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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 793 records · Page 44

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Long-duration Energy Storage Technology Analysis and Development

This project develops a new low-cost and flexible long-duration energy storage (LDES) technology based on simultaneous regeneration technology. In lieu of the technology development, the project team also conducts a complete cost analysis for LDES based on various currently available technologies, as well as grid economic and environmental benefits analysis for LDES. There are three tasks in this project: Task 1. Fe-H2 flow cell fabrication, testing, demonstration; Task 2. Dynamic modeling, simulation and control architecture of power system; Task 3. Cost and grid analysis.

25 ENERGY STORAGE↗

DOE OSTI2021

Application of Machine Learning Techniques to an Agent-Based Model of Pantoea

Agent-based modeling (ABM) is a powerful simulation technique which describes a complex dynamic system based on its interacting constituent entities. While the flexibility of ABM enables broad application, the complexity of real-world models demands intensive computing resources and computational time; however, a metamodel may be constructed to gain insight at less computational expense. Here, we developed a model in NetLogo to describe the growth of a microbial population consisting of Pantoea . We applied 13 parameters that defined the model and actively changed seven of the parameters to modulate the evolution of the population curve in response to these changes. We efficiently performed more than 3,000 simulations using a Python wrapper, NL4Py . Upon evaluation of the correlation between the active parameters and outputs by random forest regression, we found that the parameters which define the depth of medium and glucose concentration affect the population curves significantly. Subsequently, we constructed a metamodel, a dense neural network, to predict the simulation outputs from the active parameters and found that it achieves high prediction accuracy, reaching an R 2 coefficient of determination value up to 0.92. Our approach of using a combination of ABM with random forest regression and neural network reduces the number of required ABM simulations. The simplified and refined metamodels may provide insights into the complex dynamic system before their transition to more sophisticated models that run on high-performance computing systems. The ultimate goal is to build a bridge between simulation and experiment, allowing model validation by comparing the simulated data to experimental data in microbiology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Embedded, Real-Time, and Distributed Traveling Wave Fault Location Method Using Graph Convolutional Neural Networks

This work proposes and develops an implementation of a fault location method to provide a fast and resilient protection scheme for power distribution systems. The method analyzes the transient dynamics of traveling waves (TWs) to generate features using the discrete wavelet transform (DWT), which are then used to train several graph convolutional network (GCN) models. Faults are simulated in the IEEE 34-node system, which is divided into three protection zones (PZs). The goal is to identify the PZ in which the fault occurs. The GCN models create a distributed protection scheme, as all nodes are able to retrieve a prediction. Given that message-passing between nodes occurs both during training and in the execution of the model, the resiliency of such schemes to communication losses was analyzed and demonstrated. One of the models, which only uses voltage measurements, was implemented on a Texas Instruments F28379D development board. The execution times were monitored to assess the speed of the protection scheme. It is shown that the proposed method can be executed in approximately a millisecond, which is comparable to existing TW protection in the transmission system. For experimental purposes, a DWT-based detection method is employed. A design of a setup to playback TWs using two development boards is also addressed.

Jiménez-Aparicio, Miguel (ORCID:000000016864461X)↗

DOE OSTI2023

IM3 GO WEST Parameter Search Dataset

GO WEST is an open-source power grid modeling framework for U.S. Western Interconnection, which allows users to tailor the model depending on their research study and science questions. It is developed to address weather and water dynamics, and associated vulnerabilities in this bulk power system. It covers 28 balancing authorities (BA) and 12 states in U.S. Western Interconnection. GO WEST allows users to select different number of nodes and come up with a simplified network by utilizing 10,000 nodal topology of U.S. Western Interconnection created by Texas A&M University. Users can try and select different number of nodes, mathematical formulations (linear programming vs. mixed-integer linear programming), transmission line limit scaling factors, and hurdle rate scaling factors. GO WEST offers a unit commitment and economic dispatch (UC/ED) module to simulate grid operations on an hourly scale. In this sense, users can calibrate and validate their model versions by comparing model outputs to historical datasets. Therefore, GO WEST can help researchers to strike a balance between model fidelity (i.e. accuracy) and computational complexity (i.e. runtime). This dataset includes model inputs and outputs from 600 model versions for each 2019, 2020, and 2021. The folder naming convention is as follows: Exp{Number of Nodes}_{Mathematical Formulation}_{Transmission Line Limit Scaling Factor in MW}_{Hurdle Rate Scaling Factor in %}_{Year}. Linear programming is designated with "simple" label whereas mixed-integer linear programming is designated with "coal" label. For example, "Exp100_simple_1000_50_2019" folder contains inputs and outputs from 2019 model version with 100 nodes, linear programming, +1000 MW transmission line limit scaling factor, and +50% hurdle rate scaling factor. GO WEST GitHub repository hosts all raw datasets, processing scripts, and model scripts. Please refer to the README file for a detailed description of the included files.

