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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Reinforcement Learning for Intentional Islanding in Resilient Power Transmission Systems

Intentional islanding is the process of identifying and deliberately decomposing the transmission network to form self-sustained islands from an endangered network during disruptions to improve resilience and security. Most existing intentional islanding models are offline resilience decision tools and hence do not provide outage responses in a timely manner. In this paper, a reinforcement learning (RL) based model for intentional islanding is developed, which offers real-time switching control, online deployability, and adaptability to varying system conditions. The intentional islanding process is formulated as a Markov decision process, where the optimal transmission switching policy is learned using the RL approach. The control policy is learned over an environment that encompasses a Power System Simulator for Engineering (PSS/E) model of the transmission network, facilitated by an interface to the standard openAI Gym framework. The proposed RL-based methodology aims to form stable and self-sustainable islands by ensuring voltage stability while reducing the power mismatch in the formed islands. A proximal policy optimization algorithm is designed, which is suitable for controlling the on/off status of the switches with multi-layer perceptron as value and actor networks. The effectiveness of the proposed framework in the self-recovery of the grid by island formation is applied on the modified IEEE 39-bus test network and validated by dynamic simulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Low-cost Manufacturing of Semitransparent CdTe PV for Building Integration

Solar has been demonstrated to be a robust renewable energy source, constituting a significant portion of the United States’ renewable energy portfolio. Despite its growth across residential, commercial, and utility sectors over the past decades, it remains a small fraction of the overall energy infrastructure. Challenges persist in fully harnessing solar power to meet the nation's escalating energy demands. Among these challenges lies the hurdle of efficiently distributing large quantities of solar-generated electricity to densely populated regions with the highest energy needs and costs. Traditional utility-scale arrays demand extensive land, a luxury often unavailable in metropolitan areas. Consequently, installations must be situated at a distance, necessitating additional infrastructure for electricity transmission to service areas. While metropolitan landscapes lack sprawling open spaces suitable for conventional utility-scale solar deployment, they offer a different resource: windows. Semitransparent photovoltaic window technology has the potential to not only bolster the grid's energy capacity, but to also provide HVAC and economic advantages to building owners. However, commercial availability of building-integrated photovoltaic windows remains limited. Silicon based photovoltaics currently dominate the solar market but adapting them for use in windows poses a variety of engineering and economic challenges such as relatively low power density, high costs associated with custom manufacturing, and aesthetic considerations. Addressing these challenges, this project explored the use of laser ablation patterning to manufacture cost-effective, high-efficiency, semitransparent Cadmium Telluride photovoltaic modules. Results showcased the potential of this methodology in developing photovoltaic windows and other innovative semitransparent PV applications. The ablation manufacturing technique demonstrated great versatility in achieving different patterns and levels of visible light transmission, and the power loss due to ablation was nearly directly proportional to the amount of material removed. Furthermore, the manufacturing process for Cadmium Telluride modules already has established advantages in material and energy efficiency, and the conversion of a standard submodule to semitransparent essentially requires a single additional process step, ensuring scalability. It is important to note that during this work, Toledo Solar experienced substantial organizational upheaval stemming from a lawsuit with First Solar. An external investigation led the board of directors to remove and replace the previous management team, and several other members of the staff elected to depart as well, including the then acting Principle Investigator on this project. The remaining Toledo Solar team attempted to recover from the disruption and deliver on the remaining tasks, but upon its own review, the Department of Energy ruled the project in default and terminated the contract in December 2023.

14 SOLAR ENERGY↗
DOE OSTI2023

Final Technical Report Wireless Microsensors System for Monitoring Deep Subsurface Operations

