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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 343 records · Page 19

All sources NASA NTRS DOE OSTI

DOE OSTI2026

Distribution System Congestion Management - A Survey of Reliable Integration for Aggregated Resources and Microgrids

Rising penetration of consumer-owned Distribution Grid Resources (DGRs), increasingly managed by third party aggregators and enrolled in grid services and wholesale market programs, can create localized congestion in distribution networks. Managing these constraints is challenging due to a persistent coordination and information gap: utilities are accountable for reliability and have network topology and state visibility, while aggregators control the DGR capability needed to relieve congestion. This survey synthesizes congestion management solutions for distribution systems with high DGR penetration, covering both market-based mechanisms (distribution level markets, locational pricing, flexibility auctions) and non-market-based solutions (network reconfiguration, direct DGR control, demand response, curtailment, etc.). The literature is organized across three decision horizons: long term planning, operational planning, and real-time operation. Special attention is devoted to emerging distribution system operator architectures and coordination frameworks spanning transmission system operators, aggregators, and microgrids. Drawing on recent case studies and implementations, we distill best practices, identify key technical and economic barriers, and outline research directions. The evidence points to a shift toward integrated congestion management that combines market signals with technical controls, enabled by improved monitoring, forecasting, and closed loop control capabilities.

Active Distribution Networks (ADN)↗

DOE OSTI2021

Data-Driven Global Sensitivity Analysis of Three-Phase Distribution System with PVs

Global sensitivity analysis (GSA) of distribution system with respect to stochastic PV variations plays an important role in designing optimal voltage control schemes. This paper proposes a Kriging, i.e., Gaussian process modeling enabled data-driven GSA method. The key idea is to develop a surrogate model that captures the hidden global relationship between voltage and real and reactive power injections from the historical data. With the surrogate model, the Sobol index can be conveniently calculated to assess the global sensitivity of voltage to various power injection variations. Comparison results with other model-based GSA methods on the IEEE 37-bus feeder, such as the polynomial chaos expansion and the Monte Carlo approaches demonstrate that the proposed method can achieve accurate GSA outcomes while maintaining high computational efficiency.

distribution system analysis↗

DOE OSTI2017

A two-stage stochastic optimization model for scheduling electric vehicle charging loads to relieve distribution-system constraints

Electric vehicles (EVs) hold promise to improve the energy efficiency and environmental impacts of transportation. However, widespread EV use can impose significant stress on electricity-distribution systems due to their added charging loads. This paper proposes a centralized EV charging-control model, which schedules the charging of EVs that have flexibility. This flexibility stems from EVs that are parked at the charging station for a longer duration of time than is needed to fully recharge the battery. The model is formulated as a two-stage stochastic optimization problem. The model captures the use of distributed energy resources and uncertainties around EV arrival times and charging demands upon arrival, non-EV loads on the distribution system, energy prices, and availability of energy from the distributed energy resources. We use a Monte Carlo-based sample-average approximation technique and an L-shaped method to solve the resulting optimization problem efficiently. We also apply a sequential sampling technique to dynamically determine the optimal size of the randomly sampled scenario tree to give a solution with a desired quality at minimal computational cost. Here, we demonstrate the use of our model on a Central-Ohio-based case study. We show the benefits of the model in reducing charging costs, negative impacts on the distribution system, and unserved EV-charging demand compared to simpler heuristics. Lastly, we also conduct sensitivity analyses, to show how the model performs and the resulting costs and load profiles when the design of the station or EV-usage parameters are changed.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

Optimization Framework to Assess the Demand Response Capacity of a Water Distribution System

As large electricity consumers, water distribution system (WDS) pumping stations have the potential to become meaningful participants in demand response (DR) programs. The authors propose an optimization framework for assessing the DR capacity of a WDS and identifying the optimal bidding strategy for maximizing WDS revenue in the DR spot market. The proposed mixed integer linear programming (MILP) model overcomes computational constraints of previous DR optimization models by adopting a preprocessing procedure to minimize the number of binary variables and implementing a convex relaxation technique to linearize the hydraulic equations. The proposed MILP model also explicitly accounts for varying levels of risk tolerance of WDS operators by varying the recovery period over which pumping returns to business-as-usual operation. The optimization framework is implemented on a skeletonized 48-node WDS model that includes 7 pumps, 6 tanks, and 39 pipes. Using a simulated DR event and water consumption profile, the authors derive the optimal DR supply curves (i.e., compensation price versus load curtailment quantity) and revenue potential of the WDS under six scenarios for DR participation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Multiperiod Distribution System Restoration With Routing Repair Crews, Mobile Electric Vehicles, and Soft-Open-Point Networked Microgrids

