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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Multi-modality deep learning for pulse prediction in homogeneous nonlinear systems via parametric conversion

In this Letter, we introduce FusionNet, a multi-modality deep learning framework designed to predict and analyze output pulses in high-power rare-earth-doped laser systems driving parametric conversion in homogeneous guided nonlinear media. FusionNet integrates temporal, spectral, and physical experimental conditions to model ultrafast nonlinear phenomena, including parametric nonlinear frequency conversion, self-phase modulation, and cross-phase modulation in homogeneous guided systems such as gas-filled hollow-core fibers. These systems bridge physical models with experimental data, advancing our understanding of light-guiding principles and nonlinear interactions while expediting the design and optimization of on-demand high-power, high-brightness systems. Our results demonstrate a 73% reduction in prediction error and an 83% improvement in computational efficiency compared to conventional neural networks. This work establishes a new paradigm for accelerating parametric simulations and optimizing experimental designs in high-power laser systems, with further implications for high-precision spectroscopy, quantum information science, and distributed entangled interconnects.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Islanding Detection in Rural Distribution Systems

This paper summarizes the literature on detection of islanding resulting from distributed generating capabilities in a power distribution system, with emphasis on the rural distribution systems. It is important to understand the legacy technology and equipment in the rural distribution electrical environment due to the growth of power electronics and the potential for adding the new generations of intelligent sensors. The survey identified four areas needing further research: 1. Robustness in the presence of distribution grid disturbances; 2. the future role of artificial intelligence in the islanding application; 3. more realistic standard tests for the emerging electrical environment; 4. smarter sensors. In addition, this paper presents a synchro-phasor-based islanding detection approach based on a wireless sensor network developed by the University of Texas at Austin. Initial test results in a control hardware-in-the-loop (CHIL) simulation environment suggest the effectiveness of the developed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Measurement placement in electric power transmission and distribution grids: Review of concepts, methods, and research needs

Sensing and measurement systems are quintessential to the safe and reliable operation of electric power grids. Their strategic placement is of ultimate importance because it is not economically viable to install measurement systems on every node and branch of a power grid, though they need to be monitored. An overwhelming number of strategies have been developed to meet oftentimes multiple conflicting objectives. The prime challenge in formulating the problem lies in developing a heuristic or an optimisation model that, though mathematically tractable and constrained in cost, leads to trustworthy technical solutions. Further, large-scale, long-term deployments pose additional challenges because the boundary conditions change as technologies evolve. For instance, the advent of new technologies in sensing and measurement, as well as in communications and networking, might impact the cost and performance of available solutions and shift initially set conditions. Also, the placement strategies developed for transmission grids might not be suitable for distribution grids, and vice versa, because of unique characteristics; therefore, the strategies need to be flexible, to a certain extent, because no two power grids are alike. Despite the extensive literature on the present topic, the focus of published works tends to be on a specific subject, such as the optimal placement of measurements to ensure observability in transmission grids. There is a dearth of work providing a comprehensive picture for developing optimal placement strategies. Because of the ongoing efforts on the modernisation of electric power grids, there is a need to consolidate the status quo while exposing its limitations to inform policymakers, industry stakeholders, and researchers on the research-and-development needs to push the boundaries for innovation. Accordingly, this paper first reviews the state-of-the-art considering both transmission and distribution grids. Then, it consolidates the key factors to be considered in the problem formulation. Finally, it provides a set of perspectives on the measurement placement problem, and it concludes with future research directions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Regional Analysis for an Economically and Environmentally Viable Transition to Heavy-Duty Vehicles with Alternative Powertrains

