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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Resilience-Motivated Distribution System Restoration Considering Electricity-Water-Gas Interdependency

A major outage in the electricity distribution system may affect the operation of water and natural gas supply systems, leading to an interruption of multiple services to critical customers. Therefore, enhancing resilience of critical infrastructures requires joint efforts of multiple sectors. In this paper, a distribution system service restoration method considering the electricity-water-gas interdependency is proposed. The objective is maximizing the supply of electricity, water, and gas to critical customers after an extreme event. The operational constraints of electricity, water, and natural gas networks are considered. Additionally, the characteristics of electricity-driven coupling components, including water pumps and gas compressors, are also modeled. Relaxation techniques are applied to non convex constraints posed by physical laws of those networks. Consequently, the restoration problem is formulated as a mixed-integer second-order cone program, which can readily be solved by the off-the-shelf solvers. The proposed method is validated by numerical simulations on an electricity-water-gas integrated system, developed based on benchmark models of the subsystems. The results indicate that considering the interdependency refines the allocation of limited generation resources and demonstrate the exactness of the proposed convex relaxation

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Physics-Informed Graph Neural Networks for Collaborative Dynamic Reconfiguration and Voltage Regulation in Unbalanced Distribution Systems

Network reconfiguration has long been employed as a strategic approach to minimize power distribution system losses and effectively regulate voltage levels. Tap-changing voltage regulators are also critical for controlling bus voltages, especially in accommodating the increasing integration of distributed energy resources (DERs) with intermittent outputs. This paper introduces novel methodologies to address the challenges of dynamic reconfiguration and optimal tap setting in unbalanced three-phase distribution systems. We propose an approximated mixed-integer quadratically constrained program (MIQCP) to model dynamic reconfiguration, along with a pioneering formulation for voltage regulator (VR) tap-setting based on Special Ordered Set type 1 (SOS1). To mitigate computational complexity, we propose a physics-informed spatial-temporal graph convolutional network (STGCN) with an integrated link classifier. The proposed approach enables efficient solution generation by fixing specific variables in the MIQCP instance and solving the simplified sub-MIP using an MIP solver. Numerical studies demonstrate the superior prediction accuracy of our STGCN model compared to baseline neural network models, resulting in reduced DER curtailment and voltage deviation with shorter computation time.

dynamic reconfiguration↗
NASA NTRS1972

Optimal control of first order distributed systems

The problem of characterizing optimal controls for a class of distributed-parameter systems is considered. The system dynamics are characterized mathematically by a finite number of coupled partial differential equations involving first-order time and space derivatives of the state variables, which are constrained at the boundary by a finite number of algebraic relations. Multiple control inputs, extending over the entire spatial region occupied by the system ("distributed controls') are to be designed so that the response of the system is optimal. A major example involving boundary control of an unstable low-density plasma is developed from physical laws.

Johnson, T. L.↗
DOE OSTI2023

Co-Simulation of Electric Power Distribution Systems and Buildings including Ultra-Fast HVAC Models and Optimal DER Control

Smart homes and virtual power plant (VPP) controls are growing fields of research with potential for improved electric power grid operation. A novel testbed for the co-simulation of electric power distribution systems and distributed energy resources (DERs) is employed to evaluate VPP scenarios and propose an optimization procedure. DERs of specific interest include behind-the-meter (BTM) solar photovoltaic (PV) systems as well as heating, ventilation, and air-conditioning (HVAC) systems. The simulation of HVAC systems is enabled by a machine learning procedure that produces ultra-fast models for electric power and indoor temperature of associated buildings that are up to 133 times faster than typical white-box implementations. Hundreds of these models, each with different properties, are randomly populated into a modified IEEE 123-bus test system to represent a typical U.S. community. Advanced VPP controls are developed based on the Consumer Technology Association (CTA) 2045 standard to leverage HVAC systems as generalized energy storage (GES) such that BTM solar PV is better utilized locally and occurrences of distribution system power peaks are reduced, while also maintaining occupant thermal comfort. An optimization is performed to determine the best control settings for targeted peak power and total daily energy increase minimization with example peak load reductions of 25+%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1983

Data systems - Optical bus will connect distributed system

The fiber optics buses currently under consideration for the NASA space station program will have data rates of at least 20 Mb/sec. The network interconnection scheme that will eventually be used is, however, uncertain. A NASA-Langley effort on graph networks includes adaptive, fault-tolerant and self-correcting operations. A breadboard program at NASA-Johnson includes evaluations of standard devices, called 'bus interface units', in an adaptive and fault-correcting chordal or concentric ring type of network. Fiber optics would allow an evolution to wavelength modulation techniques in such systems.