This final technical report describes the main findings of the project Wireless Microsensors System for Monitoring Deep Subsurface Operations (FE0031850). The project was part of the U.S. Department of Energy National Energy Technology Laboratory FOA 1998 program to develop new sensor systems for direct observation of parameters associated with CO2 injection and to provide data collection without being disruptive to operations. The overall DOE program was aimed at developing and validating innovative transformational sensor systems, amenable for integration with autonomous intelligent monitoring systems, that are capable of being deployed within the casing annulus and do not have casing perforation or wires/cables in the annulus for installation, power supply, or data transmission needs. Project accomplishments included 1) design and fabrication of a wireless downhole sensor system to monitor parameters for CO2 storage, 2) field testing of the sensor system in two legacy oil & gas wells, and 3) development of an analysis approach that validates the measurements and demonstrates the application of the technology to depict CO2 movement in the subsurface. The project leveraged new sensor technologies along with specialized wellbore telemetry, deployment, and analysis methods designed to address the challenges and risks related to CO2 storage in the subsurface. Results from field testing were a mixture of successes and challenges. The temperature sensor rings, installation procedures in legacy oil & gas wells, wireless powering demonstration, automated data collection, and material compatibility were successful. The wireless data transfer through cement to the wellhead via the sensor relays was not functional beyond the first relay. Consequently, work in the last year of the project included some additional testing of data transmission through different materials along with modeling and analysis of field data for CO2 monitoring applications. This work suggested there are options like polymer cements and open hole annuli that may allow point-to-point transmission along the borehole. The techno-economic analysis suggests that the sensor system is ~40% less expensive than fiber optic distributed temperature system. Modeling of CO2 storage applications suggests temperature can provide an indicator of CO2 saturation but would be best combined with pressure sensors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Dynamic Interference Management for UAV-Assisted Wireless Networks

Here, we investigate a transmission mechanism aiming to improve the data rate between a base station (BS) and a user equipment (UE) through deploying multiple relaying UAVs. We consider the effect of interference incurred by another established communication network, which makes our problem challenging and different from the state of the art. We aim to design the 3D trajectories and power allocation for the UAVs to maximize the data flow of the network while keeping the interference on the existing communication network below a threshold. We utilize the mobility feature of the UAVs to evade the (un)-intended interference caused by (un)-intentional interferers. To this end, we propose an alternating-maximization approach to jointly obtain the 3D trajectories and the UAVs transmission powers. We handle the 3D trajectory design by resorting to spectral graph the power allocation through convex optimization techniques. We also approach the problem from the intentional interferer’s perspective where smart jammers chase the UAVs to effectively degrade the data flow of the network. We also extend our work to the case for multiple UEs. Finally, we demonstrate the efficacy of our proposed method through extensive simulations.

42 ENGINEERING↗
DOE OSTI2026

In situ quantum verification of polarization-stabilized optical channels

The active stabilization of polarization channels is a task of growing importance as quantum networks move to deployed demonstrations over existing fiber infrastructure. However, the uniquely strict requirements for high-fidelity qubit transmission complicate the extent to which classical solutions may apply to future quantum networks, particularly in terms of recognizing noise sources present in low-flux, nonunitary channels. Here we introduce an in situ benchmarking approach that augments a classical polarization tracking system, limited to unitary correction, with simultaneously transmitted quantum light for ancilla-assisted process tomography of the full quantum map. Implemented in a quantum local-area network, our method uses the reconstructed map both to validate the classical compensation and to expose noise sources it fails to capture. A sliding measurement window that continuously updates the estimated quantum process further increases sensitivity to rapid channel fluctuations. Our results should unlock new opportunities for in situ channel characterization in quantum-classical coexistence networks.

Stevens, Matthew L [Arizona State University]↗
DOE OSTI2024

A new HVdc Substation Architecture with Higher Power Transfer Capability

The power transferred through high voltage direct current transmission (HVdc) systems is increasing with increased resilience and reliability needs as well as large scale deployment of renewable energy systems. In this paper, a new HVdc substation (SS) architecture with higher power transfer capability is proposed. The HVdc converters or valve groups (VG) are connected in series and parallel fashion such that the total power rating of the SS is increased. The control challenges associated with such SS architecture are identified and appropriate control modifications are proposed. The same is verified through PSCAD based simulations.

Jaldanki, Sreenivasa↗
NASA NTRS1993

Waves in space plasma dipole antenna subsystem

The Waves In Space Plasma (WISP) flight experiment requires a 50-meter-long deployable dipole antenna subsystem (DASS) to radiate radio frequencies from the STS Orbiter cargo bay. The transmissions are to excite outer ionospheric plasma between the dipole and a free-flying receiver (Spartan) for scientific purposes. This report describes the singular DASS design requirements and how the resulting design satisfies them. A jettison latch is described in some detail. The latch releases the antenna in case of any problems which might prevent the bay doors from closing for re-entry and landing of the Orbiter.

