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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Comprehensive Analysis of PINNs for Power System Transient Stability

The integration of machine learning in power systems, particularly in stability and dynamics, addresses the challenges brought by the integration of renewable energies and distributed energy resources (DERs). Traditional methods for power system transient stability, involving solving differential equations with computational techniques, face limitations due to their time-consuming and computationally demanding nature. This paper introduces physics-informed Neural Networks (PINNs) as a promising solution for these challenges, especially in scenarios with limited data availability and the need for high computational speed. PINNs offer a novel approach for complex power systems by incorporating additional equations and adapting to various system scales, from a single bus to multi-bus networks. Our study presents the first comprehensive evaluation of physics-informed Neural Networks (PINNs) in the context of power system transient stability, addressing various grid complexities. Additionally, we introduce a novel approach for adjusting loss weights to improve the adaptability of PINNs to diverse systems. Our experimental findings reveal that PINNs can be efficiently scaled while maintaining high accuracy. Furthermore, these results suggest that PINNs significantly outperform the traditional ode45 method in terms of efficiency, especially as the system size increases, showcasing a progressive speed advantage over ode45.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A Comprehensive Analysis of PINNs for Power System Transient Stability

The integration of machine learning in power systems, particularly in stability and dynamics, addresses the challenges brought by the integration of renewable energies and distributed energy resources (DERs). Traditional methods for power system transient stability, involving solving differential equations with computational techniques, face limitations due to their time-consuming and computationally demanding nature. This paper introduces physics-informed Neural Networks (PINNs) as a promising solution for these challenges, especially in scenarios with limited data availability and the need for high computational speed. PINNs offer a novel approach for complex power systems by incorporating additional equations and adapting to various system scales, from a single bus to multi-bus networks. Our study presents the first comprehensive evaluation of physics-informed Neural Networks (PINNs) in the context of power system transient stability, addressing various grid complexities. Additionally, we introduce a novel approach for adjusting loss weights to improve the adaptability of PINNs to diverse systems. Our experimental findings reveal that PINNs can be efficiently scaled while maintaining high accuracy. Furthermore, these results suggest that PINNs significantly outperform the traditional ode45 method in terms of efficiency, especially as the system size increases, showcasing a progressive speed advantage over ode45.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Digital Real-Time Simulation and Power Quality Analysis of a Hydrogen-Generating Nuclear-Renewable Integrated Energy System

This paper investigates the challenges and solutions associated with integrating a hydrogen-generating nuclear-renewable integrated energy system (NR-IES) under a transactive energy framework. The proposed system directs excess nuclear power to hydrogen production during periods of low grid demand while utilizing renewables to maintain grid stability. Using digital real-time simulation (DRTS) in the Typhoon HIL 404 model, the dynamic interactions between nuclear power plants, electrolyzers, and power grids are analyzed to mitigate issues such as harmonic distortion, power quality degradation, and low power factor caused by large non-linear loads. A three-phase power conversion system is modeled using the Typhoon HIL 404 model and includes a generator, a variable load, an electrolyzer, and power filters. Active harmonic filters (AHFs) and hybrid active power filters (HAPFs) are implemented to address harmonic mitigation and reactive power compensation. The results reveal that the HAPF topology effectively balances cost efficiency and performance and significantly reduces active filter current requirements compared to AHF-only systems. During maximum electrolyzer operation at 4 MW, the grid frequency dropped below 59.3 Hz without filtering; however, the implementation of power filters successfully restored the frequency to 59.9 Hz, demonstrating its effectiveness in maintaining grid stability. Future work will focus on integrating a deep reinforcement learning (DRL) framework with real-time simulation and optimizing real-time power dispatch, thus enabling a scalable, efficient NR-IES for sustainable energy markets.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

MCP-eGridGPT (MCP-Enabled Chatbot with Electrical Power System Analysis and Interactive Visualization Tool) [SWR-25-126]

This software is an advanced chatbot system that integrates the Model Context Protocol (MCP) to provide intelligent electrical power system analysis and automated visualization generation. The system enables users to interact with complex electrical engineering tools through natural language, automatically analyzes power system data for voltage violations and grid health assessment, and generates professional interactive HTML dashboards and reports. Key features include dynamic tool discovery from MCP servers, multi-LLM provider support, intelligent data interpretation using large language models, automated chart generation, and a web-based interface for real-time analysis. The software bridges sophisticated electrical engineering analysis with user-friendly interfaces, making power system diagnostics accessible through conversational AI.