This paper proposes a distribution system restoration model which is in response to multiple outages caused by natural disasters. The proposed restoration model includes the coordination of routing repair crews (RRCs), mobile batterycarried vehicles (MBCVs), and networked microgrids (NMGs) formed by soft open points (SOPs). The travel and repair time constraints are modeled for each RRC; travel path and charging strategy are modeled for each MBCV; and the network reconfiguration is developed considering the optimal operation of SOP-based NMGs. Furthermore, the proposed model is presented as a mixedinteger linear program which is solved by an auxiliary induce function based algorithm to reduce the computational complexity. The modified IEEE 33-bus and 69-bus distribution systems are tested with multiple outages. The presented results demonstrate the effectiveness of the proposed model

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1980

On deadlock detection in distributed systems

A hierarchically organized and a distributed protocol for deadlock detection in distributed databases are presented in a previous study Menasce and Muntz (1979). In this paper, it is shown that the distributed protocol is incorrect, and possible remedies are presented. However, the distributed protocol remains impractical because 'condensations' of 'transaction-wait-for' graphs make graph updates difficult to perform. Delayed graph updates cause the occurrence of false deadlocks in this as well as in some other deadlock detection protocols for distributed systems. The performance degradation that results from false deadlocks depends on the characteristics of each protocol.

Gligor, V. D.↗

NASA NTRS1987

Fault-tolerant power distribution system

A fault-tolerant power distribution system which includes a plurality of power sources and a plurality of nodes responsive thereto for supplying power to one or more loads associated with each node. Each node includes a plurality of switching circuits, each of which preferably uses a power field effect transistor which provides a diode operation when power is first applied to the nodes and which thereafter provides bi-directional current flow through the switching circuit in a manner such that a low voltage drop is produced in each direction. Each switching circuit includes circuitry for disabling the power field effect transistor when the current in the switching circuit exceeds a preselected value.

Volp, Jeffrey A.↗

DOE OSTI2019

The Dominant Influencer of Voltage Fluctuation (DIVF) for Power Distribution System

Variability in power generation at multiple consumer owned renewable energy sources can cause random voltage fluctuations, which may result in voltage violations at multiple nodes in a power distribution system. Traditional methods of voltage control are ineffective to address fast voltage variations. New dynamic methods of voltage control using end user devices can significantly benefit from the knowledge of the dominant influencer of voltage fluctuation (DIVF). This paper introduces information theoretic metrics to identify DIVF for every node in the power distribution system. A node can be DIVF due to its location in the distribution system and its capacity to generate and change its power. Use of traditional power flow algorithms to identify the DIVF is computationally complex which limits their use in real-time applications. In this work, information theoretic indicators of the DIVF are computed analytically in a computationally efficient manner, and their effectiveness to identify the DIVF is tested using the IEEE 69 node test system. From simulations, it is illustrated that differential entropy, Kullback-Leibler distance and Frechet distance are effective indicators of the DIVF and can successfully identify the most influential nodes providing the foundation for intelligent voltage control.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Distribution System Dataset Generator for AI Applications [SWR-24-75]

This software is a simple, light-weight python package to generate pytorch compatible machine learning graph dataset representing electric power distribution system. User is able to use these graph datasets to test their graph generation artificial intelligence (AI) models, link prediction AI models, graph classification AI models and so much more. This package uses grid-data-models (https://github.com/NREL-Distribution-Suites/grid-data-models) as input data format for power distribution system. NREL-Ditto (https://github.com/NREL-Distribution-Suites/ditto) tool can be leveraged to transform popular distribution system file formats such as opendss, cyme and synergi to grid-data-models.

Duwadi, Kapil↗

DOE OSTI2019

Online Static Load Model Estimation in Distribution Systems

This paper focuses on parameter identification for time-varying voltage-dependent polynomial load models in distribution systems—namely, the constant impedance (Z), constant current (I), and constant power (P). The paper assumes the presence of measurements at the distribution nodes from various sources, each at varying temporal resolutions. The least- squares estimation method with bounded variables is used to convert the measurements into ZIP parameter estimations for loads at various locations on the feeder. The results and discussions focus on some of the estimation issues faced in a distribution system caused by varying voltage sensitivities of loads along a feeder, measurement resolution, impact of window size and sampling rate of measurement data. Finally, the paper uses dynamic simulations data (synthetic high-resolution measurements) to further improve the estimation results.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2005

Designing and Implementing a Distributed System Architecture for the Mars Rover Mission Planning Software (Maestro)

Distributed systems allow scientists from around the world to plan missions concurrently, while being updated on the revisions of their colleagues in real time. However, permitting multiple clients to simultaneously modify a single data repository can quickly lead to data corruption or inconsistent states between users. Since our message broker, the Java Message Service, does not ensure that messages will be received in the order they were published, we must implement our own numbering scheme to guarantee that changes to mission plans are performed in the correct sequence. Furthermore, distributed architectures must ensure that as new users connect to the system, they synchronize with the database without missing any messages or falling into an inconsistent state. Robust systems must also guarantee that all clients will remain synchronized with the database even in the case of multiple client failure, which can occur at any time due to lost network connections or a user's own system instability. The final design for the distributed system behind the Mars rover mission planning software fulfills all of these requirements and upon completion will be deployed to MER at the end of 2005 as well as Phoenix (2007) and MSL (2009).

