. The effectiveness of rolling element and fluid film wave bearings in breaking the vibro-acoustic propagation path from the gear to the housing is investigated.

Parker, Robert G.↗