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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 739 records · Page 41

Revealing the dynamics of ultrarelativistic non-equilibrium many-electron systems with phase space tomography

The description of physical processes with many-particle systems is a key approach to the modeling of numerous physical systems. For example in storage rings, where ultrarelativistic particles are agglomerated in dense bunches, the modeling and measurement of their phase-space distribution is of paramount importance: at any time the phase-space distribution not only determines the complete space-time evolution but also provides fundamental performance characteristics for storage ring operation. Here, we demonstrate a non-destructive tomographic imaging technique for the 2D longitudinal phase-space distribution of ultrarelativistic electron bunches. For this purpose, we utilize a unique setup, which streams turn-by-turn near-field measurements of bunch profiles at MHz repetition rates. To demonstrate the feasibility of our method, we induce a non-equilibrium state and show that the phase-space distribution microstructuring as well as the phase-space distribution dynamics can be observed in great detail. Our approach offers a pathway to control ultrashort bunches and supports, as one example, the development of compact accelerators with low energy footprints.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Current rectification by nanoparticles in bipolar nanopores

Bipolar nanochannels comprising two domains of positively and negatively charged walls along the pore axis are known to rectify current when exposed to an electric potential bias. We find that addition of charged nanoparticles can increase rectification considerably, by approximately one order of magnitude. Two bipolar channel geometries are considered here; their behavior is examined at rest and under the influence of a negative bias and a positive bias, respectively. We do so by relying on a molecular-level model of the electrolyte solution in the channels. The large increase in current rectification can be explained by the inherent electric field that charged nanoparticles generate within the channel. This effect is found to be largely dependent on the pore's geometry, its charge distribution, and the sign of the nanoparticles' charge, thereby offering new opportunities for design of engineered nanopore membrane-nanoparticle systems for energy storage.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Co-simulation Framework for Community-scale Building-grid Integration [SWR-21-75]

Distributed energy resources (DERs), including rooftop solar, energy storage, and flexible loads, are gaining popularity as costs decline and as building owners and utilities realize their benefits. DERs can improve distribution system efficiency, help prevent the need for expensive grid upgrades, and increase the resilience of local communities. However, they can also cause difficulties in grid operations and can require controls to achieve their benefits. To address this challenge, NREL researchers have developed a community-scale solution that assesses the impacts of DERs and their control strategies on a distribution system. The framework has been shown to reduce solar photovoltaic (PV) curtailment to 0%, mitigate the adverse impact of solar variability on the distribution voltage, and provide up to 5-day critical load support during emergency events. Utilizing 5 different modules representing the feeder, buildings, home energy management systems, an aggregator, and a utility controller, NREL expects this simulation technology to play a critical role in the continued integration of DERs. According to the Energy Information Administration (EIA), solar curtailments accounted for 94% of the total energy curtailed in the California Independent System Operator (CAISO) in 2020. By enabling Independent System Operators (ISOs) and utility operators to bring solar curtailments to 0%, the electrical grid can become less dependent on fossil-fueled power generation sources. NREL's co-simulation framework contains five major components: Distribution Feeder Model: describes the distribution feeder topology using OpenDSS, including the locations of all DERs. Residential Building Model: simulates a large number of buildings at a high resolution using OCHRETM. The model is equipped to control equipment based on signals from an external module. The model includes major household appliances such as HVAC and a water heater, non-dispatchable load models, a distributed PV system, and a home battery system. Home Energy Management System: optimizes the controls for the devices in a home using foreseeTM. The control can adjust based on the user preferences including cost, comfort, and convenience. In hierarchical control scenarios, where the houses follow signals from an aggregator, the home energy management system provides a flexibility band with a range of power and follows the dispatch signals received from aggregator. Community-Level Aggregator: solves for optimal energy dispatch based on the flexibility bands received from each home and the grid service signal received from the utility controller. Utility-Level Controller: provides grid signals for voltage control using Distributed Energy Resources (DERs), such as solar systems, in the community.

