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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

A Brief Review of the Need for Robust Smart Wireless Sensor Systems for Future Propulsion Systems, Distributed Engine Controls, and Propulsion Health Management

Smart Sensor Systems with wireless capability operational in high temperature, harsh environments are a significant component in enabling future propulsion systems to meet a range of increasingly demanding requirements. These propulsion systems must incorporate technology that will monitor engine component conditions, analyze the incoming data, and modify operating parameters to optimize propulsion system operations. This paper discusses the motivation towards the development of high temperature, smart wireless sensor systems that include sensors, electronics, wireless communication, and power. The challenges associated with the use of traditional wired sensor systems will be reviewed and potential advantages of Smart Sensor Systems will be discussed. A brief review of potential applications for wireless smart sensor networks and their potential impact on propulsion system operation, with emphasis on Distributed Engine Control and Propulsion Health Management, will be given. A specific example related to the development of high temperature Smart Sensor Systems based on silicon carbide electronics will be discussed. It is concluded that the development of a range of robust smart wireless sensor systems are a foundation for future development of intelligent propulsion systems with enhanced capabilities.

Hunter, Gary W.↗
DOE OSTI2023

Optimal Sizing of Movable Energy Resources for Enhanced Resilience in Distribution Systems: A Techno-Economic Analysis

This article introduces a techno-economic analysis aimed at identifying the optimal total size of movable energy resources (MERs) to enhance the resilience of electric power supply. The core focus of this approach is to determine the total size of MERs required within the distribution network to expedite restoration after extreme events. Leveraging distribution line fragility curves, the proposed methodology generates numerous line outage scenarios, with scenario reduction techniques employed to minimize computational burden. For each reduced multiple line outage scenario, a systematic reconfiguration of the distribution network, represented as a graph, is executed using tie-switches within the system. To evaluate each locational combination of MERs for a specific number of these resources, the expected load curtailment (ELC) is calculated by summing the load curtailment within microgrids formed due to multiple line outages. This process is repeated for all possible locational combinations of MERs to determine minimal ELC for each MER total size. For every MER total size, the minimal ELCs are determined. Finally, a techno-economic analysis is performed using power outage cost and investment cost of MERs to pinpoint an optimal total size of MERs for the distribution system. To demonstrate the effectiveness of the proposed approach, case studies are conducted on the 33-node and the modified IEEE 123-node distribution test systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Coordinative Voltage Control Strategy with Multiple Resources for Distribution Systems of High PV Penetration: Preprint

This paper presents an optimal voltage control methodology with coordination among different voltage-regulating resources, including controllable loads, distributed energy resources such as energy storage and photovoltaics (PV), and utility voltage-regulating devices such as voltage regulators and capacitors. The proposed methodology could effectively tackle the overvoltage and voltage regulation device distortion problems brought by high penetrations of PV to improve grid operation reliability. A voltage-load sensitivity matrix and voltage-regulator sensitivity matrix are used to deploy the resources along the feeder to achieve the control objectives. Mixed-integer nonlinear programming is used to solve the formulated optimization control problem. The methodology has been tested on the IEEE 123-feeder test system, and the results demonstrate that the proposed approach could actively tackle the voltage problem brought about by high penetrations of PV and improve the reliability of distribution system operation.