Choi, Seong [National Laboratory of the Rockies (N↗
DOE OSTI2021

An Integrated Transmission-Distribution Co-Simulation for a Distribution System with High Renewable Penetration

Traditionally, transmission and distribution system dynamic simulations are performed independently. However, dynamic co-simulation of transmission-distribution systems can be beneficial in analyzing distribution systems with high penetration of distributed renewable resources. The authors describe a framework for conducting transmission-distribution dynamic co-simulation (TDDS). A model of a real network including detailed models of solar photovoltaic units in the distribution system is constructed. The initial operating point of the network is validated against field measurements. The TDDS tool is used to simulate a single line-to-ground fault on the distribution system, highlighting the need for conducting transmission-distribution co-simulations.

14 SOLAR ENERGY↗
DOE OSTI2024

Opportunities and Implications for Low-Cost Hydrogen Production from Water Electrolysis in a Decarbonizing Power Sector

Increased deployment of renewable power generation such as wind and solar photovoltaics along with electrification of transportation and other sectors are driving changes in the operation and economics of the electric power sector. Simultaneously, efforts to decarbonize other sectors of the economy such as steelmaking and heavy duty transportation will require significant amounts of electricity to drive electrons to molecules processes. Hydrogen production via water splitting electrolysis is a key near-term technology for decarbonization that interfaces between the power sector and decarbonization efforts in industrial sectors. This poster examines the implications for increased deployment of water electrolyzers in a rapidly evolving energy system. The economic opportunities for low-cost hydrogen production from electrolysis that are facilitated by highly renewable grids will be examined and discussed. Durability, cost, and operational strategies for electrolyzers interacting in these future energy systems are key to enabling hydrogen at scale. This poster will overview these considerations and ongoing work within the U.S. Department of Energy’s H2NEW consortium that is focused on addressing them.

electrolysis↗
NASA NTRS1976

Technical challenges of integrating the Space Shuttle

A review is presented of the technology involved in integrating the Space Shuttle system. A powered flight analysis of the Shuttle is presented, touching upon the following areas: ascent profile and abort mode integration, sizing and design, control of load factor by a stage thrust shaping, structural load constraints, flight performance reserve and trajectory design for the orbital flight test. A discussion is presented of aerothermodynamics including aerodynamic and plume heating. Flight control and separation is considered with attention paid to liftoff, ascent to booster staging, elevon load relief, booster tailoff thrust mismatch and gimbal limitations and booster separation. Structural analysis and dynamics is examined, considering: vehicle loads and modes and the pogo effect. Propulsion aspects (hydraulics, the LH2 recirculation system, the antigeyser system, the pressurization system, etc.), ground vibration tests, separation system verification and flight readiness firing are all described.

Martin, A. C.↗
DOE OSTI2026

Hybrid Symbolic-Numerical Modeling and Parametric Stability Analysis of DC–AC Power Systems

Hybrid DC-AC power systems integrating diverse inverter-based resources (IBRs) and multi-terminal high-voltage direct current (MTDC) networks represent a promising architecture for future power grids, while introducing challenges for modeling, stability analysis, and control design. This paper develops a hybrid symbolic-numerical modeling framework and tool to characterize the parametric small-signal stability of DC-AC coupled power systems. The proposed approach constructs parametric state-space models to enable efficient representation of system dynamics under varying control parameters and network configurations, with target parameters retained as symbolic variables and the remainder treated numerically. The stability analysis framework covers eigenvalue, sensitivity, and stability boundary and region characterization. Enhanced linear matrix inequality (LMI) techniques are proposed to directly certify small-signal stability over regions of parameter space while also reducing the conservativeness and computational burden. The resulting tools and frameworks enable rapid parametric model construction across diverse grid conditions, thereby facilitating stability-informed control and operation in complex DC–AC power systems.

