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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Speed Variation Based Power Regulation Concept for Dynamic Wireless Charging

On-road wireless charging of electric vehicles (EVs) in-motion could potentially reduce range anxiety or battery size with wide-spread deployment. The planning and implementation of such systems are greatly complicated due to their susceptibility to load variation inherent to traffic flow. Here, this paper proposes a method for derisking the potential for traffic slowdowns by compensating for reduced vehicle speed and investigates how implementation may affect system performance. A load modeling case study is presented at 200kW for a mile of high-speed roadway employing speed-based power regulation with results indicating average power usage and maximum car hosting capability can be reduced by 20% and increased by 30% respectively. An 85kHz power electronics model is developed based on designs and prototypes for an 11kW, 190m airgap static system and a 200kW dynamic wireless track. The simulation is validated in the 11kW experimental prototype and modified for 200kW operation to compare with simulated performance. Sensitivity studies are performed in MATLAB/Simulink to evaluate how parameters influence system performance and confirm the capability to reduce output power and maintain efficiency at 11 and 200kW. The static 11kW experimental system operates at 93.6% efficiency and multiple options exist to reduce power while maintaining efficiency greater than 90%. The capability to dynamically modify power output from WPT coils, in an experimentally validated simulation, enables techniques to significantly mitigate load variability due to reductions in vehicle speed.

42 ENGINEERING↗
DOE OSTI2024

Advanced Power Electronics and Electric Machines

The advanced power electronics and electric machines (APEEM) research group at the National Renewable Energy Laboratory (NREL) has developed world-class experimental and modeling capabilities for designing and evaluating efficient and reliable power electronics and electric machines thermal management systems. They also design, fabricate and characterize advanced power electronics packaging, and are developing state-of-health monitoring techniques. These researchers deliver safe, reliable, high performing, power-dense components that allow seamless integration between renewable energy sources, electric transportation, and the grid, helping to make widespread electric vehicle (EV) adoption and greenhouse gas emissions reduction more feasible. This document outlines the group's major capabilities in the areas of power electronics; module development and characterization; thermal modeling and management; thermomechanical reliability analysis of devices, modules, inverters/converters, and electric machines; physics-of-failure-based reliability analysis; and microelectronics. It also overviews the group's state-of-the-art equipment for fluid-based thermal management; thermal measurement & characterization; thermomechanical reliability analysis; micro- and power electronics measurement & characterization; and prototype fabrication, as well as the group's world-class modeling and simulation capabilities.

advanced gate drivers↗
DOE OSTI2024

Understanding Line Losses and Transformer Losses in Rural Isolated Distribution Systems

Rural, isolated power systems in the mainland U.S. and in states like Alaska and Hawaii are powered by assets like diesel generators. These rural, isolated power systems also cannot operate at the higher band of medium voltage (like 69kV). They are primarily in the 12 to 14 kV range to keep the cost of the distribution investments lower. Because of this mid-band medium voltage range, the line losses and distribution transformers losses consume significant diesel consumption (almost 10 percent of the peak load). This work considers one such power system powering an isolated system and presents key findings online losses, and transformer losses. Understanding and documenting the impacts is critical for these communities operating their power systems and take actions to reduce expensive diesel consumption. In this paper, we will present one such typical grid and model it in electromagnetic transients (EMT) domain. We used the tower structure, under ground cabling installation to develop high fidelity models of lines. We also used high fidelity models of distribution transformers to present the no-load losses and full load loses. We will also present technical solutions available commercially off-the-shelf to reduce these losses and reduce diesel consumption. This work will be a primer for communities to understand the technical challenges and to understand the possible solution available to solve such challenges for rural, isolated power system operators.

blackstart↗
DOE OSTI2025

Real-Time Simulation of Solid Oxide Electrolyzers (SOEC) for Dynamic Operability Improvement and Cyber-Physical System Development

As more intermittent-renewable generations are being added to the power grid, solid oxide electrolysis cells (SOEC) must enhance their rapid load transition capabilities to load follow and support grid resilience. At NETL, we developed real-time SOEC models to research SOEC transients during load step changes. The gained insights can be useful for dynamic operability improvement. These real-time SOEC models also established the basis for cyber-physical SOEC hybrid energy systems. (Virtual presentation to the 2025 MILLENNIUM CLEAN and SUSTAINABLE POWER workshop, University of Genoa, Italy)

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

SEAS Communication Engine: An Extensible, Flexible Wrapper for Co-Simulation Agents