Goldgof, Gregory M.↗

NASA NTRS1982

The implementation and use of Ada on distributed systems with high reliability requirements

The use and implementation of Ada in distributed environments in which the hardware components are assumed to be unreliable is investigated. The possibility that a distributed system can be programmed entirely in Ada so that the individual tasks of the system are unconcerned with which processor they are executing on, and that failures can occur in the underlying hardware is considered. The reduced cost of computer hardware and the advantages of distributed processing (for example, increased reliability through redundancy and greater flexibility) indicate that many aerospace computer systems can be distributed. The use of Ada and distributed systems is a good combination for aerospace embedded systems.

Knight, J. C.↗

DOE OSTI2023

Data exchange and processing synchronization in distributed systems

Systems, methods, techniques and apparatuses of asynchronous communication is distributed systems are disclosed. One exemplary embodiment is a method determining, with a plurality of agent nodes structured to communicate asynchronously in a distributed system, a first set of iterations including an iteration determined by each of the plurality of agent nodes; determining, with a first agent node of the plurality of agent nodes, a local vector clock; receiving, with the first agent node, a first iteration of the first set of iterations and a remote vector clock determined based on the first iteration; updating, with the first agent node, the local vector clock based on the received remote vector clock; and determining a first iteration of a second set of iterations based on the first set of iterations after determining all iterations of the first set of iterations have been received based on the local vector clock.

Cintuglu, Mehmet H.↗

NASA NTRS2005

Enabling Requirements-Based Programming for Highly-Dependable Complex Parallel and Distributed Systems

The manual application of formal methods in system specification has produced successes, but in the end, despite any claims and assertions by practitioners, there is no provable relationship between a manually derived system specification or formal model and the customer's original requirements. Complex parallel and distributed system present the worst case implications for today s dearth of viable approaches for achieving system dependability. No avenue other than formal methods constitutes a serious contender for resolving the problem, and so recognition of requirements-based programming has come at a critical juncture. We describe a new, NASA-developed automated requirement-based programming method that can be applied to certain classes of systems, including complex parallel and distributed systems, to achieve a high degree of dependability.

Hinchey, Michael G.↗

DOE OSTI2021

Enhancement of Distribution System State Estimation Using Pruned Physics-Aware Neural Networks

Realizing complete observability in the three-phase distribution system remains a challenge that hinders the implementation of classic state estimation algorithms. In this paper, a new method, called the pruned physics-aware neural network (P2N2), is developed to improve the voltage estimation accuracy in the distribution system. The method relies on the physical grid topology, which is used to design the connections between different hidden layers of a neural network model. To verify the proposed method, a numerical simulation based on one- year smart meter data of load consumptions for three-phase power flow is developed to generate the measurement and voltage state data. The IEEE 123-node system is selected as the test network to benchmark the proposed algorithm against the classic weighted least squares (WLS). Numerical results show that P2N2 outperforms WLS in terms of data redundancy and estimation accuracy.

distribution system state estimation↗

NASA NTRS1986

Clouds: A support architecture for fault tolerant, distributed systems

Clouds is a distributed operating system providing support for fault tolerance, location independence, reconfiguration, and transactions. The implementation paradigm uses objects and nested actions as building blocks. Subsystems and applications that can be supported by Clouds to further enhance the performance and utility of the system are also discussed.

Dasgupta, P.↗

DOE OSTI2016

Distribution system model calibration with big data from AMI and PV inverters

Efficient management and coordination of distributed energy resources with advanced automation schemes requires accurate distribution system modeling and monitoring. Big data from smart meters and photovoltaic (PV) micro-inverters can be leveraged to calibrate existing utility models. This paper presents computationally efficient distribution system parameter estimation algorithms to improve the accuracy of existing utility feeder radial secondary circuit model parameters. The method is demonstrated using a real utility feeder model with advanced metering infrastructure (AMI) and PV micro-inverters, along with alternative parameter estimation approaches that can be used to improve secondary circuit models when limited measurement data is available. Lastly, the parameter estimation accuracy is demonstrated for both a three-phase test circuit with typical secondary circuit topologies and single-phase secondary circuits in a real mixed-phase test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Equity‐aware power distribution system restoration

Abstract The efficient, reliable, and resilient supply of electricity has become essential for social and economic well‐being of the modern society. However, more frequent occurrence of extreme weather events has exposed inequity in the planning and operation practices of power distribution systems, evidenced in higher vulnerability and longer power interruptions for some parts of the grid as compared to others. This paper proposes an equity‐aware power distribution system restoration model in an effort to ensure a more equitable yet resilient power distribution operation after outages. To this end, the proposed equity‐aware distribution system restoration model balances the efficiency of the restoration operation and the equitable allocation of distributed energy resources among affected customers after an outage, while prioritizing the critical infrastructure (e.g. hospitals). The results demonstrate the effectiveness of the proposed framework to ensure a more equitable restoration process as measured by the proposed fairness and restoration performance indices.

Engineering↗