Thomson, Mark↗
NASA NTRS1994

Pre-Departure Clearance (PDC): An Analysis of Aviation Safety Reporting System Reports Concerning PDC Related Errors

Airlines operating in the United States are required to operate under instrument flight rules (EFR). Typically, a clearance is issued via voice transmission from clearance delivery at the departing airport. In 1990, the Federal Aviation Administration (FAA) began deployment of the Pre-Departure Clearance (PDC) system at 30 U.S. airports. The PDC system utilizes aeronautical datalink and Aircraft Communication and Reporting System (ACARS) to transmit departure clearances directly to the pilot. An objective of the PDC system is to provide an immediate reduction in voice congestion over the clearance delivery frequency. Participating airports report that this objective has been met. However, preliminary analysis of 42 Aviation Safety Reporting System (ASRS) reports has revealed problems in PDC procedures and formatting which have caused errors in the proper execution of the clearance. It must be acknowledged that this technology, along with other advancements on the flightdeck, is adding more responsibility to the crew and increasing the opportunity for error. The present study uses these findings as a basis for further coding and analysis of an additional 82 reports obtained from an ASRS database search. These reports indicate that clearances are often amended or exceptions are added in order to accommodate local ATC facilities. However, the onboard ACARS is limited in its ability to emphasize or highlight these changes which has resulted in altitude and heading deviations along with increases in ATC workload. Furthermore, few participating airports require any type of PDC receipt confirmation. In fact, 35% of all ASRS reports dealing with PDC's include failure to acquire the PDC at all. Consequently, this study examines pilots' suggestions contained in ASRS reports in order to develop recommendations to airlines and ATC facilities to help reduce the amount of incidents that occur.

Montalyo, Michael L.↗
DOE OSTI2025

Edge AI-Enhanced Traffic Monitoring and Anomaly Detection Using Multimodal Large Language Models

This paper addresses the challenge of traffic monitoring and incident detection in remote areas, utilizing multimodal large language models (LLMs) deployed on edge AI devices. The key novelty of the LLM is to convert real-time video streams into descriptive texts, enabling low-bandwidth transmissions and reliable detection of anomalies and incidents in environments of intermittent connectivity. The model is developed based on fine-tuning open-source LLMs and extending it with multi-modal capabilities to analyze video frames. Our work also involves deploying this model on edge devices such as Nvidia IGX Orin and is planned to be tested in realistic environments in future work. The methodology includes data set curation, iterative model fine-tuning and compression, and hardware-based optimization. This approach aims to enhance traffic safety and response speed in remote areas, marking a significant advancement in the application of AI for traffic monitoring and safety management.

Peruski, Ryan [University of Tennessee, Knoxville ↗
NASA NTRSDate not supplied

Segmented Solid Surface Reflector Concentrically Stacked With Tubular Shape Memory Composite Hinges

A new architecture for solid surface reflector antennas scalable to sizes greater than 10 m is presented. The design uses compact, light, and simple advanced deployable structures to create sub-reflectors that can be assembled in space into larger units using a robotic arm. The seven-panel hexagonal sub-reflector is divided into hexagonal panels that stack concentrically and vertically. The central panel is connected to each side panel on the back side by a pair of tubular shape memory composite hinges that enable the required deployment kinematics with controlled dynamics. A secondary mechanism closes the interpanel gap. The focus of the paper is on the development of the sub-reflector elements, namely the tubular hinges that use embedded heaters and sensors for triggering and control, the actuation mechanisms, and the lightweight sandwich construction reflector panels. A parametric study using finite element analyses was conducted to assess how design features of the hinge affect its stowage and deployment dynamics. The preliminary component fabrication and testing results for the two-panel assembly breadboard model are outlined. Finally, the results of the test campaign with the brassboard reflector model are presented. A comparison of deployed reflector surface deviation between the measured surface after the stowage and deployment process and the pre-test scans and the nominal surface revealed root mean square errors of less than 1 mm, as required by X-band radiofrequency transmission.

