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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 sourcesNASA NTRSDOE OSTI
NASA NTRS1981

The utilization of nonterrestrial materials

The development of research and technology programs on the user of nonterrestrial materials for space applications was considered with emphasis on the space power satellite system as a model of large space systems for which the use of nonterrestrial materials may be economically viable. Sample topics discussed include the mining of raw materials and the conversion of raw materials into useful products. These topics were considered against a background of the comparative costs of using terrestrial materials. Exploratory activities involved in the preparation of a nonterrestrial materials utilization program, and the human factors involved were also addressed. Several recommendations from the workshop are now incorporated in NASA activities.

Source record↗
NASA NTRS1988

Terrestrial implications of mathematical modeling developed for space biomedical research

This paper summarizes several related research projects supported by NASA which seek to apply computer models to space medicine and physiology. These efforts span a wide range of activities, including mathematical models used for computer simulations of physiological control systems; power spectral analysis of physiological signals; pattern recognition models for detection of disease processes; and computer-aided diagnosis programs.

Lujan, Barbara F.↗
NASA NTRS1994

The nature of the compact X-ray source in the supernova remnant G27.4+0.0

High-resolution X-ray imaging data obtained with ROSAT is used to constrain the nature of the central compact source in the supernova remnant G27.4+0.0. Diffuse emission is seen from throughout the approximately 4 min diameter radio shell, while the central source remains unresolved at approximately 3 sec. We combine archival data from the Einstein HRI, IPC, and MPC with the ROSAT HRI data to define the X-ray spectra of the diffuse and point-like emission. The bulk of the shell radiation is consistent with that of a approximately 10(exp 7) K plasma, although a higher temperature component is also suggested by the data; coupled with the remnant's size and distance, we derive an age of between 500 and 2500 yr. The point source has a substantially harder spectrum, with a power-law photon index less than or approximately equal to 1. A search for periodic modulation from the point source yields upper limits ranging from 10%-35% for periods between 0.025 and 1000 s, depending on the assumed pulse shape. No aperiodic variability on timescales of from 10(exp 3) to 10(exp 8) s is required, although a factor of approximately 2 change between the Einstein and ROSAT eras is possible. We show that the point source cannot represent thermal emission from the surface of a young neutron star and is unlikely to be explained as nonthermal, Crab-like X-ray pulses or a small synchrotron nebula. The most likely models involve accretion-powered systems -- either a wind-fed neutron star with a massive companion or a low-mass X-ray binary. In all probability, this is the youngest X-ray binary in the Galaxy.

Helfand, David J.↗
NASA NTRSDate not supplied

Development of an Adaptive Droop Control Method for Interconnected Lunar DC Microgrids Using Power Hardware-in-the-Loop

NASA’s Artemis Program outlines the need for a habitat capable of sustaining human life as well as mining and producing raw materials on the lunar surface. This mission is viewed as a means towards deeper space exploration, with plans for reaching Mars and beyond. Human presence on the moon is not possible without the ability to generate and distribute energy, namely electricity, through a network of energy sources, loads, and power converters called a microgrid. Multiple microgrids can be deployed on the moon based on location and need. Separate microgrids will require interconnection to increase resiliency and reliability given the mission’s high criticality. A method for adaptive control over power converters connecting two dc microgrids is proposed. A simulation is modeled after the lunar power system with two approaches to power converter droop control, allowing for a more flexible and adaptive microgrid architecture. Further experiments are conducted using the control methods in a power hardware-in-the-loop test environment to study the performance of hardware converter control used in this application.

dc microgrid↗
DOE OSTI2020

Modeling Flexible Generator Operating Regions via Chance- constrained Stochastic Unit Commitment

Here, we introduce a novel chance-constrained stochastic unit commitment model to address uncertainty in renewables' production uncertainty in power systems operation. For most thermal generators,underlying technical constraints that are universally treated as "hard" by deterministic unit commitment models are in fact based on engineering judgments, such that system operators can periodically request operation outside these limits in non-nominal situations, e.g., to ensure reliability. We incorporate this practical consideration into a chance-constrained stochastic unit commitment model, specifically by in-frequently allowing minor deviations from the minimum and maximum thermal generator power output levels. We demonstrate that an extensive form of our model is computationally tractable for medium-sized power systems given modest numbers of scenarios for renewables' production. We show that the model is able to potentially save significant annual production costs by allowing infrequent and controlled violation of the traditionally hard bounds imposed on thermal generator production limits. Finally, we conduct a sensitivity analysis of optimal solutions to our model under two restricted regimes and observe similar qualitative results.

