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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

High-frequency ac power distribution in Space Station

A utility-type 20-kHz ac power distribution system for the Space Station, employing resonant power-conversion techniques, is presented. The system converts raw dc voltage from photovoltaic cells or three-phase LF ac voltage from a solar dynamic generator into a regulated 20-kHz ac voltage for distribution among various loads. The results of EASY5 computer simulations of the local and global performance show that the system has fast response and good transient behavior. The ac bus voltage is effectively regulated using the phase-control scheme, which is demonstrated with both line and load variations. The feasibility of paralleling the driver-module outputs is illustrated with the driver modules synchronized and sharing a common feedback loop. An HF sinusoidal ac voltage is generated in the three-phase ac input case, when the driver modules are phased 120 deg away from one another and their outputs are connected in series.

Tsai, Fu-Sheng↗
DOE OSTI2020

Quantifying Technical Diversity Benefits of Wind as a Distributed Energy Resource

Distributed energy resources are increasingly used in power distribution systems and microgrids to supply cost competitive power, improve resilience, and provide a host of grid services. Diversifying variable renewable resources (e.g., by combining wind with solar) can increase energy usage efficiency and improve system resilience. However, when grid optimization and resilience studies consider multiple renewable resources, diversity benefits are usually captured only implicitly in the results of location-specific economic optimization. In this paper, metrics are introduced to express the technical value of resource diversity independent of jurisdiction-specific market structures. Specifically, marginal energy usage efficiency metrics are developed to quantify the ability of new distributed generation to produce useful energy and an incremental sustainable ride through metric is developed to express improvement in grid outage ride through capability. While there are economic implications for each of these metrics, the metrics themselves are technically-driven and could be used as components of a technical figure of merit that could be used to inform policy actions, such as development of resource-specific incentives and time-of-use tariff designs. Each of these metrics is demonstrated using balance-of-energy simulations that highlight the benefits of improving resource diversity.

Reiman, Andrew P.↗
NASA NTRS1992

Lessons learned from the Autonomous Power System

The Autonomous Power System (APS) project at the NASA Lewis Research Center is designed to demonstrate the applications of integrated intelligent diagnosis, control and scheduling techniques to space power distribution systems. The project consists of three elements: the Autonomous Power Expert System (APEX) for Fault Diagnosis, Isolation, and Recovery (FDIR); the Autonomous Intelligent Power Scheduler (AIPS) to efficiently assign activities start times and resources; and power hardware (Brassboard) to emulate a space-based power system. The APS project had been through one design iteration. Each of the three elements of the APS project has been designed, tested, and integrated into a complete working system. After these three portions were completed, an evaluation period was initiated. Each piece of the system was critiqued based on individual performance as well as the ability to interact with the other portions of the APS project. These critiques were then used to determine guidelines for new and improved components of the APS system.

Ringer, Mark J.↗
NASA NTRS1998

Verification of Space Station Secondary Power System Stability Using Design of Experiment

This paper describes analytical methods used in verification of large DC power systems with applications to the International Space Station (ISS). Large DC power systems contain many switching power converters with negative resistor characteristics. The ISS power system presents numerous challenges with respect to system stability such as complex sources and undefined loads. The Space Station program has developed impedance specifications for sources and loads. The overall approach to system stability consists of specific hardware requirements coupled with extensive system analysis and testing. Testing of large complex distributed power systems is not practical due to size and complexity of the system. Computer modeling has been extensively used to develop hardware specifications as well as to identify system configurations for lab testing. The statistical method of Design of Experiments (DoE) is used as an analysis tool for verification of these large systems. DOE reduces the number of computer runs which are necessary to analyze the performance of a complex power system consisting of hundreds of DC/DC converters. DoE also provides valuable information about the effect of changes in system parameters on the performance of the system. DoE provides information about various operating scenarios and identification of the ones with potential for instability. In this paper we will describe how we have used computer modeling to analyze a large DC power system. A brief description of DoE is given. Examples using applications of DoE to analysis and verification of the ISS power system are provided.

Karimi, Kamiar J.↗
NASA NTRS1979

Microwave system performance for a solar power satellite during startup/shutdown operations

The paper investigates the system performance and antenna characteristics under startup/shutdown conditions for the high power beam from a solar power satellite. Attention is given to the present microwave system reference configuration together with the dc power distribution system in the solar array and in the antenna. The pattern characteristics for the main beam, sidelobes, and grating lobes are examined for eight types of energizing configurations which include: random sequences, two types of concentric circles, and three types of line strips. In conclusion, it is noted that a proper choice of sequences should not cause environmental problems due to increased microwave radiation levels during the short time periods of energizing and de-energizing the antenna.