Balamurugan, Sivasathya Pradha↗

GridDS: Data Science Toolkit for Energy Grid Data

According to the U.S. Energy Information Administration (EIA), the demand for energy is expected to increase 50% by the year 20501. While energy standards, such as the Institute of Electrical and Electronics Engineers (IEEE) Standard 1547, (Basso 2015) and monitoring with wide area management systems (WAMS) (Liu 2017, Zhou 2016) have enabled large scale data collection and storage, the application of this data in mitigating costs associated with increased consumer demand is an ongoing focus for energy research. This ubiquitous data collection presents a promising opportunity for machine learning and data science to improve efficiency of distributed energy resources (DERs). The GridDS software toolkit is designed to leverage advanced metering infrastructure (AMI), outage management systems data (OMS), Supervisory control Data Acquisition (SCADA), and geographic information systems (GIS) to forecast future energy demands and detect incipient grid failures. GridDS is a python software library designed to be modular and generalizable to data recorded by DERs. In adapting to disparate datasets recorded by various WAMS, GridDS provides a range of unique functionality not presently implemented in current WAMS which have highly specific software infrastructure by design. GridDS functionality ranges from data specification and preparation, to training and validation for state of the art machine learning, to interactive data visualization. For data intake, GridDS combines: Pandera: a library for creating data specifications. TimeScaleDB: a postgresSQL database infrastructure for efficient storage of timeseries data. Dataset class: A custom dataset class / interface that ensures modularity between a range of synthetic and live recorded datasets. Is

Ladd, Alexander↗

Cybersecurity for Digital Energy Infrastructure : Trends, Threats, and Cyber-Informed Engineering

This presentation discusses the rise in digital energy infrastructure and associated threats. It covers an in-depth risk assessment of digital energy equipment and provides real world examples of threats, vulnerabilities, and known incidents. Research conducted by INL assessing and addressing these risks follows, concluding with a dive into Cyber-Informed Engineering (CIE) and it's application to digital energy infrastructure, using battery energy storage systems (BESS) as an example.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Inertial Energy Storage for Spacecraft

The feasibility of inertial energy storage in a spacecraft power system is evaluated on the basis of a conceptual integrated design that encompasses a composite rotor, magnetic suspension and a permanent magnet (PM) motor/generator for a 3-kW orbital average payload at a bus distribution voltage of 250 volts dc. The conceptual design, is referred to as a Mechanical Capacitor. The baseline power system configuration selected is a series system employing peak-power-tracking for a Low Earth-Orbiting application. Power processing, required in the motor/generator, provides potential alternative that can only be achieved in systems with electrochemical energy storage by the addition of power processing components. One such alternative configuration provides for peak-power-tracking of the solar array and still maintains a regulated bus, without the expense of additional power processing components. Precise speed control of the two counterrotating wheels is required to reduce interaction with the attitude control system (ACS) or alternatively, used to perform attitude control functions.

Rodriguez, G. E.↗

Center for High-Efficiency Electrical Technologies for Aircraft (CHEETA)

The aeronautics industry has been challenged on many fronts to increase efficiency, reduce emissions, and decrease dependency on carbon-based fuels. With subsonic transports serving as the dominant contributor to the fuel consumption and carbon footprint of global aviation, the need for environmentally-responsible transportation has been met with a boom of research in the field of aircraft propulsion electrification across industry, government, and academic organizations. However, adoption of electrified propulsion systems for large commercial aircraft today is unattainable, due to the lack of motors and power electronics appropriately sized for these vehicles, high weight requirements of conventional electrical energy storage systems, and new principles required to design these classes of aircraft. The mission of the Center for High-Efficiency Electrical Technologies for Aircraft (CHEETA) program is to develop, mature, and design disruptive technologies for electric commercial aviation. The associated technologies being researched include distributed aero-propulsion system integration, high-efficiency electrochemical power conversion, flight-weight electric machines and power electronics, materials and systems for superconducting high-efficiency power transmission, and methods for complex system integration and optimization. Additionally, the current program is investigating the use of unconventional energy storage and power generation architectures, such as liquid hydrogen fuel and high-efficiency fuel cell systems. The research program provides a direct line-of-sight to not only achieving, but potentially even exceeding the aviation community goals for transition to alternative propulsion and energy through convergence of various novel technologies. The end result of maturation and integration of these technologies is an aircraft system with a quiet, efficient propulsion system that produces zero carbon dioxide, nitrogen oxides, and particulate matter emissions at the vehicle level.