42 ENGINEERING↗
DOE OSTI2023

Robust Real-Time Modeling of Distribution Systems with Data-Driven Grid-Wise Observability (Final Technical Report)

The overall objective of this project is to leverage existing and emerging sensor measurements to develop data-driven observability enhancement algorithms as well as robust state estimation and parameter identification techniques to enable real-time grid-wise monitoring and modeling of loads and distributed energy resources (DERs). The project resulted in a holistic framework with the following key components: 1) data-driven and machine learning-based grid-edge visibility enhancement, 2) robust branch-current-based state estimation (BCSE), and 3) robust real-time steady-state and dynamic-state modeling of loads and DERs. The research outcomes have provided utility companies better network visibility, higher-fidelity load/DER models, and more accurate assessment of DERs’ impacts, thus, facilitating the integration of renewable energy sources. The synergistic collaborative project among Iowa State University (ISU), Argonne National Laboratory (ANL), Electric Power Research Center (EPRC), SIEMENS Industry, Alliant Energy, Cedar Falls Utilities (CFU), and Maquoketa Valley Electric Cooperative (MVEC) to leverage the team’s extensive expertise and experience in power distribution systems, state estimation, online modeling and identification, and DER integrations. The proposed frameworks have been verified with industry adopted software and attempted integrated with existing tool wherever possible

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

AI-Based EMT Dynamic Model of PV Systems

Several electromagnetic transient (EMT) dynamic modeling methods are available to model systems like photovoltaic (PV) plants, wind power plants, variable-speed drives, among others. The methods include: (a) physics-based models and (b) data-driven models. The physics-based dynamic models may include high-fidelity switched system model and average-value model that both require the control algorithms included in the models. However, manufacturers typically prefer to provide black-box models to avoid disclosing proprietary. One of the solutions to prevent disclosing control algorithms is the use of data-driven dynamic EMT models of PV systems. In this paper, data-driven dynamic EMT model based on artificial intelligence (AI) algorithms are presented. The AI algorithms evaluated include convolutional neural networks, recurrent neural networks, and nonlinear auto-regressive exogenous model. Automation in generating data and training these models is also discussed in this paper. The results generated by the best AI algorithms have been observed to be greater than 95 % accurate.

Debnath, Suman↗
DOE OSTI2021

Developing a Distributed Trust Model for Distributed Energy Resources

Electric power system operators can manage distribution system reliability by coordinating end customer usage of distributed energy resources. The end customers in this regard are Service Provisioning Customers, who provide their energy resources to a Grid Service Provider, which in turn dispatches large aggregations of distributed energy resources to provide reliable service to the power system.The security of this system relies upon information protection mechanisms, as described in IEEE 2030.5. However, in addition to preventive security measures, a monitoring function is required to ensure trustworthiness. Trust models are a method to detect and respond to both expected and unexpected behavior. Different trust models are required for various types and characteristics of each situation. This paper will describe the topics that must be considered when developing a trust model as it applies to distributed energy resources. The major contribution of this paper is the creation and application of a Distributed Trust Model applied to distributed energy resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

An Adaptive-Importance-Sampling-Enhanced Bayesian Approach for Topology Estimation in an Unbalanced Power Distribution System

The reliable operation of a power distribution system relies on a good prior knowledge of its topology and its system state. Although crucial, due to the lack of direct monitoring devices on the switch statuses, the topology information is often unavailable or outdated for the distribution system operators for real-time applications. Apart from the limited observability of the power distribution system, other challenges are the nonlinearity of the model, the complicated, unbalanced structure of the distribution system, and the scale of the system. To overcome the above challenges, we, in this paper, propose a Bayesian-inference framework that allows us to simultaneously estimate the topology and the state of a three-phase, unbalanced power distribution system. Specifically, by using the very limited number of measurements available that are associated with the forecast load data, we efficiently recover the full Bayesian posterior distributions of the system topology under both normal and outage operation conditions. This is performed through an adaptive importance sampling procedure that greatly alleviates the computational burden of the traditional Monte-Carlo (MC)-sampling-based approach while maintaining a good estimation accuracy. The simulations conducted on the IEEE 123-bus test system and an unbalanced 1282-bus system reveal the excellent performances of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Hardware-based Advanced Electromagnetic Transient Simulation for A Large-Scale PV Plant in Real Time Digital Simulator