Arndt, G. D.↗
NASA NTRS2004

Soft-Fault Detection Technologies Developed for Electrical Power Systems

The NASA Glenn Research Center, partner universities, and defense contractors are working to develop intelligent power management and distribution (PMAD) technologies for future spacecraft and launch vehicles. The goals are to provide higher performance (efficiency, transient response, and stability), higher fault tolerance, and higher reliability through the application of digital control and communication technologies. It is also expected that these technologies will eventually reduce the design, development, manufacturing, and integration costs for large, electrical power systems for space vehicles. The main focus of this research has been to incorporate digital control, communications, and intelligent algorithms into power electronic devices such as direct-current to direct-current (dc-dc) converters and protective switchgear. These technologies, in turn, will enable revolutionary changes in the way electrical power systems are designed, developed, configured, and integrated in aerospace vehicles and satellites. Initial successes in integrating modern, digital controllers have proven that transient response performance can be improved using advanced nonlinear control algorithms. One technology being developed includes the detection of "soft faults," those not typically covered by current systems in use today. Soft faults include arcing faults, corona discharge faults, and undetected leakage currents. Using digital control and advanced signal analysis algorithms, we have shown that it is possible to reliably detect arcing faults in high-voltage dc power distribution systems (see the preceding photograph). Another research effort has shown that low-level leakage faults and cable degradation can be detected by analyzing power system parameters over time. This additional fault detection capability will result in higher reliability for long-lived power systems such as reusable launch vehicles and space exploration missions.

Button, Robert M.↗
DOE OSTI2026

Grid Topology Discovery Algorithm Evaluation of Suitability for Utility Deployment (CRADA 606 Final Report)

This work presents the results of a field-informed demonstration aimed at evaluating the practical suitability of a topology discovery algorithm for utility environments. We demonstrated an algorithm that uses a graph-theory-informed state estimation approach for model selection. In collaboration with Survalent and Peninsula Light Co., the algorithm was applied to real feeder models and field measurements from supervisory control and data acquisition (SCADA) and advanced metering infrastructure (AMI) systems to identify the operational topology of a power distribution system. The demonstration assessed the algorithm’s performance under realistic data conditions, including sparse and noisy measurements, and examined its ability to identify the most likely network configurations. The results confirmed that the approach can effectively narrow down feasible topologies, providing operators with improved situational awareness of network status. Key lessons learned emphasize the need for systematic data validation and strategic sensor placement to enhance observability. These insights inform future deployment strategies and guide refinements for broader adoption in utility operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

A matheuristic for design and dispatch of a utility-connected distributed energy system

Modeling distributed power generation systems often requires complicated mathematical expressions that present challenges for commercial optimization solvers. Here, this paper presents a matheuristic to solve a mixed-integer optimization model that informs decisions regarding the design and dispatch of a utility-connected microgrid. We deploy a genetic algorithm to search the system design space and a linear program to solve the economic dispatch problem. The model is a component of a web tool that requires solutions within a few minutes. Our method yields objective function values within 5% of an exogenously produced optimal in fewer than 30 seconds for 90% of our test cases compared to only 10% of our test cases by a traditional optimization solver in the same amount of time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Towards Robustness Guarantees for Feedback-Based Optimization

Feedback-based online optimization algorithms have gained traction in recent years because of their simple implementation, their ability to reject disturbances in real time, and their increased robustness to model mismatch. While the robustness properties have been observed both in simulation and experimental results, the theoretical analysis in the literature is mostly limited to nominal conditions. In this work, we propose a framework to systematically assess the robust stability of feedback-based online optimization algorithms. We leverage tools from monotone operator theory, variational inequalities and classical robust control to obtain tractable numerical tests that guarantee robust convergence properties of online algorithms in feedback with a physical system, even in the presence of disturbances and model uncertainty. The results are illustrated via an academic example and a case study of a power distribution system.

approximation algorithms↗
DOE OSTI2022

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗
DOE OSTI2025

Weather-Driven Resilience for Distribution Systems

With increasing billion dollar disasters due to weather events, it is of utmost priority for utility and grid operators to maintain and enhance the resilience of distribution grid. Traditionally, such analysis were conducted with reliability metrics alone. However, with increasing complexity of distribution grid and advancements in grid edge resources, evaluating grid resilience is challenging and involves multi-faceted analysis of the impact of weather events on the distribution grid. This presentation provides background, details, and future works in the field of weather-driven resilience for power distribution systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources: Preprint

Integration of a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problem requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs) including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperformed other benchmark controllers regarding computation time without compromising operational performance.

DER↗
DOE OSTI2022

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (control-lable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗
NASA NTRS1989

Development of Ada language control software for the NASA power management and distribution test bed

The Ada language software developed to control the NASA Lewis Research Center's Power Management and Distribution testbed is described. The testbed is a reduced-scale prototype of the electric power system to be used on space station Freedom. It is designed to develop and test hardware and software for a 20-kHz power distribution system. The distributed, multiprocessor, testbed control system has an easy-to-use operator interface with an understandable English-text format. A simple interface for algorithm writers that uses the same commands as the operator interface is provided, encouraging interactive exploration of the system.

Wright, Ted↗
NASA NTRS2006

Power Budget Analysis for High Altitude Airships

The High Altitude Airship (HAA) has various potential applications and mission scenarios that require onboard energy harvesting and power distribution systems. The energy source considered for the HAA s power budget is solar photon energy that allows the use of either photovoltaic (PV) cells or advanced thermoelectric (ATE) converters. Both PV cells and an ATE system utilizing high performance thermoelectric materials were briefly compared to identify the advantages of ATE for HAA applications in this study. The ATE can generate a higher quantity of harvested energy than PV cells by utilizing the cascaded efficiency of a three-staged ATE in a tandem mode configuration. Assuming that each stage of ATE material has the figure of merit of 5, the cascaded efficiency of a three-staged ATE system approaches the overall conversion efficiency greater than 60%. Based on this estimated efficiency, the configuration of a HAA and the power utility modules are defined.

Choi, Sang H.↗