When modeling and analyzing the power grid and other large scale systems, researchers often express scenarios as optimization problems and feed them into advanced software solvers. In order to allow multiple solvers to communicate with each other and share data from different domains, the National Renewable Energy Laboratory (NREL) and associated Department of Energy (DOE) labs have developed a software framework called the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS). HELICS allows cosimulation via a collection of client libraries for different languages that can be called from the appropriate optimization software. However, these client libraries do not provide a higher level of abstraction beyond reading and writing data off of the shared HELICS bus. In this paper, we describe a new software library called the SEAS Communication Engine that exposes a higher-level API for running cosimulation problems. The SEAS Engine provides a class-based abstraction on top of the Python HELICS client, in order to allow users to implement their domain-specific cosimulations without needing to interact with core HELICS primitives. This will make adoption of HELICS and cosimulation in general easier, by exposing a simpler API. In the second part of the paper, we validate our library on a collection of different simulation examples, including the canonical IEEE 13 Bus Feeder. Lastly, we demonstrate using the SEAS Engine to directly call domain-specific code written in the Julia programming language. Our hope is that this will serve as a template for easily calling software in different programming languages via the SEAS Engine, thereby avoiding code duplication and complexity.

co-simulation↗
DOE OSTI2024

Adaptive Narrowband Damping for Improving Harmonic Stability of Modular Multilevel Converter

Harmonic instability events between modular multilevel converter (MMC) and ac systems have been widely reported in recent years. To damp harmonic resonance, this paper proposes an adaptive narrowband damping control that automatically programs, adds, and adjusts the damping around the oscillation frequency when an oscillation is detected. First, the paper presents a low-pass filter design for MMC control loops that pushes all negative damping of the MMC impedance down to the medium-frequency range (< ~ 1000 Hz). Then, an adaptive damping control that uses online oscillation detection is proposed, which can automatically configure the narrowband damper to provide positive damping to the MMC around the detected oscillation frequency. In contrast to existing narrowband damping methods, the proposed adaptive narrowband damper dynamically adjusts the damping gain and the width of the damping range based on continuous monitoring of system resonance conditions (e.g., adjust damping gain to zero when the system resonance disappears). Electromagnetic transient simulation results validate the efficacy of the proposed method in two typical MMC-based power systems.

active damping↗
DOE OSTI2024

Adaptive Narrowband Damping for Improving Harmonic Stability of Modular Multilevel Converter: Preprint

Harmonic instability events between modular multilevel converter (MMC) and ac systems have been widely reported in recent years. To resolve it, this paper proposes an adaptive narrowband damping control that automatically programs, adds and adjusts damping around the oscillation frequency when detect the oscillation. The paper first presents a low-pass filter design for MMC control loops, which pushes all negative damping of MMC impedance down to the medium frequency range (< approximately 1000 Hz). This makes narrowband damping can be more targeted and easier to design because multiple harmonic oscillations are avoided. An adaptive damping control that uses online oscillation detection is then proposed, which can automatically configure the narrowband damper to provide damping to the MMC at the detected oscillation frequency. In contrast to existing narrowband damping methods, the proposed adaptive narrowband damper adjusts the damping gain (e.g., to zero when system resonance disappears) and the width of the damping range automatically based on continuous monitoring of system resonance conditions. Electromagnetic transient (EMT) simulation results validate the efficacy of the proposed method in two typical MMC-based power systems.

active damping↗
DOE OSTI2026

Reliable Protection for an Inverter-Based Resources Dominant Grid: Technology Development and Field Demonstration

The project aimed to address the challenges posed by the rapid growth of inverter-based resources (IBR) such as solar, wind, and battery storage, which have fundamentally changed fault behavior, system strength, and protection performance in bulk power systems. Traditional protection schemes, designed for synchronous generator-dominated grids, are inadequate under high IBR penetration. Overall, the project materially advances protection modeling and simulation capabilities needed to maintain reliable grid protection under high IBR penetration. The results build utility confidence in operating power systems safely and reliably across a wide range of generation mixes, supporting grid modernization goals.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Power Analysis of an ePump Applied to the Linear Functions of an Agricultural Planter

Like many other industries, the agricultural industry has recently ex-perienced pressure to reduce vehicle emissions while improving productivity. Electric actuation is perceived as a viable solution to replace or augment hydrau-lic and mechanical actuation. However, electrification presents challenges with regards to linear functions, where hydraulic actuators have advantages in terms of compactness, tolerance to contamination and resistance to shocks. A combined electro-hydraulic actuation architecture can leverage the benefits of both electric and hydraulic actuation, while reducing the drawbacks of both approaches. This work investigates the potential of a centralized electric driven pump (ePump) system powering the pressure-controlled linear functions of an agricul-tural planter, with the goal of improving the operating point of the main supply pump. In this application, the rotary functions are hydraulically actuated, alt-hough such a solution could be applied also to electric rotary actuation. This is accomplished by setting the ePump to boost the pressure supplied by the tractor to the level required by the linear functions. An accumulator is used to stabilize the flow requirements of the linear functions, and control the pressure supplied to the actuators. Two control schemes are proposed for the regulation of the ac-cumulator pressure, one favoring an efficient operating point for the ePump, the other favoring stable steady state operation. A simulation model of the baseline system and proposed system is developed and validated using experimental data from a full-scale machine. Using the vali-dated simulation, both control architectures are then evaluated for improvement in system power consumption and dynamic requirements on the ePump to assess their effectiveness. Both systems demonstrate significant improvement in power consumption over the baseline system, with the best solution improving effi-ciency by 64%.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