Koushik Datta↗

Use Cases and Model Development of Thermal Storage Coupling for Advanced Nuclear Reactors

This report discusses the different options for coupling thermal energy storage (TES) systems to advanced nuclear power plants (A-NPPs) in order to enable flexible and hybrid plant operation. An advanced light-water reactor (ALWR) and a high-temperature gas-cooled reactor (HTGR) were selected as the initial use cases for demonstrating a thermally balanced energy storage coupling design for thermal power extraction. Cost functions for the A-LWR were derived from the fully balanced models that were developed based on three different coupling options with three different thermal energy bypass ratios. For the next steps, cost functions for the HTGR will also be derived, and additional nuclear reactors (e.g., a liquid-cooled fast reactor [LFR] or molten-salt reactor [MSR]) will be evaluated for coupling with TES in similar fashion, including the evaluation of their steady-state condition models and cost functions. The models presented herein showcase several design considerations, focusing on optimal deployment methodologies for achieving steady-state operation with minimum disruption to the nuclear power generation cycle. This report presents the results of steady state models developed using Aspen HYSYS®, wherein the thermal energy bypass for an NPP-TES coupling was varied up to 50%. The various components were sized using Aspen Process Economic Analyzer (APEA) and Aspen Exchanger Design and Rating (EDR), when applicable. Cost functions from these models were developed using the latest publicly available data obtained from APEA V11. The current steady-state models and cost functions provide a baseline for additional work focusing on dynamic operation and process optimization by using Idaho National Laboratory (INL)’s Framework for Optimization of Resources and Economics (FORCE) tools to evaluate the technoeconomic viability and transient operations of TES-coupled A-NPPs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Strong and Efficient Consistency with Consistency-aware Durability

We introduce consistency-aware durability or C ad , a new approach to durability in distributed storage that enables strong consistency while delivering high performance. We demonstrate the efficacy of this approach by designing cross-client monotonic reads , a novel and strong consistency property that provides monotonic reads across failures and sessions in leader-based systems; such a property can be particularly beneficial in geo-distributed and edge-computing scenarios. We build O rca , a modified version of ZooKeeper that implements C ad and cross-client monotonic reads. We experimentally show that O rca provides strong consistency while closely matching the performance of weakly consistent ZooKeeper. Compared to strongly consistent ZooKeeper, O rca provides significantly higher throughput (1.8--3.3×) and notably reduces latency, sometimes by an order of magnitude in geo-distributed settings. We also implement C ad in Redis and show that the performance benefits are similar to that of C ad ’s implementation in ZooKeeper.

Computer Science↗

A Neural Network-Based Power Mismatch Elimination Strategy for Integrated Solar and ESS AC/DC Systems (MARS)

The multiport autonomous reconfigurable solar power plant (MARS) is a promising concept for the integration of photovoltaic (PV) and energy storage system (ESS) to the transmission ac grid and a high-voltage direct current (HVdc) link. The presence of PV and ESS in each arm of the MARS results in uneven distribution of active power among different submodules (SMs), thereby leading to unbalanced SM capacitor voltages and potentially compromising the system stability. Moreover, in the case of partial shadings, shaded PV SMs will suffer from decreased power injections causing power mismatch in the MARS system. To address this issue, a neural-network-based power mismatch elimination (NNPME) strategy is proposed in this article. The proposed NNPME strategy optimizes ESS usage and leverages both dc and ac circulating currents to facilitate power transfer among the SMs, arms, and phases of the MARS system. Simulation and control hardware-in-the-loop (cHIL) experiments demonstrate the effectiveness of the proposed NNPME strategy. Compared with the traditional approaches, the proposed NNPME strategy can significantly enhance system efficiency and ensure stable and continuous operation, even in the presence of uneven power distribution within the MARS system.

14 SOLAR ENERGY↗

The Planetary Data System - A solution to data management for the planetary science community

An overview of the first release of the Planetary Data System (PDS) is presented, and some of the challenges encountered during development of the system are described. The principal goals of the PDS are to distribute planetary science data and information about these data to NASA, to provide scientific knowledge to users of these data, and to provide for permanent storage. The current architecture and capabilities of the PDS (Version 1.0) are examined, and some of the special challenges encountered and lessons learned during the application are highlighted. Finally, implications for future versions of the PDS as well as for other science data systems are discussed.