The transportation sector is responsible for a significant portion of greenhouse gas emissions. Within the sector, truck freight is responsible for a third of the associated emissions. Alternative powertrains are seen as a viable approach to significantly reduce these emissions. Prior to making a large-scale transition, it is important to consider the following questions: will the power grid support a transition to alternative powertrains?; will the transition truly reduce carbon emissions?; and will the transition impose an unnecessary economic burden on companies within the industry? The answer to these questions, however, can vary by geography, maturity/capacity of the energy distribution network or predicted vehicle load. We focus on the latter two questions, investigating the variation in estimated total cost of ownership and carbon emissions across the United States at the zip code level for both heavy-duty battery electric vehicles and heavy-duty fuel cell electric vehicles. As a benchmark, we compare estimated emissions and costs of alternative powertrain vehicles to that of conventional heavy-duty vehicles powered by diesel internal combustion engines. This work highlights areas with electric grids primed for a transition to alternative powertrain vehicles, such as the Pacific Northwest, and areas that require further infrastructure investment in renewables, such as many of the Mountain states, Missouri, and Florida. Additionally, this work illustrates the current advantages in carbon emissions of battery electric vehicles compared to fuel-cell electric vehicles, while providing insights into required regional investments for narrowing the gap.

Goulet, Nate [ORNL] (ORCID:0000000237314965)↗
DOE OSTI2020

Connectivity, Centrality, and Bottleneckedness: On Graph Theoretic Methods for Power Systems

This report provides an introduction to selected graph theoretic topics with pertinence to the structural analysis of electric power grid and communication systems. We focus on methodologies for defining, scoring, and identifying connectivity, spectral, and bottleneckeness properties in graphs, as well as vertex and edge importance measures such as centrality. We apply these measures to power systems and communications graph data, discuss and visualize the results, and comment on computational aspects of these methods. We show that graph theoretic methods can provide useful insights into grid and communication network structure, leading to tools and methods that could be used by electric utility engineers to improve key grid and communication network characteristics, such as resilience and scalability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Deep Learning-Based Dynamic Modeling of Three-Phase Voltage Source Inverters

Inverter-based resource (IBR) models are necessary to analyze modern power system stability and create effective control strategies. Modeling IBRs in converter-rich power systems is crucial, yet challenging due to the lack of commercial information on converter topologies and control parameters. This paper proposes novel convolutional neural network (CNN)–based data-driven techniques for modeling IBRs, addressing adaptability and proprietary concerns without requiring internal system physics knowledge. The proposed method is tested using real grid-tied commercial IBR transient data and demonstrates effectiveness and accuracy. Furthermore, the developed modeling approach is integrated and implemented in the open-source power distribution simulation and analysis tool, GridLAB-D, to illustrate the potentiality of dynamic analysis of large-scale power systems with high IBRs.

deep learning, artificial intelligence↗
DOE OSTI2023

Alternatives to Contour Visualizations for Power Systems Data

Electrical grids are geographical and topological structures whose voltage states are challenging to represent accurately and efficiently for visual analysis. The current common practice is to use colored contour maps, yet these can misrepresent the data. We examine the suitability of four alternative visualization methods for depicting voltage data in a geographically dense distribution system - Voronoi polygons, H3 tessellations, S2 tessellations, and a network-weighted contour map. We find that Voronoi tessellations and network-weighted contour maps more accurately represent the statistical distribution of the data than regular contour maps.

MATHEMATICS AND COMPUTING,POWER TRANSMISSION AND D↗
DOE OSTI2022

Assessment of the Electrical Substation-Grid Testbed with Inside/Outside Devices and Distributed Ledger Technology