Power electronics-based resources, such as high-voltage direct current (HVdc) substations, photovoltaic (PV) plants, wind plants, electric vehicle charging stations, and energy storage systems, are increasingly being integrated within the power grid. Recently, multiple reports have emphasized the necessity for high-fidelity electromagnetic transient (EMT) simulations of these large-scale power electronics-based resources to accurately understand their behavior in power grids. However, performing hardware-based EMT simulations with high-fidelity models for such large power electronics systems is challenging due to the small time-step requirements and the involvement of a large number of states. This paper presents the implementation of hardware-based high-fidelity EMT dynamic model of a large-scale PV plant, accomplished through custom model development using the specific-C language in real-time digital simulator hardware (RTDS) and software (RSCAD).

Choi, Jongchan↗
DOE OSTI2021

Managing Solar Photovoltaic Integration in the Western United States Appendix: Reference and High Solar Photovoltaic Scenarios for Three Regions [Slides]

This slide deck is an appendix to a paper series that examines potential challenges related to planning future power systems with higher solar photovoltaic (PV) penetrations. The series uses the western U.S. power system for these investigations because it is a region the authors and their colleagues have already extensively studied. We are therefore well-suited to analyze even higher PV penetrations and then examine the results in multiple models to determine whether our current approaches are missing key details that only emerge at higher PV penetrations. This deck details the systems underlying those analyses and how they were modeled using the Resource Planning Model (RPM), a capacity expansion modeling tool. We examine both Western Interconnection-wide and regional results for three regions in the Western U.S. with significantly different existing power systems and connections to neighboring regions; this provides a more balanced picture as to how power systems with high PV penetration might emerge in different contexts and what the resulting grid challenges, if any, might be.

14 SOLAR ENERGY↗
DOE OSTI2022

Demonstration of a modeling toolkit for the design of building electrical distribution systems

The deployment of building equipment (e.g., lighting, security) and miscellaneous electrical loads that fundamentally require DC power for operation is increasing. Powering these DC loads has traditionally required an AC/DC converter, but the installation of photovoltaic (PV) and battery energy storage systems that primarily produce DC power eliminates the need for AC/DC converters at each end-device. However, analyzing system energy efficiency and cost for different electrical distribution architectures can be challenging as software tools that support this are not readily available. This paper presents preliminary results from a laboratory verification of the Building Electrical Efficiency Analysis Model (BEEAM) toolkit that was developed to address this gap. Three different eight-luminaire lighting systems comprised of market-available products were designed and modeled: one that used traditional AC distribution, a second that used a hybrid AC -to- centralized DC electrical distribution architecture, and a third that used a hybrid AC -to- distributed DC architecture. Notably, AC/DC conversions are required in all three systems. BEEAM models for LED drivers as well as Power-over-Ethernet (PoE) switches were created using laboratory characterization data. The lighting systems were simulated in Modelica, and the results were compared with each other and physics-based expectations. Simulation results show that PoE system energy efficiency is highly dependent on both device specification (e.g., LED driver and PoE switch efficiency) and system architecture (e.g., PoE switch loading) choices, as expected. For the products and system architectures selected for this study, the two DC systems were found to be less efficient than the AC system over the course of typical operation. In future work, simulation results will be compared with laboratory measurements to validate the usefulness of this software for design, and lighting systems with integrated PV and battery energy storage will be simulated to quantify the energy performance improvements that result from the elimination of some AC/DC converters.

Waghale, Anay S.↗
NASA NTRS1979

Report of the Power Sub systems Panel

Problems in spacecraft power system design, testing, integration, and operation are identified and solutions are defined. The specific technology development problems discussed include substorm and plasma design data, modeling of the power subsystem and components, power system monitoring and degraded system management, rotary joints for transmission of power and signals, nickel cadmium battery manufacturing and application, on-array power management, high voltage technology, and solar arrays.