Dobinson, Elaine R.↗

Tracking the Sun: Pricing and Design Trends for Distributed Photovoltaic Systems in the United States (2021 Edition) [Slides]

Berkeley Lab’s annual Tracking the Sun report describes trends among grid-connected, distributed solar photovoltaic (PV) systems in the United States. The latest edition of the report focuses on systems installed through year-end 2020, and is based on data from roughly 2.2 million systems, covering 79% of all distributed PV systems installed nationally through 2020. The report describes trends related to project characteristics, including system size, module efficiencies, prevalence of paired PV with storage, use of module-level power electronics, third-party ownership, mounting configurations, panel orientation, and non-residential customer segmentation ownership. Median installed-price trends, including both long-term and more recent temporal trends at the national and state levels, with comparisons to other recent PV cost and pricing benchmarks as well as to prices reported for other countries. Variability in pricing across individual projects based on system size, state, installer, module efficiency, inverter technology, and non-residential customer type. The report also includes an econometric analysis to estimate the effects of individual drivers on installed prices for host-owned residential systems installed in 2020.

14 SOLAR ENERGY↗

Solar thermal electric power plants - Their performance characteristics and total social costs

The central receiver (power tower) concept as a thermal conversion approach to the conversion of solar energy into electricity is compared to other solar power plant designs which feature distributed solar collection and use other types of solar collector configurations. A variety of solar thermal storage concepts are discussed and their impacts on system performance are assessed. Although a good deal of quantification is possible in a comparative study, the subjective judgments carry enormous weight in a socio-economic decision, the ultimate choice of central power plant being more a social than an economic or technical decision. Major elements of the total social cost of each type of central plant are identified as utility economic costs, R&D funds, health costs, and other relevant social impacts.

Caputo, R. S.↗

Unitized Regenerative Fuel Cell System Dryer-Humidifier Analytical Model Development

A Unitized Regenerative Fuel Cell (URFC) Energy Storage System is being developed at the NASA Glenn Research Center. This URFC system is unique in that it uses regenerative gas dryers/humidifiers that are mounted on the surface of the gas storage tanks that act as the radiators for thermal control of the URFC system. As the gas storage tanks cool down during URFC charging the regenerative gas dryers/humidifiers dry the hydrogen and oxygen gases produced by electrolysis. As the gas storage tanks heat up during URFC discharging, the regenerative gas dryers/humidifiers humidify the hydrogen and oxygen gases used by fuel cell. An analytical model was developed to simulate the URFC system's regenerative gas dryers/humidifiers. The model is in the form of an EXCEL@ worksheet that allows the investigation of the regenerative gas dryers/humidifier performance as a function of time and position within the regenerative gas dryers/humidifiers, as well as other key system variables. Finite Element Analysis (FEA) modeling of the regenerative gas dryers/humidifier and gas storage tank wall was also done to analyze spatial temperature distribution within the regenerative gas dryers/humidifiers and the localized tank wall. Test results obtained from the testing of the regenerative gas dryers/humidifiers in a thermal vacuum environment were used to corroborate the analyses.

Burke, Kenneth A.↗

Processing Raw HST Data With Up-to-Date Calibration Data

On-the-Fly Reprocessing (OTFR) is a collection of data-processing routines that work within the context of the Hubble Space Telescope (HST) pipeline data-flow system. The purpose served by OTFR is to generate, on demand, scientifically useful data products from raw HST data stored in an archive. First, on the basis of the requested final data products, OTFR retrieves the corresponding sets of raw data from the archives. Next, OTFR processes the raw data sets to remove artifacts and to establish proper header and other template information. Finally, the calibration routines appropriate to the specific data sets are invoked to produce the requested data products, and the data products are released to an archive distribution system for transmission to the requesting party. OTFR offers two notable advantages: (1) Inasmuch as calibrated data occupy about 8 times as much storage space as do raw data, by obviating storage of calibrated data, OTFR reduces the storage capacity needed by the archive; and (2) the calibration routines can be updated to give requesters the benefit of the most recent calibrations.

Miller, Warren↗

Decentralized Voltage Control with Peer-to-peer Energy Trading in a Distribution Network

Utilizing distributed renewable and energy storage resources via peer-to-peer (P2P) energy trading has long been touted as a solution to improve energy system’s resilience and sustainability. Consumers and prosumers (those who have energy generation resources), however, do not have expertise to engage in repeated P2P trading, and the zero-marginal costs of renewables present challenges in determining fair market prices. To address these issues, we propose a multi-agent reinforcement learning (MARL) framework to help automate consumers’ bidding and management of their solar PV and energy storage resources, under a specific P2P clearing mechanism that utilizes the so-called supply-demand ratio. In addition, we show how the MARL framework can integrate physical network constraints to realize decentralized voltage control, hence ensuring physical feasibility of the P2P energy trading and paving ways for real-world implementations.

