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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Towards Efficient Alternating Current Optimal Power Flow Analysis on Graphical Processing Units

We present a solution of sparse ACOPF analysis on GPU. In particular, we discuss the performance bottlenecks and detail our efforts to accelerate the linear solver, a core component of ACOPF that dominates the computational time. ACOPF solutions of two large-scale systems, synthetic Northeast (25,000 buses) and Eastern (70,000 buses) \cite{birchfield2017tamu-cases} on GPU show promising speed-up compared to CPU based solution using a state-of-the-art solver. To our knowledge, this is the first result demonstrating acceleration of sparse ACOPF on GPUs.

Power grid analysis, GPU↗
DOE OSTI2023

Disjunctive optimization model and algorithm for long-term capacity expansion planning of reliable power generation systems

This paper proposes a new optimization model and algorithm for long-term capacity expansion planning of reliable power generation systems. The model optimizes both investment decisions (e.g., size, location, and time to install, retire and decommission facilities) and operation decisions (e.g., on/off status, operating capacity, and expected power output). It is also able to optimize reserve systems (or backup systems), as well as the main systems, to improve power systems reliability. An impact of operational strategies of generators (i.e., participating in electricity production vs. remaining as idle units during operation) on power systems reliability is considered. Probability of equipment failures and capacity failure states are used to rigorously estimate the power systems reliability depending on design and operation strategies. The optimization model is formulated with Generalized Disjunctive Programming (GDP), which is reformulated as a mixed-integer linear programming (MILP) model using the Hull relaxation. Two reliability-related penalties, such as downtime penalty and unmet demand penalty, are included in the objective function to maximize reliability while minimizing the total net present cost. Furthermore, a bilevel decomposition with tailored cuts is developed to reduce computational times of the multi-scale optimization model. The effectiveness of the proposed model is shown by comparing the results with the results obtained from the expansion planning models that do not explicitly consider reliability. In conclusion, we also show that the proposed bilevel decomposition is computationally efficient for solving large scale problems through 5-years and 10-years planning case studies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Novel Health Assessment Techniques for a Modern Power Distribution System

Distribution systems are large and complex systems that grow over time. When contingencies occur dispatchers, engineers, and executives need to know the answer to the question, "How bad is it?", in order to make timely and meaningful decisions. Therefore, a scalable method to add context to system conditions is needed. In this paper we present novel deviation-based techniques which enable scaled bus voltage and line power measurement deviations to quickly assess local and global health, and lend context to the severity of contingencies. The proposed techniques are demonstrated using simulations of line-to-line, line-to-ground, and three-phases-to-ground fault conditions on an IEEE 33-bus distribution model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Effect of coaxial nozzle wear on catchment efficiency in direct energy deposition built components

Laser based Direct Energy Deposition (DED) systems using metallic powder feedstock are recognized as a promising manufacturing method for their ability to shorten production cycles and create complex part geometries. Components are built by generating a melt pool with a high-power laser beam while material is coaxially injected and left to solidify. An impediment to large scale use of DED lies in poor powder catchment efficiency, the condition in which a portion of injected powder escapes the melt pool resulting in a ratio of decreased printed material mass to mass of supplied feedstock. The wear state of a coaxial nozzle on a DED system within a hybrid manufacturing machine tool has been observed to decrease catchment efficiency over time. Herein this study investigates this effect by adapting flow visualization techniques to an in-situ process monitoring format, the implementation of a Computational Fluid Dynamics (CFD) simulation, and deposition testing. Nozzle geometric defects due to wear are identified and categorized, and the impact of nozzle tip wear, resulting in axial tip reduction, on powder catchment efficiency is proven by multiple calculation methods. A linear correlation between catchment efficiency and powder stream diameter is identified, causing a 15–20% loss in efficiency sustained over incremental nozzle tip reduction up to − 1 mm. These results provide a foundation for further study of wear effects and Zero defect manufacturing solutions for powder fed DED systems.

42 ENGINEERING↗
DOE OSTI2022

Charaterization of Emerging Computing Architectures for Dynamic Simulation of Future Power Grids with Large-Scale Power Electronics

The increasing penetration of power electronics in power grids significantly raises the computing requirements in a real-time (and/or fast) simulation of the power grid. The real-time simulation is an enabler for evaluating controllers, protection systems, new equipment, and twinning. In this paper, emerging computing architectures such as tensor processing units (TPU), neural/neuromorphic processing units (NPU), and quantum processing units (QPU) are introduced and characterized for the real-time (and/or fast) simulation of power electronics-dominated power grids. The metrics and the process to characterize emerging computing architectures to perform real-time (and/or fast) simulations of future power grids with power electronics are discussed. Three of the emerging computing units are characterized based on these metrics and the process developed. This characterization will enable identification and comparison of emerging computing architectures that can perform real-time (and/or fast) simulation of future power grids.