Swingle, W. L.↗
NASA NTRS1989

Optimal dynamic control of resources in a distributed system

The authors quantitatively formulate the problem of controlling resources in a distributed system so as to optimize a reward function and derive optimal control strategies using Markov decision theory. The control variables treated are quite general; they could be control decisions related to system configuration, repair, diagnostics, files, or data. Two algorithms for resource control in distributed systems are derived for time-invariant and periodic environments, respectively. A detailed example to demonstrate the power and usefulness of the approach is provided.

Shin, Kang G.↗
NASA NTRS1990

A comparative study of electric power distribution systems for spacecraft

The electric power distribution systems for spacecraft are compared concentrating on two interrelated issues: the choice between dc and high frequency ac, and the converter/inverter topology to be used at the power source. The relative merits of dc and ac distribution are discussed. Specific converter and inverter topologies are identified and analyzed in detail for the purpose of detailed comparison. Finally, specific topologies are recommended for use in dc and ac systems.

Stuart, Thomas A.↗
DOE OSTI2023

Multi-Fidelity Gaussian Process for Distribution System Voltage Probabilistic Estimation with PVs

The increasing penetration of behind-the-meter PVs causes challenges to maintain voltage security due to the lack of distribution system visibility. This paper proposes a nonlinear autoregressive Gaussian process (NARGP) approach to fuse limited number of SCADA/AMI data together with historical pseudo measurements for distribution node voltage probabilistic estimation. The high-fidelity SCADA data are fused with the low-fidelity AMI and pseudo measurements by the autoregressive algorithm embedded in the Gaussian process. This allows us to use multi-fidelity data to achieve entire distribution system voltage visibility. Numerical results carried out on the IEEE 123node system demonstrate that the NARGP method is able to obtain high accuracy in estimating bus voltage and quantifying estimation uncertainties as compared to other approaches.

distribution system estimation↗
DOE OSTI2021

Environmental control and air distribution system and method of using the same

An indoor environmental control and air distribution system for a building includes: an air handling unit; a manifold connected to the air handling unit having a chamber formed by a plurality of walls and a plurality of orifices formed through at least one of the walls; air distribution conduits each independently having a first end connected to the orifices of the manifold and a second end extending out from the manifold into different zones throughout the building; and an airflow modulating device having one or more airflow regulating dampers independently configured to move into at least two positions in which each position provides a different percentage of total air volume to each air distribution conduit. A method of using the indoor environmental control and air distribution system is also included.

Poerschke, Andrew↗
DOE OSTI2024

Environmental control and air distribution system and method of using the same

An indoor environmental control and air distribution system for a building includes: an air handling unit; a manifold connected to the air handling unit having a chamber formed by a plurality of walls and a plurality of orifices formed through at least one of the walls; air distribution conduits each independently having a first end connected to the orifices of the manifold and a second end extending out from the manifold into different zones throughout the building; and an airflow modulating device having one or more airflow regulating dampers independently configured to move into at least two positions in which each position provides a different percentage of total air volume to each air distribution conduit. A method of using the indoor environmental control and air distribution system is also included.

Poerschke, Andrew↗
NASA NTRS1983

Fault tolerant distributed systems using Ada

This paper discusses the use of Ada on distributed systems in which failure of processors has to be tolerated. It is assumed that communication between tasks on separate processors will take place using the facilities of the Ada language, primarily the rendezvous. It is shown that there are numerous aspects of the language which make its use on a distributed system very difficult. The issues are raised from the desire to be able to recover, reconfigure, and provide continued service in the presence of hardware failure. For example, if a rendezvous takes place between two tasks on different processors, failure of the processor executing the serving task will cause the calling task to be permanently suspended because the rendezvous will never end. Extensive modifications to the execution support required for Ada are proposed which provide all the necessary facilities for programs written in Ada to withstand arbitrary processor failure. Mechanisms are suggested to allow processor failure to be detected and for tasks which would be permanently suspended to be released. Provided the required program structures are used, continued processing can be provided.