Economics↗

NASA NTRS1981

On regulators with a prescribed degree of stability

Several important aspects of the Regulator with a Prescribed Degree of Stability (RPDS) methodology and its applications are considered. The solution of the time varying RPDS problem as well as the characterization of RPDS closed loop eigenstructure properties are obtained. Based on the asymptotic behavior of RPDS root loci, a one step algorithm for designing Regulators with Prescribed Damping Ratio (RPDR) is developed. The robustness properties of RPDS are characterized in terms of the properties of the return difference and the inverse return difference matrices for the RPDS state feedback loop. This class of regulators is found to possess excellent multiloop margins with respect to stability and degree of stability properties. The ability of RPDS design to tolerate changing operating conditions and unmodelled dynamics are illustrated with a multiterminal dc/ac power system example. The output feedback realization of RPDS requires the use of Linear Quadratic Gaussian (LQG) methodology.

Ng, P. T. P.↗

NASA NTRS1985

An overview of the Space Station Technology/Advanced Development Program

The Advanced Technology Plan of the Fiscal Year (FY) 1986 is designed to focus on the most promising technology options applicable to the Space Station (SS), selected from the list of tasks identified by the FY 1984 Technology Program as the most critical technologies to be developed for the initial SS Initial Operating Capability. Most of the current activities are in the stages of manufacture and life tests of specific SS subsystems. Special attention is given to major technologies, which include power systems (PSs) (with emphasis on a Solar Dynamic PS concept); the thermal control system (with the focus on the 'thermal bus' concept); the environmental control and life support system; and the data management system; all are illustrated schematically. Other tasks, including dynamics, communications, extravehicular activities, mechanics, propulsion, and fluid, as well as the tasks of cost, maintainability, automation and robotics, and productivity are discussed.

Carlisle, R. F.↗

NASA NTRS1987

Small-Signal ac Analysis

Program simulates power circuits and systems. Small Signal A.C. Analysis program (SSAC) valuable tool for design and analysis of electrical-power-system circuits. By combining "black box" power-system components operating in specified manner, user characterizes system modeled. Menu-driven program proved simple and cost effective in development and modification of arbitrary power-system configurations. Package includes sample data from Dynamic Explorer satellite family. Results compared favorable to calculations from such general circuit-analysis programs as SPICE. Written in FORTRAN 77.

Jagielski, James M.↗

NASA NTRS1987

High thermal-transport capacity heat pipes for space radiators

This paper presents the results of performance tests of several dual-slot heat pipe test articles. The dual-slot configuration has a very high thermal transport capability and has been identified as a very promising candidate for the radiator system for the NASA Space Station solar dynamic power modules. Two six-foot long aluminum heat pipes were built and tested with ammonia and acetone. A 20-ft long heat pipe was also built and tested with ammonia. The test results have been compared with performance predictions. A thermal transport capacity of 2000 W at an adverse tilt of 1 in. and a 1000 W capacity at an adverse tilt of 2 in. were achieved on the 20-ft long heat pipe. These values are in close agreement with the predicted performance limits.

Carlson, Albert W.↗

NASA NTRS1993

Engine management during NTRE start up

The topics are presented in viewgraph form and include the following: total engine system management critical to successful nuclear thermal rocket engine (NTRE) start up; NERVA type engine start windows; reactor power control; heterogeneous reactor cooling; propellant feed system dynamics; integrated NTRE start sequence; moderator cooling loop and efficient NTRE starting; analytical simulation and low risk engine development; accurate simulation through dynamic coupling of physical processes; and integrated NTRE and mission performance.