The electrical substation-grid testbed was created to integrate the GOOSE and/or DNP (Distributed Network Protocol) messages with time synchronized sources and Distributed Ledger Technology (DLT). The objective was to study the impact of faults and cyber-events at an electrical substation with inside (protective relays) and outside (power meters) substation devices. The electrical substation-grid testbed was based on the design of a 34.5/ 12.47 kV electrical substation (sectionalized bus configuration) with two power transformers, connected to radial power lines and load feeders. The electrical substation-grid testbed was installed at 252 lab space (Advanced Power System Protection), Grid Research Integration and Deployment Center (GRID-C), Oak Ridge National Laboratory. This testbed was created for Task 5, DarkNet project. The electrical substation-grid testbed was created to simulate fault and/or cyber events that could potentially result in damage to the electrical infrastructure. In addition, tests were run that are usually not allowed to be performed in an operational electrical power grid, because these test scenarios could trip breakers and/or generate fault situations that could potentially damage equipment. The number of tests performed in the electrical substation-grid testbed were executed in a better way than in a real electrical substation and/or power grid, because multiple tests could be run in a short period of time, and complex permits, and safety/ schedule restrictions like in a real electrical substation environment were not needed. The electrical substation-grid testbed was created using real measurement, communication, and protection devices that are used by electrical utilities, to have same conditions that we could observe in a real power grid or electrical substation. The electrical substation-grid testbed was based on using a real time simulator and expansion box with amplifiers that were wired to electrical substation-grid devices. This hardware-in-the-loop (HIL) was provided by protective relays, power meters, ethernet switches, remote terminal units, synchronized timing network clock, DLT devices, workstations, and servers. This report includes the design, installation, and assessment of the electrical substation-grid testbed that was similar to an operational electrical substation, integrating the power system protection, communication, and control systems. The results for the electrical substation-grid testbed were based on:• verifying the analog signals for protective relays and power meters, • observing the synchronized time source frame at devices, • authenticating the GOOSE (IEC 61850) and DNP messages from power meters and protective relays, and • verifying the trip conditions of protective relays at fault tests with the power system fault event detection, using DLT devices. For future work, the electrical substation-grid testbed with protective relays and power meters, using DLT and synchronized time source from DarkNet, will be used to study the impact of cyber-events at inside and outside substation devices. Advanced algorithms for detecting cyber-events produced by non-desired protective relay settings will be studied, to improve the detection and reliability of protection, control, and communication systems at power grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Control systems and data management for high-power laser facilities

The next generation of high-power lasers enables repetition of experiments at orders of magnitude higher frequency than what was possible using the prior generation. Facilities requiring human intervention between laser repetitions need to adapt in order to keep pace with the new laser technology. A distributed networked control system can enable laboratory-wide automation and feedback control loops. These higher-repetition-rate experiments will create enormous quantities of data. A consistent approach to managing data can increase data accessibility, reduce repetitive data-software development and mitigate poorly organized metadata. An opportunity arises to share knowledge of improvements to control and data infrastructure currently being undertaken. We compare platforms and approaches to state-of-the-art control systems and data management at high-power laser facilities, and we illustrate these topics with case studies from our community

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Enhancing Active Distribution Systems Resilience by Fully Distributed Self-Healing Strategy

Distributed restoration can exploit smart grid technologies to enhance the resilience of active distribution networks toward a self-healing smart grid. However, the large number of decision variables, especially the binary ones for reconfiguration, bring challenges to developing scalable distributed distribution service restoration (DDSR) strategies. This paper proposes a fully distributed solution procedure based on the alternating direction method of multipliers (ADMM) for mixed-integer programming problems and applies to develop the DDSR framework. The method consists of relax-drive-polish phases, 1) relaxing binary variables, and applying the convex ADMM as a warm start; 2) driving the solutions toward Boolean values through a proximal operator; 3) fixing the obtained binding binary variables and solving the rest of the problem to polish results and achieve a high-quality suboptimal solution. Then, an autonomous clustering strategy and consensus ADMM are integrated with the proposed method to realize the fully distributed cluster-based framework of DDSR. This framework can first determine DER scheduling and switch status for reconfiguration to energize the out-of-service areas from local faults, and then provide the load restoration solution in a distributed manner for total blackouts in large-scale distribution networks. Furthermore, the effectiveness and scalability of the proposed DDSR framework are demonstrated through testing on the IEEE 123-node, IEEE 8500-node, and synthetic 100k-node test feeders.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Optimized V1G and V2G Electric Vehicle Fleet Management and Grid Transaction at Marine Corps Air Station Miramar in San Diego, CA