A Methodology to Evaluate the Grid Reliability Impact of Oscillations Induced by Large Loads

The rapid growth of hyperscale AI data centers is bringing renewed attention to the reliability risk that sustained forced oscillations pose to bulk power systems, with cyclic computational workloads emerging as a new forcing source. Unlike the broadband, stochastic disturbances from traditional industrial loads such as arc furnaces, AI training and inference facilities can inject large active power swings concentrated at specific frequencies over extended durations - characteristics that existing grid planning practices do not account for. While the North American Electric Reliability Corporation (NERC) has recognized this gap and called for system-level studies of large load interconnections, no standardized methodology exists to screen, simulate, and quantify these risks at the planning stage. This report presents the Risk Assessment Tool for Large Load-induced Events (RATLLE), a Python-based, publicly available script suite developed at the Pacific Northwest National Laboratory to evaluate bulk power system reliability risks from data center-induced oscillations. RATLLE implements a three-module workflow: a screening module that identifies vulnerable interconnection locations and excitable system modes; a simulation module that models cyclic data center load behavior using a commercial positive sequence simulation platform; and an analysis module that computes risk metrics and generates interactive visualization dashboards. The risk metrics, formulated around simulation observables, map oscillation impacts to a three-stage severity scale spanning latent equipment fatigue through imminent cascading failure. The methodology is demonstrated on two Western Electricity Coordinating Council (WECC) system models: a publicly available 240-bus reduced representation and a detailed 2031 Heavy Winter planning case. Case studies illustrate that even modest 50 MW forced oscillations at resonant frequencies can produce wide-area power swings, N-1 security constraint violations, and cascading generator trips through protection actions - outcomes that would not occur under normal operating conditions without oscillations present. The results underscore the need for standardized oscillation impact assessment in large load interconnection studies and provide a reproducible, extensible framework for utilities to adopt or customize within their existing planning workflows.

Biswas, Shuchismita↗
DOE OSTI2024

Flow reversal benchmark of a one-sided heated narrow rectangular channel with CATHARE and RELAP5

Flow reversal in narrow coolant channels can be a crucial phenomenon for the safety of research reactors with a downward nominal flow direction. During a loss of forced flow accident, the downward flow stagnates briefly before transitioning into an upward natural circulation flow. The fuel may be damaged if dryout occurs and threshold fuel and/or cladding temperatures are exceeded. A comprehensive study is provided for flow reversal in narrow rectangular channels by examining experimental data and conducting software model analyses. The literature on flow reversal was reviewed, and selected experimental datasets were used to benchmark against CATHARE and RELAP5 models and also compare the code calculations with each other. The experimental data comes from flow reversal tests conducted with a narrow rectangular channel with one-sided heating. The results were compared with experimental data for successful flow reversal tests and predicted dryout power for dryout conditions. Also, the study examined the effects of the pump coastdown period, inlet liquid temperature, system pressure, and localized pressure drops. The experimental results showed that shorter coastdown periods, reduced pressure drops, and lower coolant inlet temperatures increased the dryout power. However, the system pressure did not noticeably affect the results. The simulation results showed that both CATHARE and RELAP5 agreed with experimental data, capturing the trends of the experimental results. Slight differences between each code calculation, as well as the predicted and measured dryout powers, were attributed to experimental uncertainties and the modeling of physical phenomena such as wall nucleation, interfacial heat transfer, drag coefficients, and critical heat flux. Overall, this study provides an understanding of flow reversal and the prediction capabilities of thermal-hydraulics software models. In conclusion, a future study of the flow reversal benchmark of a narrow rectangular channel with two-sided heating may provide additional valuable insights.