Choi, Jongchan↗
NASA NTRS2018

Evaluation of a Variable Thickness Hybrid Composite Bull Gear

For several years, NASA Glenn Research Center and the U.S. Army Research Laboratory have been investigating hybrid (compositesteel) gear technology for use in vertical lift drive systems. The hybrid gear concept replaces the structural portion of a gear between the shaft and the gear rim with a lightweight carbon fiber composite, in an effort to reduce the overall weight of a gear and increase the drive system power density. An overview of the concept of the hybrid gear design is described in Ref. 1, 2, and 3. The research presented in these references includes both small-scale and large-scale hybrid gear concepts all of which have a constant composite thickness throughout. The design described in this paper is of a variable thickness, such that the composite is thickest at the inner diameter and this thickness is gradually reduced toward the outer diameter. The resulting stair stepped design stems from dropping plies of the braided carbon fiber composite fabric gradually with increased radius. Additionally, the interlock pattern at the inner metallic adapter was adjusted slightly from previous designs to obtain a better stress distribution on the inner metallic adapter. The manufactured variable thickness web was tested both in static torsion tests and operationally in a relevant gearbox environment. The results of these experiments will be presented and compared to a baseline steel configuration.

Rotorcraft Propulsion↗
DOE OSTI2021

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗
NASA NTRS2001

Zero-Boiloff Cryogenic Storage Cryocooler Integration Test

Developments in NASA Glenn Research Center's Centaur work have led to an exciting new cryogenic storage concept being considered for future NASA space missions. With long-duration cryogenic storage, propellants will boil off because of the environmental heating of the tank. To accommodate these losses, extra propellant is required along with larger propellant tanks. Analyses of space transportation concepts show that spacetransfer cryogenic stages with the zero boiloff (ZBO) cryogenic storage concept reduce the stage mass for missions longer than approximately 45 days in low Earth orbit. The ZBO system consists of an active cryocooling system using a cryocooler in addition to traditional passive thermal insulation. Engineers at Glenn analyzed, designed, built, and bench tested a heat exchanger and integration hardware for a large-scale ZBO demonstration for the NASA Marshall Space Flight Center. The heat exchanger, which transfers the heat that enters the tank from the fluid to the cryocooler, must limit the temperature difference across it to limit the cryocooler size and power requirements. With a low temperature difference, the system efficiency is improved. For that temperature difference to be reduced, the thermal conductivity must be as high as possible at liquid hydrogen temperatures, around 25 K (-248 C). In addition, it is important for the heat exchanger to be welded to a stainless steel flange and have enough strength to accommodate piping stress. High-conductivity copper was selected and fabricated, then integrated with the stainless steel piping tee as shown in the cutaway representation. Literature showed that this conductivity might range from 2 to 100 W/cm/K but that is was likely to be around 13 W/cm/K. Unexpectedly, this conductivity was measured to be 23 W/cm/K, which limited the temperature increase along the heat exchanger to just 2 K. This limited temperature increase, compared with the predicted difference of 3.5 K, improves the overall system efficiency by 7.4 percent and limits the expected integration losses to a projected 4 percent with a flight design for liquid hydrogen storage. These results improve the cryocooler integration concept by allowing the cryocooler to operate at a lower input power, or by potentially permitting a smaller cryocooler to be selected.

Plachta, David W.↗
DOE OSTI2022

Future energy infrastructure, energy platform and energy storage

Today fossil energy dominates energy consumption across the world. There has been an increasing momentum to reduce fossil energy consumption and increase renewable energy utilization to more than 70%. Such high penetrations of distributed renewable resources bring large uncertainty and complexity that cannot be easily handled by the current infrastructure. For the last two decades, telecommunication industry has gone through a similar transition from centralized to distributed systems, and more recently to platform approaches, which become the corner stone of today’s vibrant platform economy. Based on telecommunication history, we believe that a platform-based approach, called the energy platform, is a viable solution for addressing the renewable energy challenges. The energy platform consists of an array of computational algorithms, sensing and control technologies for key industry, energy generators and users to jointly manage and control the complex energy infrastructure. It includes the following key components: (1) the hardware and software to generate, store, control and transmit electricity/data (the energy cloud), (2) the digital platforms and tools for key energy producers, digital, service and communication industry to share the assets, participate in and manage the complex infrastructure, and for customers to participate in energy transactions, (3) the transaction platform for new service and business models. Additionally, the energy platform requires breakthroughs in large scale energy storage and many other areas including efficient power electronics, sensors and controls, new mathematical and computational tools, and deep integration of energy technologies and information sciences to control and stabilize such complex chaotic systems.