The overall technical goal of the project was to demonstrate an all-electric bi-directional non-tactical fleet at Marine Corps Air Station (MCAS) Miramar that was integrated and controlled with other distributed energy resources (DERs) (i.e., PV, stationary battery, and building loads) to provide resilience to critical electric loads in the event of grid outages, to minimize charging costs, and to provide economic energy resources to electricity markets. In this project, the specific, technical objectives were: 1. Demonstrate that bi-directional electric vehicles can provide critical complementary services to fixed storage batteries in microgrid applications while performing function as non-tactical vehicles. 2. Demonstrate participation of bi-directional (V2G) and unidirectional (V1G) PEVs for demand management and minimization of charging costs. 3. Demonstrate integration of multiple DERs for grid service participation. US Marine Corps Air Station (MCAS) Miramar in San Diego was the site of this electric vehicle-to-microgrid-utility grid test and demonstration project. Existing microgrid assets in this study included (1) a public works building; (2) a 30-kW rooftop photovoltaic (PV) system and (3) a separate 250 kW carport PV system. In this project, six bi-directional V2G vans were located at the MCAS Miramar’s showcase building-scale microgrid to develop and test technical capabilities that V2G can provide in microgrid applications (e.g., cost reduction and resiliency). These resources provided aggregated demand management and simulated participation in current retail DR programs. The vehicles used in this demonstration were selected because they provided functionality that MCAS Miramar needed, 15 passenger transport and facilities work cargo carrying capacity, and bi-directional charging capability that the research project required. All vehicles in this study were manufactured and distributed by VIA Motors, Inc. There were six vehicles total and each was VIA’s VTRUX eREV V2G model, a modified General Motors Chevrolet 2500 2WD van. Three of the vans were configured as passenger vans and the other three were configured as cargo vans. Each van had an on-board bi-direcrtional inverter/charger, Bel Power Solutions model 350INVCHGT150-120-240-8G nominally rated at +/-15 kW. The VIA van’s charging connector follows the J1772 charging protocol. The bi-directional EVSEs demonstrated in this study were manufactured by Coritech, Inc. Each VGI-80-AC charging station enabled enhanced V2G charging capability to a Clipper Creek CS-100 charging module. The enhanced capabilities included ethernet communication following the SEP2.0 protocol with a distributed energy resource function set and an operator screen displaying real-time SOC, voltage, and current. The VGI-80-AC charging stations are classified as level 2 with a maximum current output of 80 A or effectively 19 kW. The VIA van’s onboard charger limited the charging and discharging power to 15 kW in each direction. A control computer was installed in the EWOC and connected to an existing monitor. The V2G control communication network was a completely stand-alone closed system that did not have any connection to any other networks on the base. A cybersecure remote communication connection was created with a cellular modem, firewall hardware, and a virtual private network configuration.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)

Recent proliferation of distributed energy sources in distribution or sub-transmission systems necessitates close monitoring of these three-phase power grids which typically operate under unbalanced loading conditions. Unlike the transmission systems where the network equations are commonly based on the positive sequence component models, a detailed three phase model will have to be used in implementing network applications for these systems. In the specific case of the state estimator, where measurement and parameter errors may bias the solution, bad data and parameter error detection algorithms should also be incorporated. Implementing the state estimator and error detection algorithms for three-phase systems impose additional computational burden and modifications to the state estimation code. This paper proposes a practical solution to avoid these issues by using synchronized phasor measurements and modal decoupling. The previously developed parameter error detection algorithm based on the normalized Lagrange multipliers (NLM) test is applied to the measurements independently in each mode in parallel, not only saving CPU time but also avoiding new code development for a three-phase estimator. Different parameter error scenarios are created and tested to verify the effectiveness of the proposed error detection approach.