DC–AC power systems↗
DOE OSTI2018

Transient Stability Analysis for Offshore Wind Power Plant Integration Planning Studies - Part II: Long Term Faults

Here, this paper addresses the transient stability (also called large-signal stability) analysis of power systems for offshore wind power plant integration planning studies. In particular, this study develops a comprehensive practical methodology to assess transient stability of power systems, including rotor angle stability, voltage stability, and frequency response for large scale power systems. This methodology considers variability of the offshore wind power plants as well as the type of any faulted system' components present and is applicable to the study of both short term and long term faults. Part I of this research discussed the short term faults whereas as Part II, the present paper, discusses long term faults. This research considers the integration of offshore wind power plants into existing power systems and demonstrates the utility of this methodology through the examination of the specific case of integrating 1,000 MW of offshore wind power into the FirstEnergy/PJM service territory using a realistic model of 63k-bus test system that represents the U.S. Eastern Interconnection.

17 WIND ENERGY↗
DOE OSTI2019

A Novel Equivalent Model of Active Distribution Networks Based on LSTM

Dynamic behaviors of distribution networks are of great importance for the power system analysis. Nowadays, due to the integration of the renewable energy generation, energy storage, plug-in electric vehicles, and distribution networks turn from passive systems to active ones. Hence, the dynamic behaviors of active distribution networks (ADNs) are much more complex than the traditional ones. The research interests how to establish an accurate model of ADNs in modern power systems are drawing a great deal of attention. In this paper, motivated by the similarities between power system differential algebraic equations and the forward calculation flows of recurrent neural networks (RNNs), a long short-term memory (LSTM) RNN-based equivalent model is proposed to accurately represent the ADNs. First, the adoption reasons of the proposed LSTM RNN-based equivalent model are explained, and its advantages are analyzed from the mathematical point of view. Then, the accuracy and generalization performance of the proposed model is evaluated using the IEEE 39-Bus New England system integrated with ADNs in the study cases. Here, it reveals that the proposed LSTM RNN-based equivalent model has a generalization capability to capture the dynamic behaviors of ADNs with high accuracy.

42 ENGINEERING↗
DOE OSTI2019

Analysis on the Influence of an Energy Storage System and its Impact to the Grid for a Wave Energy Converter

Reducing power fluctuations is essential for controlling the integration impacts of wave energy converter (WEC) plants in both distribution and transmission grids, and in stand-alone isolated power systems. This paper presents an analysis on the cost of and how a battery storage system can be used to further reduce the variation of power generated from the WEC due to the fluctuating nature of waves and its impact to the grid. The electrical power output from WEC-Sim simulations for the six sea states used in the Wave Energy Prize was analyzed to compute the peak power and power time history. The results were used to evaluate the battery storage capacity that is needed for a WEC system to provide reasonable power flow to the grid and estimate its cost based on the latest cost information for battery technologies published by the U.S. Energy Information Administration. Finally, a preliminary grid integration analysis was performed to demonstrate how WEC-generated power would contribute to a small island electricity system. As shown in the study, the instantaneous peak power is the primary cost driver for the battery storage and the power take-off system, and reducing the power fluctuations is essential for reducing the overall levelized cost of energy (LCOE). The power flow variation from WECs can be significantly reduced using battery storage without adding significant overall system costs, and the implementation of battery storage is essential for grid integration applications. There may also be additional opportunities to further investigate energy storage technologies that are specific to WEC applications to reduce these costs even further.