Knight, J. C.↗
NASA NTRS1991

Building a generalized distributed system model

A modeling tool for both analysis and design of distributed systems is discussed. Since many research institutions have access to networks of workstations, the researchers decided to build a tool running on top of the workstations to function as a prototype as well as a distributed simulator for a computing system. The effects of system modeling on performance prediction in distributed systems and the effect of static locking and deadlocks on the performance predictions of distributed transactions are also discussed. While the probability of deadlock is considerably small, its effects on performance could be significant.

Mukkamala, Ravi↗
DOE OSTI2021

Multi Time-scale Imputation aided State Estimation in Distribution System

With the transition to a smart grid, we are witnessing a significant growth in sensor deployments and smart metering infrastructure in the distribution system. However, information from these sensors and meters are typically unevenly sampled at different time-scales and are incomplete. It is critical to effectively aggregate these information sources for situational awareness. In order to reconcile the heterogeneous multi-scale time-series data, we present a multi-task Gaussian process framework. This framework exploits the spatio-temporal correlation across the time-series data to impute data at any desired timescale while providing confidence bounds on the imputations. The value of the imputed data for distribution system operation is illustrated via a matrix completion based state estimation strategy. Results on the IEEE 37 bus distribution system reveals the superior performance of the proposed approach relative to linear interpolation approaches.

Dahale, Shweta↗
DOE OSTI2025

Deep Reinforcement Learning for Distribution System Operations: A Tutorial and Survey

Here, the rapid evolution of modern electric power distribution systems into complex networks of interconnected active devices, distributed generation (DG), and storage poses increasing difficulties for system operators. The large-scale integration of distributed energy resources (DERs) and the rapid exchange of measurement data via communication networks present major opportunities for advancing grid operations but also introduce greater uncertainty, higher data dimensionality, more complex network and device models, and challenging control and optimization problems. Deep reinforcement learning (DRL) algorithms are promising in addressing these challenges. However, they have not been effectively adapted for power systems applications, requiring extensive customization for implementation and evaluation. This has resulted in reproducibility challenges and a steep learning curve for researchers new to applying DRL algorithms to the power systems domain. To bridge these gaps, this tutorial aims to serve as a valuable resource for researchers interested in exploring learning-based algorithms to operate active power distribution networks. Specifically, this work presents a generalized process for translating sequential decision-making problems in power distribution systems into Markov decision process (MDP) formulations, illustrated through concrete grid service examples. Additionally, we introduce a simple environment design strategy to develop and evaluate example DRL algorithms for distribution system applications, complete with an included code repository to guide users through environment construction.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Decision-Dependent Uncertainty-Aware Distribution System Planning Under Wildfire Risk

The interaction between power systems and wildfires can be dangerous and costly. Distribution grids can be liable for the outbreak of wildfires during extreme weather. In wildfire-prone areas, investment planning should consider the impact of operational actions on wildfire-related uncertainties affecting line failure likelihood. Here, in this case, endogenous-based uncertainty modeling should comprise the backbone of the investment planning model viz-a-viz the inability of standard exogenous-based uncertainty modeling. Therefore, we propose a decision-dependent uncertainty (DDU) aware methodology to optimize investment portfolios for distribution systems, considering that high power-flow levels in high-threat areas can ignite wildfires and increase line failure probability. The methodology identifies the best combination of upgrades (new lines, hardening existing lines, and placing switching devices). Methodologically, we propose a two-stage distributionally robust planning optimization problem with DDU that considers the distribution system's multiperiod operation. The first stage determines optimal switching actions and line investments, and the second stage evaluates the worst-case expected operational cost under a DDU framework designed to account for the endogenous impact of power-flow levels and hardening investment decisions in the line failure probabilities. An iterative method is tailored to handle the problem and numerical experiments demonstrate a more prepared grid to deal with wildfire risk.

Power systems investment planning↗
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)↗