25 ENERGY STORAGE↗
DOE OSTI2022

Scalable Deposition of NiOxas a Hole Transport Layer for Perovskite Solar Cells on PET Substrates

Transition from laboratory scale fabrication to large scale perovskite fabrication processes remains a challenge. Upscaling perovskite fabrication requires the development of deposition methods that yield uniform charge transport layers at scale. By optimizing ink composition, we have developed a doped nickel oxide hole transport material for uniform large area deposition on a roll-to-roll system with a peak power conversion efficiency of 11.2%.

Armstrong, Peter↗
DOE OSTI2025

Scalable Hybrid Large-Scale dc-ac Grid Analysis Methods (Phase II)

The goals of the project included the identification and evaluation of a voltage source converter multiterminal high-voltage direct current (VSC-MTdc) system architecture suitable for a high amount of power transfer through long transmission lines.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

An overview of the operation architectures and energy management system for multiple microgrid clusters

The emerging novel energy infrastructures, such as energy communities, smart building-based microgrids, electric vehicles enabled mobile energy storage units raise the requirements for a more interconnective and interoperable energy system. It leads to a transition from simple and isolated microgrids to relatively large-scale and complex interconnected microgrid systems named multi-microgrid clusters. In order to efficiently, optimally, and flexibly control multi-microgrid clusters, cross-disciplinary technologies such as power electronics, control theory, optimization algorithms, information and communication technologies, cyber-physical, and big-data analysis are needed. This paper introduces an overview of the relevant aspects for multi-microgrids, including the outstanding features, architectures, typical applications, existing control mechanisms, as well as the challenges.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2001

Large-Scale Mini-Magnetosphere Plasma Propulsion (M2P2) Experiments

Mini-Magnetosphere Plasma Propulsion (M2P2) is an innovative plasma propulsion system that has the potential to propel spacecraft at unprecedented speeds of 50 to 80 km per second with a low-power requirement of approx. 1 kW per 100 kg of payload and approx. 1 kg of neutral gas [fuel] consumption per day of acceleration. Acceleration periods from several days to a few months are envisioned. High specific impulse and efficiency are achieved through coupling of the spacecraft to the 400 km per second solar wind through an artificial magnetosphere. The mini-magnetosphere or inflated magnetic bubble is produced by the injection of cold dense plasma into a spacecraft-generated magnetic field envelope. Magnetic bubble inflation is driven by electromagnetic processes thereby avoiding the material and deployment problems faced by mechanical solar sail designs, Here, we present the theoretical design of M2P2 as well as initial results from experimental testing of an M2P2 prototype demonstrating: 1) inflation of the dipole magnetic field geometry through the internal injection of cold plasma; and 2) deflection of and artificial solar wind by the prototype M2P2 system. In addition, we present plans for direct laboratory measurement of thrust imparted to a prototype M2P2 by an artificial solar wind during the summer of 2001.

Winglee, R. M.↗
DOE OSTI2020

Overcoming Communications Outages in Inverter Downtime Analysis: Preprint

Inverters are often reported to be the highest-impact failure point in PV systems. This importance is belied by the simplistic assumptions about inverter downtime losses used in industrial energy modeling. Energy models often assume the extent of inverter-related losses is limited to 1% of annual production from scheduled inverter preventative maintenance. In reality, inverter-related production losses are much more variable, although data from large-scale surveys of fielded systems are rare. Here we present a method of detecting inverter downtime events and estimating the associated lost production using inverter- and meter-level power data. Because communications outages are of similar frequency to true production outages, the method pays particular attention to distinguishing communications outages from true production outages. The results of applying the method at fleet-scale are presented and discussed.

41 EE - Solar Energy Technologies Office (EE-4S)↗
NASA NTRS1976

Computer systems: What the future holds

Developement of computer architecture is discussed in terms of the proliferation of the microprocessor, the utility of the medium-scale computer, and the sheer computational power of the large-scale machine. Changes in new applications brought about because of ever lowering costs, smaller sizes, and faster switching times are included.