Feng, Chen↗

Fireballs in the Sky: An Augmented Reality Citizen Science Program

Fireballs in the Sky is an innovative Australian citizen science program that connects the public with the research of the Desert Fireball Network (DFN). This research aims to understand the early workings of the solar system, and Fireballs in the Sky invites people around the world to learn about this science, contributing fireball sightings via a user-friendly augmented reality mobile app. Tens of thousands of people have downloaded the app world-wide and participated in the science of meteoritics. The Fireballs in the Sky app allows users to get involved with the Desert Fireball Network research, supplementing DFN observations and providing enhanced coverage by reporting their own meteor sightings to DFN scientists. Fireballs in the Sky reports are used to track the trajectories of meteors - from their orbit in space to where they might have landed on Earth. Led by Phil Bland at Curtin University in Australia, the Desert Fireball Network (DFN) uses automated observatories across Australia to triangulate trajectories of meteorites entering the atmosphere, determine pre-entry orbits, and pinpoint their fall positions. Each observatory is an autonomous intelligent imaging system, taking 1000 by 36 megapixel all-sky images throughout the night, using neural network algorithms to recognize events. They are capable of operating for 12 months in a harsh environment, and store all imagery collected. We developed a completely automated software pipeline for data reduction, and built a supercomputer database for storage, allowing us to process our entire archive. The DFN currently stands at 50 stations distributed across the Australian continent, covering an area of 2.5 million square kilometers. Working with DFN's partners at NASA's Solar System Exploration Research Virtual Institute, the team is expanding the network beyond Australia to locations around the world. Fireballs in the Sky allows a growing public base to learn about and participate in this exciting research.

Day, Brian↗

Storage Enabled Flexibility of Conventional Generation Assets (StorFlex)

The power systems have faced progressively more demanding operational requirements over the last two decades. Several factors contribute to these challenging operating conditions, including load growth, aging infrastructure, increasing penetrations of distributed energy resources (DERs), electrification of the economy, and policy initiatives such as decarbonization. The power system and its components must provide high operational flexibility to mitigate these challenges. For example, the proliferation of intermittent DERs such as wind and solar has increased the need for conventional generation assets like hydropower plants to respond to sudden load-generation imbalances. The higher flexibility requirements for hydropower plants cause more wear and tear, potentially shortening the useful lifespan of hydropower turbines. To reduce the need for hydropower plants to follow sudden changes in the dispatch signal, we investigate their combined operation with the energy storage systems (ESSs; “ESS-based hybridization”). Our analyses focuses on improving the lifespan of hydropower plants through ESS-based hybridization. Wear and tear on hydropower turbines (particularly Francis turbines) is modeled using a loss-of-life concept that is based on damage experienced by the turbine due to various cycles of operation. Then, we show that using ESSs to offset some of the high variation increases the remaining life of the hydropower plants. To demonstrate this, a few modeling tools were developed for this work: (1) a dynamic model for various components of the turbine and its governor; (2) a control strategy that assigns a slow-varying dispatch signal to a hydropower unit versus a fastmoving signal to ESS, such that the overall power request remains the same; and (3) models for the financial analysis to quantify the economic merits of such a framework. We used the models we developed to analyze the dispatch pattern of an actual hydropower plant with a power output of 50 MW and a head height of 152 m. This work showed that ESS-based hybridization could extend the life of the hydropower plant by 5% on average. This extension in life was then used to estimate the economic benefit in terms of cost deferrals associated with hydropower plant maintenance and replacement: on average, $3.6 million. Sensitivity analysis with respect to the size of ESS and cost of turbines was performed to show the variation in benefits over the range of turbine costs and ESS sizes. Crucially, stacking damage reduction and lifetime extension with other ESS value streams such as providing ancillary services could substantially increase the financial benefits of ESS-based hybridization. The higher costs associated with ESS of appropriate size would make more financial sense when multiple value streams are stacked and co-optimized to extract the maximum benefit. This dimension will be explored in future work.

13 HYDRO ENERGY↗