Bulman, Mel↗

NASA NTRS2018

Optically Inaccessible Flow Visualization using Positron Emission Tomography

Flow visualization is a powerful tool for characterizing fluid dynamics within engineering systems that utilize fluid working media. Recent advances in Positron Emission Tomography (PET) have enhanced its ability to extend beyond the medical field, and offer an alternate vantage point in visualizing optically inaccessible fluid distributions and flow fields within the aerospace field. In light of this prospect an investigation has ensued to parametrically bound the flows that can be sufficiently resolved using current PET technology. Results from an initial series of experiments and analyses performed at the Positron Imaging Centre (PIC) located at the University of Birmingham, UK, will be presented. Discussion will also cover preliminary, on-going, activities associated with assessing the utility of PET technology in zero-gravity propellant gauging, ionization efficiency characterization in electric propulsion devices, and broader industrial applications.

PET↗

NASA NTRS2018

Optically Inaccessible Flow Visualization using Positron Emission Tomography

Bruggemann, Jeremy↗

DOE OSTI2023

Developing Renewable Energy Applications for Water Treatment Technologies and Transmission

The need for smaller treatment facilities for more isolated or rural municipal entities and industrial water treatment facilities continues to grow. From environmental justice and energy needs in remote communities that have never been serviced by larger scale utilities to smaller onsite treatment requirements to meet discharge regulations, energy efficient treatment systems that can leverage renewable energy sources can be an important asset to owners. Climate change and population dynamics have changed the needs for distributed water treatment systems and the manner in which they function. New treatment technologies that can operate under dynamic conditions and leverage variable energy sources (e.g., renewable energy, RE) can provide substantial efficiencies and cost savings. The National Renewable Energy Laboratory (NREL) is embarking on research projects that will perform multi-scale studies to investigate treatment technologies on varying source water quality that can operate under unsteady state flow conditions (timing) in response to energy availability, supply, and demand. A pilot-scale system will be built to assess modularity and scaling of treatment system operating conditions and performance. Modeling will also be used to determine feasibility and integration into grid emulation platforms to understand the use and value of operation with RE. Optimization will be completed for the treatment and distribution systems to document strengths and weaknesses of using RE power sources. Results of this effort will advance dynamic water treatment understanding under variable conditions and integration of RE sources to power these systems. This will lead to further decarbonization of municipal and private treatment facilities while supporting a paradigm shift in water treatment process operation and system design to achieve net-zero goals and move toward energy-sensitive resilient water treatment systems.

ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Quantum Algorithm for Simulating Hamiltonian Dynamics with an Off-diagonal Series Expansion

We propose an efficient quantum algorithm for simulating the dynamics of general Hamiltonian systems. Our technique is based on a power series expansion of the time-evolution operator in its off-diagonal terms. The expansion decouples the dynamics due to the diagonal component of the Hamiltonian from the dynamics generated by its off-diagonal part, which we encode using the linear combination of unitaries technique. Our method has an optimal dependence on the desired precision and, as we illustrate, generally requires considerably fewer resources than the current state-of-the-art. We provide an analysis of resource costs for several sample models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

An ERCOT test system for market design studies

An open source test system is developed that permits the dynamic modeling of centrally-managed wholesale power markets operating over highvoltage transmission grids. In default mode, the test system models basic operations in the Electric Reliability Council of Texas (ERCOT): namely, centrally-managed day-ahead and real-time markets operating over successive days, with congestion handled by locational marginal pricing. These basic operational features characterize all seven U.S. energy regions organized as centrally-managed wholesale power markets. Modeled participants include dispatchable generators, load-serving entities, and non-dispatchable generation such as unrmed wind and solar power. Users can congure a broad variety of parameters to study basic market and grid features under alternative system conditions. Users can also easily extend the test system's Java/Python software classes to study modied or newly envisioned market and grid features. Finally, the test system is integrated with a high-level simulation framework that permits it to function as a software component within larger systems, such as multi-country systems or integrated transmission and distribution systems. Finally, detailed test cases with 8-bus and 200-bus transmission grids are reported to illustrate these test system capabilities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2020

An Electrical Modeling and Thermal Analysis Toolbox for Electrified Aircraft Propulsion Simulation

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 paper is to present an overview 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 also provide some examples of EAP system modeling using EMTAT.

Mark E Bell↗

NASA NTRS2020

An Electrical Modeling and Thermal Analysis Toolbox for Electrified Aircraft Propulsion Simulation

Mark E Bell↗

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↗