14 SOLAR ENERGY↗
DOE OSTI2017

Smart-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios

The National Renewable Energy Laboratory (NREL) in collaboration with Massachusetts Institute of Technology (MIT), Universidad Pontificia Comillas (Comillas-IIT, Spain) and GE Grid Solutions, is working on an ARPA-E GRID DATA project, titled Smart-DS, to create: 1) High-quality, realistic, synthetic distribution network models, and 2) Advanced tools for automated scenario generation based on high-resolution weather data and generation growth projections. Through these advancements, the Smart-DS project is envisioned to accelerate the development, testing, and adoption of advanced algorithms, approaches, and technologies for sustainable and resilient electric power systems, especially in the realm of U.S. distribution systems. This talk will present the goals and overall approach of the Smart-DS project, including the process of creating the synthetic distribution datasets using reference network model (RNM) and the comprehensive validation process to ensure network realism, feasibility, and applicability to advanced use cases. The talk will provide demonstrations of early versions of synthetic models, along with the lessons learnt from expert engagements to enhance future iterations. Finally, the scenario generation framework, its development plans, and co-ordination with GRID DATA repository teams to house these datasets for public access will also be discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Multi-Fidelity Learning for Distribution System Voltage Probabilistic Analysis with High Penetration of PVs

This paper proposes a multi-fidelity learning approach for distribution voltage probabilistic analysis with high penetration of PVs. Unlike the existing machine learning-based approaches that require a large number of high fidelity data to achieve satisfactory results, our approach strategically leverage massive low fidelity data from inaccurate model simulations and limited high fidelity historical data. The key idea is to use low-fidelity data to establish an initial model and then the high-fidelity data to calibrate and correct the constructed low-fidelity model. This allows us to fuse low- and high-fidelity data, yielding a high fidelity prediction model. Results obtained from a realistic feeder in US with 80% penetration of PVs show that the proposed approach can achieve a similar accuracy to the one with a large number of high fidelity data. This significantly highlights the advantages of the proposed method as compared to existing data-hungry machine learning methods. Different levels of fidelity data and their impacts are also investigated.

distribution system↗
DOE OSTI2021

Learning Sequential Distribution System Restoration via Graph-Reinforcement Learning

We report a distribution service restoration algorithm as a fundamental resilient paradigm for system operators provides an optimally coordinated, resilient solution to enhance the restoration performance. The restoration problem is formulated to coordinate distribution generators and controllable switches optimally. A model-based control scheme is usually designed to solve this problem, relying on a precise model and resulting in low scalability. To tackle these limitations, this work proposes a graph-reinforcement learning framework for the restoration problem. We link the power system topology with a graph convolutional network, which captures the complex mechanism of network restoration in power networks and understands the mutual interactions among controllable devices. Latent features over graphical power networks produced by graph convolutional layers are exploited to learn the control policy for network restoration using deep reinforcement learning. The solution scalability is guaranteed by modeling distributed generators as agents in a multi-agent environment and a proper pre-training paradigm. Comparative studies on IEEE 123-node and 8500-node test systems demonstrate the performance of the proposed solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1992

A trace-driven analysis of name and attribute caching in a distributed system

This paper presents the results of simulating file name and attribute caching on client machines in a distributed file system. The simulation used trace data gathered on a network of about 40 workstations. Caching was found to be advantageous: a cache on each client containing just 10 directories had a 91 percent hit rate on name look ups. Entry-based name caches (holding individual directory entries) had poorer performance for several reasons, resulting in a maximum hit rate of about 83 percent. File attribute caching obtained a 90 percent hit rate with a cache on each machine of the attributes for 30 files. The simulations show that maintaining cache consistency between machines is not a significant problem; only 1 in 400 name component look ups required invalidation of a remotely cached entry. Process migration to remote machines had little effect on caching. Caching was less successful in heavily shared and modified directories such as /tmp, but there weren't enough references to /tmp overall to affect the results significantly. We estimate that adding name and attribute caching to the Sprite operating system could reduce server load by 36 percent and the number of network packets by 30 percent.

Shirriff, Ken W.↗
DOE OSTI2023

An Electromagnetic Transient and Three-Phase Phasor Co-Simulation Platform for Studying Distribution System Transients with High Pentration of DERs

Inverter vendors usually have electro-magnetic transient (EMT) models of distributed energy resources (DERs) for validation purposes and these types of models are usually black-boxed considering intellectual property (IP) protection. Limited by small simulation time step for the entire power system network, studying the system-level responses of DERs in EMT simulators is more time-consuming as the network size increases. Meanwhile, vendors usually do not have inverter models that can be used in three-phase phasor-domain simulators. This paper proposes a platform that can dynamically co-simulate the EMT inverter models and three-phase phasor-domain distribution networks considering high penetration of inverter-based DERs. This platform is very useful for evaluating the impacts of vendor-provided black-box DER model on distribution system dynamics. The co-simulation platform is validated against the full EMT model using a simple two-inverter test system and tested using IEEE 34-node test feeder.