Khalili, Ramtin↗
DOE OSTI2025

Stability Analysis of Parallel Connected Bidirectional WPT System

This paper presents a stability analysis of parallel-connected bi-directional series-series resonant network wireless power transfer (WPT), optimized for Electric Vehicle (EV) charging and vehicle-to-grid (V2G) applications. The study addresses critical stability challenges in systems integrated with diverse distributed energy resources (DERs), including photovoltaics, fuel cells, wind turbines, energy storage systems, and the AC grid. The stability of such integrated DC grid systems is paramount for ensuring reliable operation, particularly under varying power flow conditions and dynamic interactions between parallel WPT systems. The analysis included system impedance characterization, state-space modeling, and open and closed-loop stability evaluations. The results demonstrated that the integration of a robust control architecture effectively mitigates instability risks and supports scalable, efficient operation. This work underscores the converter's adaptability and its potential for large-scale deployment in wireless EV charging infrastructures and integrated DC grid systems.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗
DOE OSTI2020

Using an Advanced Distribution Management System Test Bed to Evaluate the Impact of Model Quality on Volt/VAR Optimization: Preprint

In this paper, we present a test bed for evaluating existing and future advanced distribution management system (ADMS) applications in a realistic laboratory setting, including other utility management systems and field equipment. We present an example of using it to evaluate the impact of the ADMS network model quality on a Volt/VAR optimization (VVO) application. The test bed integrates a commercial ADMS with a real-time simulation model of a utility distribution feeder. Representative power and controller hardware are integrated through hardware-in-the-loop (HIL) techniques. The performance of the ADMS VVO application is also evaluated for different levels of measurement density. Initial results indicate that a higher model quality achieves the highest possible energy savings while avoiding voltage violations, whereas a lower model quality results in increased energy savings but at the expense of more voltage violations.

ADMS↗
DOE OSTI2022

Security-Constrained Unit Commitment for Electricity Market: Modeling, Solution Methods, and Future Challenges

This paper summarizes the technical activities of the IEEE Task Force on Solving Large Scale Optimization Problems in Electricity Market and Power System Applications. This Task Force was established by the IEEE Technology and Innovation Subcommittee to first review the state-of-the-art of the security-constrained unit commitment (SCUC) business model, its mathematical formulation, and solution techniques in solving electricity market clearing problems. The Task Force then investigated the emerging challenges of future market clearing problems and presented efforts in building benchmark mathematical and business models.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Achieving Cyber-Resilience for Power Systems using a Learning, Model-Assisted Blockchain Framework

The secure integration and management of distributed energy resources (DER) and power aggregators in the electric grid requires secure communications and a physics-aware Command and Control (C2) strategy. A Blockchain (BC)-based overlay network was developed to provide a security layer for the existing power grid network that mitigates risks in current and legacy network and C2 protocols. By integrating a Model-Assisted Machine Learning (MAML) framework with a Secure Blockchain Overlay Network (SBON) a defense-in-depth strategy was achieved. In our approach, the MAML framework leveraged a smart contract framework to gather network data and learn the dynamics of DER to develop detection strategies for attacks targeting sensors and actuators used by DER. The MAML framework learned dynamical systems models for individual DERs to detect sensor attacks. For DER we utilized a Digital Twin (DT) to accelerate the learning process for a model resistant to stealthy attacks. The project created DT for PV inverters and BESS. The DTs were coupled with a model-assisted, data-driven learning of DER behavior. Specifically, we evaluated architectures for model-based learning with model-free fine-tuning. Additionally, differential privacy techniques were used to obfuscate data, while still allowing the computation of attack detection results based on obfuscated data. The SBON developed leverages a private permissioned blockchain network orchestrated with the Hyperledger Fabric framework. To connect the cyber world, which orchestrates the blockchain fabric, and the physical world where the power network resides, we developed a system implementation to enable the secure interaction of the physical world and the abstracted blockchain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Assessing Uncertainty in Solar Measurements: Key Findings From NLR's SUNI Application Across 89 Stations

The Solar Uncertainty Integrator (SUNI) study was developed by the National Laboratory of the Rockies (NLR's) to provide a standardized "bulk uncertainty processing" method for solar irradiance data, which are essential for the successful deployment of solar energy systems. This poster provides an overview of key findings from NLR's SUNI application across 89 stations.

14 SOLAR ENERGY↗