CATHARE↗
DOE OSTI2024

Incorporating energy justice and equity objectives in power system models

Ensuring an equitable energy transition requires models and tools that can account for equity and energy justice goals. Power system models (PSMs) are widely used throughout industry, government, and academia to simulate or optimize the operations and planning of current and future electricity systems under different scenarios, parameter assumptions and policy frameworks. These models are important tools that allow users to understand how the power system may evolve under different future conditions, but importantly, they are also used to inform policy implementation and investment decisions across all aspects of the power system. However, existing models seldom include energy justice considerations and therefore energy justice priorities are not reflected in the policies and other decision-making processes that are informed by these models. The purpose of this review is to provide a framework that energy modelers can draw upon to integrate energy justice and equity goals into PSMs. To this end, 99 papers that examine the intersection of energy justice and power system models are summarized and ten core aspects of the power system that can impact energy justice outcomes, and therefore require new modeling approaches, are identified. This review then establishes key current practices, challenges, and opportunities associated with capturing energy justice considerations in power system models across these ten aspects. This review concludes by proposing four key research directions that should be pursued to improve the representation of energy justice and equity in power system modeling. Finally, this review also addresses challenges raised by United Nations Sustainable Development Goal 7, which aims to ensure affordable energy access to everyone and Sustainable Development Goal 13, which aims to take urgent action to address climate change.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

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↗
DOE OSTI2024

Deep Learning-enhanced Block-Diagram Modeling of Solar Power Systems

Data-driven models of power system inverter-based resources are desired to run simulations faster than with detailed electromagnetic transient models, to hide proprietary design details, to support control system design applications, and to aggregate the effects of distributed energy resources. This paper applies a customized Hammerstein Wiener framework to train block diagram models from thousands of electromagnetic transient simulations or experimental test records. The block diagram models integrate with larger grid simulations as voltagecontrolled current sources or current-controlled voltage sources for several simulators. Guidelines for block architecture and training are presented. Three-phase balanced, three-phase unbalanced, and single-phase examples all achieve an acceptable root mean square error of no more than 0.05 per-unit.

Mcdermott, Thomas E. [Private consulting company]↗
DOE OSTI2026

Scheduler Modeling of Distributed Energy Resources for Providing Ancillary Services

Distribution energy resources (DERs) have been integral components of modern power systems, and their capability to provide grid services has been widely studied. To promote the deployment of these resources in providing grid services in real-world utility operations, this paper proposes a day-ahead scheduler model for a distribution system connected DER plant. A certain amount of generation capacity of this DER plant is reserved for frequency services, and some ancillary services for the distribution system-including peak load reduction, voltage regulation, and power factor control-are integrated into the model. The model is tested on a real-world distribution system. From the simulation results, the energy and reserve schedule of the solar photovoltaic (PV) unit and battery energy storage system (BESS) can be determined, and voltage and power factor are well maintained. Additionally, in order to demonstrate the specific characteristics of the co-located and hybrid operation modes for the PV and BESS, these two modes are analyzed both theoretically and through real-time simulation. Simulation results show that most of PV's variability is transferred to the net power in the co-located mode, whereas it is transferred to the BESS in the hybrid mode. This proposed scheduler model and the comparison of co-located and hybrid modes can provide practical guidance for the applications of DER plant in the real-world utility.

14 SOLAR ENERGY↗
DOE OSTI2026

A Data-Driven Method for Synthetic Extreme Weather Generation and Solar Impact Assessment: Preprint

High-resolution, high-fidelity weather datasets are essential for testing and evaluating the resilience of power systems, particularly under extreme weather conditions. However, existing extreme weather datasets are typically derived from historical events that are localized and may lack the spatial and temporal resolution or scenario diversity needed to test largescale power systems. In this work, we propose a synthetic extreme weather simulation approach capable of generating targeted extreme events, such as hurricanes, using publicly available data sources. Preliminary results demonstrate the impact of a simulated Category 1 hurricane on renewable generation and critical infrastructure in California. The work aims to provide a flexible approach for creating multiple types of extreme weather scenarios across different regions, enabling comprehensive system stress testing, training, and resilience assessment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Efficient Simulation of Cascading Outages Using an Energy Function-Embedded Quasi-Steady-State Model

Here, this paper proposed an energy function-embedded quasi-steady-state model for efficient simulation of cascading outages on a power grid while addressing transient stability concerns. Compared to quasi-steady-state models, the proposed model incorporates short-term dynamic simulation and an energy function method to efficiently evaluate the transient stability of a power grid together with outage propagation without transient stability simulation. Cascading outage simulation using the proposed model conducts three steps for each disturbance such as a line outage. First, it performs time-domain simulation for a short term to obtain a post-disturbance trajectory. Second, along the trajectory, the system state with the local maximum potential energy is found and used as the initial point to search for a relevant unstable equilibrium by Newton's method. Third, the transient energy margin is estimated based on this unstable equilibrium to predict an out-of-step condition with generators. The proposed energy function-embedded quasi-steady-state model is tested in terms of its accuracy and time performance on an NPCC 140-bus power system and compared to a quasi-steady-state model embedding transient stability simulation.

Guo, Zhenping [Univ. of Tennessee, Knoxville, TN (↗