gravity offloading↗
NASA NTRS2004

CHEM-Based Self-Deploying Spacecraft Radar Antennas

A document proposes self-deploying spacecraft radar antennas based on cold hibernated elastic memory (CHEM) structures. Described in a number of prior NASA Tech Briefs articles, the CHEM concept is one of utilizing open-cell shape-memory-polymer (SMP) foams to make lightweight structures that can be compressed for storage and can later be expanded, then rigidified for use. A CHEM-based antenna according to the proposal would comprise three layers of microstrip patches and transmission lines interspersed with two flat layers of SMP foam, which would serve as both dielectric spacers and as means of deployment. The SMP foam layers would be fabricated at full size at a temperature below the SMP glass-transition temperature (Tg). The layers would be assembled into a unitary structure, which, at temperature above Tg, would be compacted to much smaller thickness, then rolled up for storage. Next, the structure would be cooled to below Tg and kept there during launch. Upon reaching the assigned position in outer space, the structure would be heated above Tg to make it rebound to its original size and shape. The structure as thus deployed would then be rigidified by natural cooling to below Tg

Sokolowski, Witold↗
DOE OSTI2020

Demand Response Optimization and Management System for Real-TIme (DROMS-RT)

To design and demonstrate DROMS-RT, a highly distributed Demand Response Optimization and Management System for Real-Time (DROMS-RT) power flow control to support large scale integration of distributed renewable generation into the grid. AutoGrid developed a novel control and communications platform to allow highly dispatchable demand response (DR) services in time frames suitable for providing ancillary services to the transmission grid. These services will be substantially less expensive and more efficient than other forms of ancillary services options currently available to manage the intermittency associated with large-scale renewable integration. DROMSRT successfully leveraged Automated Demand Response (ADR) by fundamentally re-thinking the architecture of the DR platform from the ground up and by developing innovative new technologies in a number of areas related to DR. DROMS-RT leveraged the low-cost, open, interoperable DR signaling technology, OpenADR, and low-cost, internet-protocol based telemetry solutions to reduce the cost of hardware. This allowed DROMS-RT to provide dynamic price signals to millions of OpenADR clients. Statistically rigorous signal processing techniques were developed to reliably detect even small load reductions in the presence of noisy baseline profiles. Novel forecasting engines based on modern online machine learning algorithms enabled accurate individualized forecasts for customer loads in the presence of dynamic pricing signals, and a real-time decision engines enabled continuous optimization and optimal dispatch of DR resources across a large portfolio of heterogeneous loads that respond at varying time-scales. Moreover, the real-time optimization conducted by the decision engine can utilize grid physics to maximize load reduction at the transmission system in addition to the distribution sites, for more efficient grid operation. Finally, the Software-as-a-Service (SaaS) availability of the DROMS-RT platform has reduced the cost of deployment and enable participation of small commercial and residential customers in DR who otherwise would not be able to do so.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Design, Deployment, and Characterization of the World’s First Flexible Large Power Transformer

As we know, power transformers are the most critical asset of the transmission network. Although highly reliable, they still can fail prematurely or ultimately retire at the end of their service life. In today’s design practices, transformers are tailored to their specific application and therefore cannot replace each other unless identical. Additionally, they provide minimal support to the grid operation and therefore limit the grid flexibility and resiliency when facing severe conditions. In this presentation, we will introduce the concept of flexible power transformer and demonstrate how one single unit can serve as a spare to multiple units in a given fleet, allow to control the power flow between transformers or lines operating in parallel and ultimately be used to limit subsequent faults in transmission lines. We will also introduce the world’s first prototype in operation, a 60MVA, 165kV flexible autotransformer.