Liu, Yuan↗
NASA NTRS1987

Exploiting virtual synchrony in distributed systems

Applications of a virtually synchronous environment are described for distributed programming, which underlies a collection of distributed programming tools in the ISIS2 system. A virtually synchronous environment allows processes to be structured into process groups, and makes events like broadcasts to the group as an entity, group membership changes, and even migration of an activity from one place to another appear to occur instantaneously, in other words, synchronously. A major advantage to this approach is that many aspects of a distributed application can be treated independently without compromising correctness. Moreover, user code that is designed as if the system were synchronous can often be executed concurrently. It is argued that this approach to building distributed and fault tolerant software is more straightforward, more flexible, and more likely to yield correct solutions than alternative approaches.

Birman, Kenneth P.↗
DOE OSTI2017

Control of Networked Traffic Flow Distribution: A Stochastic Distribution System Perspective

At signalized intersections, the traffic queues are controlled by traffic signal control settings and effective traffic lights control would realize both smooth traffic flow and minimize fuel consumption. Funded by the Energy Efficient Mobility Systems (EEMS) program of the Vehicle Technologies Office of the US Department of Energy, we performed a preliminary investigation on the modelling and control framework in context of urban network of signalized intersections. In specific, we developed a recursive input-output traffic queueing models. The queue formation can be modeled as a stochastic process where the number of vehicles entering each intersection is a random number. Further, we proposed a preliminary B-Spline stochastic modelling and control for a one-way single-lane corridor traffic system based on theory of stochastic distribution control that shapes the PDF of the queue length.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1991

Maintaining consistency in distributed systems

In systems designed as assemblies of independently developed components, concurrent access to data or data structures normally arises within individual programs, and is controlled using mutual exclusion constructs, such as semaphores and monitors. Where data is persistent and/or sets of operation are related to one another, transactions or linearizability may be more appropriate. Systems that incorporate cooperative styles of distributed execution often replicate or distribute data within groups of components. In these cases, group oriented consistency properties must be maintained, and tools based on the virtual synchrony execution model greatly simplify the task confronting an application developer. All three styles of distributed computing are likely to be seen in future systems - often, within the same application. This leads us to propose an integrated approach that permits applications that use virtual synchrony with concurrent objects that respect a linearizability constraint, and vice versa. Transactional subsystems are treated as a special case of linearizability.

Birman, Kenneth P.↗
DOE OSTI2014

Impact of Electric Vehicle Infrastructure on the City of Chatsworth Distribution System

With the growing penetration of the electric vehicles to our daily life owing to their economic and environmental benefits, there will be both opportunities and challenges to the utilities when adopting plug-in electric vehicles (PEV) to the distribution network. In this paper, a thorough analysis based on real-world project is conducted to evaluate the impact of electric vehicles infrastructure on the grid relating to system load flow, load factor, and voltage stability. Chatsworth distribution system was selected and tested along with different case scenarios utilizing the electrical distribution design (EDD) software to find out the potential impacts to the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Evaluating Transactive Controls of Integrated Transmission and Distribution Systems using the Framework for Network Co-Simulation