Stone, H. S.↗
DOE OSTI2026

Safe Deep Reinforcement Learning for Active Distribution System Model Predictive Control with EVs and DERs

The temporal and spatial mismatch between PV generation and electric vehicle (EV) charging and discharging may cause voltage violations in active distribution networks. Despite the widespread use of deep reinforcement learning (DRL) in power system optimization and control, it lacks guarantees on constraint satisfaction during both training and deployment. This paper proposes a Lagrangian-based safe DRL approach for model predictive control (MPC) of active distribution systems with large-scale integration of PVs, EVs, and energy storage systems (ESSs). A Transformer-LSTM time-series model is proposed to forecast EV charging demand, which is then formulated as a constraint to ensure charging requirements are met. Using this prediction, a Lagrangian-based safe soft actor-critic (SAC) framework is developed for real-time control in a three-phase unbalanced distribution system, enforcing voltage safety constraints while optimizing the cumulative net reward. By integrating the forecasting model with multi-period constraints, the proposed framework jointly coordinates PV systems, EV charging and discharging, and ESS scheduling within the MPC horizon. Numerical experiments on a modified IEEE 123-bus system with real-world data show that, under a high PV penetration scenario, the proposed method increases the net reward by 30.74% and reduces average voltage violations from 0.0011 p.u. to 0.0002 p.u. compared with standard SAC. Compared with the optimal power flow (OPF) approach, it achieves similar voltage security while yielding lower line losses. It also maintains real-time control capability, reducing operation latency to 53.21 ms per 15-minute control interval. The proposed method remains effective under varying PV/EV penetrations and load conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

2020 Hydrogen and Fuel Cell Technologies Market Report

This report features summaries of relevant hydrogen and fuel cell activity in 2020, consistent with prior annual reports across applications and sectors. However, 2020 was no ordinary year. Despite pandemic hardships, the hydrogen and fuel cell industry not only stepped up to assist with humanitarian and healthcare efforts but saw continued momentum in several growing market sectors with numerous partnerships, initiatives, and investments. Using hydrogen and fuel cell technologies to provide an environmental and economic pathway to clean, reliable power was a key feature of world economic recovery and energy infrastructure plans. Today, hydrogen energy and fuel cell systems are being developed and deployed in a range of stationary power, portable power, and transportation applications around the world. Throughout 2020, there were significant achievements in each sector, building on years of research and development (R&D), field testing, large-scale demonstration projects, and real-world customer experience. The heavy-duty truck market in particular continued to make substantial gains, with new players entering the space and a coalition of companies pledging to produce and deploy more than 100,000 fuel cell trucks in the next two decades. To provide hydrogen for trucks and other end users, larger and larger electrolyzer projects were announced throughout the year. Collectively, there were more than 430 megawatts (MW) of electrolyzer systems either deployed, ordered, or proposed around the world. This 2020 report also provides special “Spotlights” on the collective industry response to the COVID-19 pandemic as well as international commitments and hydrogen strategies, providing overviews of significant activity during and after the initial onset of COVID-19 around the world.

08 HYDROGEN↗
DOE OSTI2024

Wet chemistry-synthesized Fe/mixed ferrite soft magnetic composites for high-frequency power conversion

State-of-the-art soft magnetic (SM) alloy systems such as electrical steels and permalloys exhibit large eddy current losses at high-frequency (kHz range and above), limiting their application in fast switching devices. Eddy current losses can be reduced for metallic alloys through a decrease in characteristic length scale or embedding them in an insulation layer. This work proposes the development of fine-scale core materials consisting of metallic SM nano/microparticles with magnetic, inorganic insulation layers, and their synthesis using a wet chemistry-based, scalable method for high frequency and high-power applications. More specifically, a magnetic ferrite coating (Ni 0.5-x Mn x Zn 0.5 Fe 2 O 4 , x = 0.0–0.5) was applied via deposition of ferrite powder produced using a “wet chemistry-based” co-precipitation method; the ferrite was distributed through the Fe micropowder via either ball milling or ultrasonic mixing. Powder cores were prepared by compaction of the synthesized composites. Relative magnetic permeability and core loss were measured at excitation frequencies to 200 kHz. A core loss of 127 kW/m 3 was measured at excitation frequency of 100 kHz and magnetization of 0.02 T. This value improves on the 199.3 kW/m 3 reported in literature at identical excitation conditions for a compact formed from a composite comprising Fe microparticles coated with low-permeability Ni 0.5 Zn 0.5 Fe 2 O 4 . Ultrasonic mixing resulted in slightly lower core loss than ball milling, possibly because ball milling causes loss-increasing deformation of the Fe micropowder. XRD and SEM were used to observe composite composition and core cross-section microstructure.

36 MATERIALS SCIENCE↗