Source record↗
NASA NTRS1980

Error analysis in the measurement of average power with application to switching controllers

Power measurement errors due to the bandwidth of a power meter and the sampling of the input voltage and current of a power meter were investigated assuming sinusoidal excitation and periodic signals generated by a model of a simple chopper system. Errors incurred in measuring power using a microcomputer with limited data storage were also considered. The behavior of the power measurement error due to the frequency responses of first order transfer functions between the input sinusoidal voltage, input sinusoidal current, and the signal multiplier was studied. Results indicate that this power measurement error can be minimized if the frequency responses of the first order transfer functions are identical. The power error analysis was extended to include the power measurement error for a model of a simple chopper system with a power source and an ideal shunt motor acting as an electrical load for the chopper. The behavior of the power measurement error was determined as a function of the chopper's duty cycle and back EMF of the shunt motor. Results indicate that the error is large when the duty cycle or back EMF is small. Theoretical and experimental results indicate that the power measurement error due to sampling of sinusoidal voltages and currents becomes excessively large when the number of observation periods approaches one-half the size of the microcomputer data memory allocated to the storage of either the input sinusoidal voltage or current.

Maisel, J. E.↗
NASA NTRS1989

Tracing Rays In A Solar Power System

OFFSET is ray-tracing computer code for analysis of optics of solar collector. Code models distributions of solar flux within receiver cavity, produced by reflections from collector. Developed to model mathematically offset solar collector of solar dynamic electric power system being developed for Space Station Freedom. Used to develop revised collector-facet concept of four groups of toroidally contoured facets. Also used to develop methods for tailoring distribution of flux incident on receiver. Written in FORTRAN 77 (100 percent).

Jefferies, Kent↗
NASA NTRS1987

Description of the US Army small-scale 2-meter rotor test system

A small-scale powered rotor model was designed for use as a research tool in the exploratory testing of rotors and helicopter models. The model, which consists of a 29 hp rotor drive system, a four-blade fully articulated rotor, and a fuselage, was designed to be simple to operate and maintain in wind tunnels of moderate size and complexity. Two six-component strain-gauge balances are used to provide independent measurement of the rotor and fuselage aerodynamic loads. Commercially available standardized hardware and equipment were used to the maximum extent possible, and specialized parts were designed so that they could be fabricated by normal methods without using highly specialized tooling. The model was used in a hover test of three rotors having different planforms and in a forward flight investigation of a 21-percent-scale model of a U.S. Army scout helicopter equipped with a mast-mounted sight.

Phelps, Arthur E., III↗
NASA NTRS1993

Communications and control for electric power systems: Power flow classification for static security assessment

This report investigates the classification of power system states using an artificial neural network model, Kohonen's self-organizing feature map. The ultimate goal of this classification is to assess power system static security in real-time. Kohonen's self-organizing feature map is an unsupervised neural network which maps N-dimensional input vectors to an array of M neurons. After learning, the synaptic weight vectors exhibit a topological organization which represents the relationship between the vectors of the training set. This learning is unsupervised, which means that the number and size of the classes are not specified beforehand. In the application developed in this report, the input vectors used as the training set are generated by off-line load-flow simulations. The learning algorithm and the results of the organization are discussed.

Niebur, D.↗
DOE OSTI2024

Cooperation in Transmission Expansion Planning: Enhancing Grid Reliability and Efficiency Under a Changing Climate

Electricity grids are challenged to maintain reliability during more intense and frequent extreme weather events due to climate change. This challenge is exacerbated by multi-sector electrification and power sector decarbonization through increased reliance on variable renewable energy, which necessitates the expansion of transmission infrastructure. However, transmission expansion planning is often complicated by intertwined planning authorities and jurisdictions, and allocation of large capital investment needs. These factors cause authorities to manage transmission investments individually (i.e., only/mostly intraregional planning), which can lead to suboptimal transmission networks. This study investigates the potential benefits of cooperative transmission expansion planning (i.e., both intraregional and interregional planning that optimizes transmission investments across the entire physical system). Using sectoral and economic optimization, and machine learning models, it analyzes the impact of different levels of cooperation among transmission planning regions within U.S. Western Interconnection in 2019 and 2059 via an iterative investment process. Furthermore, it examines the effects of future climate change on transmission cooperation by simulating historical heat waves from 2019 under conditions of 2059. The results indicate that cooperative transmission planning leads to lower wholesale electricity prices, decreased energy outages, and reduced greenhouse gas emissions. However, the advantages of collaboration diminish during widespread heat waves, despite remaining beneficial especially for regions like California Independent System Operator with substantial solar installations. The study underscores the importance of transmission cooperation in reducing costs and enhancing reliability, emphasizing the need for strategic investments in storage to address challenges posed by future extreme weather events with varying spatial scales.

Capacity Expansion Model↗