16 TIDAL AND WAVE POWER↗
NASA NTRS2000

System Design Techniques for Reducing the Power Requirements of Advanced life Support Systems

The high power requirement associated with overall operation of regenerative life support systems is a critical Z:p technological challenge. Optimization of individual processors alone will not be sufficient to produce an optimized system. System studies must be used in order to improve the overall efficiency of life support systems. Current research efforts at NASA Ames Research Center are aimed at developing approaches for reducing system power and energy usage in advanced life support systems. System energy integration and energy reuse techniques are being applied to advanced life support, in addition to advanced control methods for efficient distribution of power and thermal resources. An overview of current results of this work will be presented. The development of integrated system designs that reuse waste heat from sources such as crop lighting and solid waste processing systems will reduce overall power and cooling requirements. Using an energy integration technique known as Pinch analysis, system heat exchange designs are being developed that match hot and cold streams according to specific design principles. For various designs, the potential savings for power, heating and cooling are being identified and quantified. The use of state-of-the-art control methods for distribution of resources, such as system cooling water or electrical power, will also reduce overall power and cooling requirements. Control algorithms are being developed which dynamically adjust the use of system resources by the various subsystems and components in order to achieve an overall goal, such as smoothing of power usage and/or heat rejection profiles, while maintaining adequate reserves of food, water, oxygen, and other consumables, and preventing excessive build-up of waste materials. Reductions in the peak loading of the power and thermal systems will lead to lower overall requirements. Computer simulation models are being used to test various control system designs.

Finn, Cory↗
DOE OSTI2020

Comparison of Thermal Management Approaches for Integrated Traction Drives in Electric Vehicles

The continuous push to increase power densities of electric vehicle (EV) traction drive systems necessitates combining electric motor and power electronics into one unit. A single, compact traction drive unit with fewer interconnecting components also facilitates fast, automated assembly of electric vehicles, driving production costs down and enabling wider adoption of EVs. There are a number of challenges associated with the integration of power electronics with the electric machine, including thermal management of the combined traction drive system. However, one important benefit of integration from the thermal management system perspective is the potential for using a single fluid loop instead of two separate cooling systems for the electric machine and the power electronics/inverter. This paper reviews several integration approaches and, employing finite element analysis (FEA), compares thermal management solutions for the combined electric machine and power electronics systems. Namely, three different scenarios are modeled: (1) independent component (motor and power electronics) cooling, which is compared to the combined cooling system approach for (2) radially and (3) axially integrated power electronics modules into the motor enclosure. Temperature distributions for selected thermal loads and thermal resistances from the key heat-generating components to the cooling fluid are compared for each scenario.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

IMG-ABC. A knowledge base to fuel discovery of biosynthetic gene clusters and novel secondary metabolites

In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of “big” genomic data for discovering small molecules. IMG-ABC relies on IMG’s comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC’s focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in lphaproteobacteria . IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG’s extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Enhancing Power Grid Resilience with Causal Loops Diagram and Bayesian Networks

Enhancing power grid resilience through improved analysis and planning of Distributed Energy Resources is a key for power system planner. This paper explores the integration of Causal Loop Diagrams (CLDs) and Bayesian Networks (BNs) for enhancing resilience in power systems, focusing on Distributed Energy Resources (DER) planning. By automating CLD analysis in Python's matplotlib, we present a tool for rapid model validation and structural accuracy, crucial for power system planners. This hybrid approach utilizes BNs for inferential depth and CLDs for dynamic system modeling, offering a comprehensive framework for policy formulation and collaborative strategy development against disruptions. Here, we highlight the tool's capability to identify and analyze interconnected feedback loops, facilitating a deeper understanding of DER integration's impact on network resilience. This work aims to bridge quantitative analysis and qualitative insights, addressing the limitations of each method while providing a robust model for power system resilience assessment.

14 SOLAR ENERGY↗