With an ever-evolving power grid, concerns regarding how to maintain system stability, efficiency, and reliability remain constant because of increasing uncertainties and decreasing rotating inertia. To alleviate some of these concerns, demand response represents a viable solution and is virtually an untapped resource in the current power grid. This work describes a hierarchical control framework that allows coordination between distributed energy resources and demand response. This control framework is composed of two control layers: a coordination layer that ensures aggregations of resources are coordinated to achieve system objectives and a device layer that controls individual resources to assure the predetermined power profile is tracked in real time. Large-scale simulations are executed to study the hierarchical control, requiring advancements in simulation capabilities. Technical advancements necessary to investigate and answer control interaction questions, including the Framework for Network Co-Simulation platform and Arion modeling capability, are detailed. Insights into the interdependencies of controls across a complex system and how they must be tuned, as well as validation of the effectiveness of the proposed control framework, are yielded using a large-scale integrated transmission system model coupled with multiple distribution systems.

demand response↗
DOE OSTI2024

Multi-agent voltage control in distribution systems using GAN-DRL-based approach

Active distribution grids can experience voltage fluctuations and violations due to the high penetration of variable distributed energy resources (DERs). These problems might occur because of the uncertain and variable generation natures of these resources, especially solar photovoltaic resources, during panel shadowing scenarios. Volt-VAR control (VVC) is an efficient method that controls the reactive power set-points of the inverters to regulate the voltage of distribution grids. Although several VVC approaches have been proposed recently, the performance of these approaches degrades significantly if behind-the-meter solar generation data are unobservable/missing. Therefore, it is necessary to impute missing/unobservable PV data accurately to be utilized in VVC approaches. Further, this paper proposes a model-free, data-driven, centrally trained, and decentrally executed multi-agent deep reinforcement learning-based VVC architecture to regulate the voltage of distribution networks. A generative adversarial network (GAN) is incorporated to impute the unobservable PV data accurately, which improves the performance of the proposed control architecture. The proposed multi-agent-soft-actor–critic algorithm (MASAC)-based VVC technique utilizes the actual PV dataset as well as the imputed dataset from the GAN framework to learn the optimal coordinated control policy for controlling the optimal reactive power set-points of PV inverters. The effectiveness of the proposed approach is analyzed on a modified IEEE 34-bus test case with added PV inverters. The results are compared and analyzed with a base case model with no VVC and VVC with a local droop control approach, genetic algorithm optimization, and a centralized soft actor–critic-based approach. Moreover, the performance of the proposed approach is compared with that of a multi-agent VVC framework without using the PV generation data and load information as the system state. The results illustrate that the proposed method with more state input improves the voltage profile and reduces the power loss of the network across various loading and PV generation scenarios.

14 SOLAR ENERGY↗
NASA NTRS1979

A distributed system adaptive control strategy

One attitude control device being studied for large spacecraft consists of two counter-rotating rings, each designated as an annular momentum control device (AMCD), that are attached to a spacecraft using several magnetic bearings distributed along the circumference of the rings. For large spacecraft large rings are desirable. Unfortunately, for large rings flexibility is appreciable and it becomes necessary to account for the distributed nature of the rings in the design of the magnetic bearing controllers. Also ring behavior is unpredictably sensitive to ring temperature, spin rate, manufacturing imperfections, and other variables. For that reason a distributed adaptive microcomputer-based control system is being sought for ring stabilization and maneuvering. An original adaptive-control methodology for distributed-parameter systems is detailed and application to spinning ring, i.e., AMCD, stabilization is used as an illustration. The proposed methodology, presented as a step-by-step procedure, combines a lumped-parameter expansion description of distributed parameter systems with a fundamental simultaneous identification and control strategy. Simulations are presented providing preliminary evidence of the capabilities of the proposed procedure.

Johnson, C. R., Jr.↗
NASA NTRS1972

Stability of distributed systems with feedback via Michailov's criterion.

Development of a stability criterion of the Nyquist type from Michailov's criterion for a large class of distributed parameter systems, in particular, for a large class of transmission line systems with feedback. Following a generalization of Michailov's criterion, simplifying assumptions, usually valid in practice, are shown to yield a simplified test for determining whether 'encirclement-counting' constitutes a valid stability test. The results are reformulated for an open-loop analysis. Three examples show various aspects of the theoretical analysis.

Reis, G. C.↗