flexible power transformer, autotransformer, varia↗
DOE OSTI2024

Wake Effects in Lower Carbon Future Scenarios

In August 2022, the U.S. Congress passed the Inflation Reduction Act (IRA), which intended to accelerate U.S. decarbonization, clean energy manufacturing, and deployment of new power and end-use technologies. The National Renewable Energy Laboratory has examined possible scenarios for growth by 2050 resulting from the IRA and other emissions reduction drivers and defined several possible scenarios for large-scale wind deployment. These scenarios incorporate large clusters of turbines operating as wind farms grouped around existing or likely transmission lines which will result in wind farm wakes. Using a numerical weather prediction (NWP) model, we assess these wake effects in a domain in the U. S. Southern Great Plains for a representative year with four scenarios in order to validate the simulations, estimate the internal wake impact, and quantify the cluster wake effect. Herein, we present a validation of the ”no wind farm” scenario and quantify the internal waking effect for the ”ONE” wind farm scenario. Future work will use the “MID” scenario (more than 8000 turbines) and the “HI” scenario (more than 16,000 turbines) to quantify the effect of cluster wakes or inter-farm wakes on power production.

17 WIND ENERGY↗
DOE OSTI2021

A Multi-physics Computational Investigation of Droplet Pathogen Transport Eminating from Synthetic Coughs and Breathing

In response to the global SARS-CoV-2 transmission pandemic, Sandia National Laboratories Rapid Lab-Directed Research and Development (LDRD) COVID-19 initiative has deployed a multi-physics, droplet-laden, turbulent low-Mach simulation tool to model pathogen-containing water droplets that emanate from synthetic human coughing and breathing. The low-Mach turbulent Eulerian/point-particle Lagrangian methodology directly couples mass, momentum, energy, and species to capture droplet evaporation physics that supports the ability to distinguish between droplets that deposit and those that persist in the environment. Additionally, the cough mechanism is modeled as a pulsed-spray with a prescribed log-normal droplet size distribution. Simulations demonstrate direct droplet deposition lengths in excess of three meters while the persistence of a droplet nuclei entrained within a buoyant plume is noted. Including the effect of protective barriers demonstrates effective mitigation of large-droplet transport. For coughs into a protective barrier, jet impingement and large-scale re-circulation can drive droplets vertically and back towards the subject while supporting persistence of droplet nuclei. Simulations in quiescent conditions demonstrate droplet preferential concentrations due to the coupling between vortex ring shedding and the subsequent advection of a series of three-dimensional rings that tilt and rise vertically due to a misalignment between the initial principle vortex trajectory and gravity. These resolved coughing simulations note vortex ring formation, roll-up and breakdown, while entraining droplet nuclei for large distances and time scales.

42 ENGINEERING↗
DOE OSTI2022

Improved Line Outage Detection in Transmission Systems with Few PMUs

Unlike transmission systems, distribution systems historically lack enough measurements, making their real-time monitoring almost impossible. Recent deployment of diverse types of devices such as phasor measurement units (PMUs), smart meters, solar inverters and weather information sensors opens up new ways of monitoring these systems, with the assistance of customized machine learning (ML) applications. The paper describes a grid-model-informed machine learning (ML) tool which integrates heterogeneous data streams and creates synchronous measurement snapshots to be used by a hybrid robust state estimator (SE) which provides not only accurate state estimates but also real-time feedback for ML model refinement. Improved monitoring performance due to the use of developed computational framework is experimentally observed by simulated scenarios on an electric utility’s distribution system.

Distribution systems, graph learning, machine lear↗
DOE OSTI2023

Strengthening Connections Between Research and Deployment [Slides]

This slide deck provides a high-level review of Clean Cities, Clean Energy to Communities, and Technologists in Communities and the ways these DOE-funded efforts work to translate research into deployment opportunities across the United States through community engagement, industry partnerships, and collaborative project teams.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Data for "Implications of Zoning Ordinances for Rural Utility-Scale Solar Deployment and Power System Decarbonization in the Great Lakes Region".

This dataset includes the Energy Zoning Database and geographic shapefiles used to identify suitable rural areas for utility-scale solar development. Additionally, it contains the input data required for the capacity expansion model, including information on existing electric generators and their associated costs, solar resource potential, and transmission infrastructure data. These datasets collectively support the analysis presented in the paper, ensuring a comprehensive assessment of zoning regulations, land suitability, and the economic and technical feasibility of solar deployment in rural areas.

Owusu-Obeng, Papa Yaw (ORCID:0000000334385183)↗