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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Error-controlled Progressive Retrieval of Scientific Data under Derivable Quantities of Interest

The unprecedented amount of scientific data has introduced heavy pressure on the current data storage and transmission systems. Progressive compression has been proposed to mitigate this problem, which offers data access with on-demand precision. However, existing approaches only consider precision control on primary data, leaving uncertainties on the quantities of interest (QoIs) derived from it. In this work, we present a progressive data retrieval framework with guaranteed error control on derivable QoIs. Our contributions are three-fold. (1) We carefully derive the theories to strictly control QoI errors during progressive retrieval. Our theory is generic and can be applied to any QoIs that can be composited by the basis of derivable QoIs proved in the paper. (2) We design and develop a generic progressive retrieval framework based on the proposed theories, and optimize it by exploring feasible progressive representations. (3) We evaluate our framework using five real-world datasets with a diverse set of QoIs. Experiments demonstrate that our framework can faithfully respect any user-specified QoI error bounds in the evaluated applications. This leads to over 2.02× performance gain in data transfer tasks compared to transferring the primary data while guaranteeing a QoI error that is less than 1E-5.

Wu, Xuan↗
DOE OSTI2025

A Design for Remanufacturing Framework Incorporating Identification, Evaluation, and Validation: A Case Study of Hydraulic Manifold

In recent years, academic researchers and engineers in the industry have widely recognized the necessity of integrating remanufacturing considerations into product design iterations to advance sustainability objectives. Acknowledging the importance of design for remanufacturing (DfRem), efforts were made to develop tools and guidelines that could be implemented in practice. However, such methods largely rely upon experiential insights and qualitative assessments, leaving a gap in the ability to quantitatively assess the economic and environmental impacts of design choices. To bridge this gap, we investigate existing efforts and present a framework for DfRem that integrates established design and remanufacturing practices into a cohesive workflow with quantitative assessments. To demonstrate its efficacy for making practical design changes for remanufacturing, we apply the framework to a hydraulic manifold in a transmission system for heavy-duty tractors. Through this industry-relevant case study, we focus on showcasing the practical utility of our framework. Based on the identified design modifications from remanufacturability analysis, we estimate the reductions in life cycle costs, energy consumption, and emissions. Afterward, the modifications are tested using physical experiments with plans for integration into future iterations of the hydraulic manifold design and production. Here, we anticipate this framework can illustrate the process of remanufacturing that ensures improvements in sustainability while maintaining performance and reliability standards.

design for X↗
DOE OSTI2024

GDM (Grid Data Models) [SWR-24-31]

Grid Data Models (GDM) is a collection of pydantic data models for power distribution and transmission system components. These data models can be easily serialized and deserialized. GDM provides a standard interface for accessing power system component data with built in validation. See also: https://pypi.org/project/grid-data-models/

Duwadi, Kapil↗
DOE OSTI2025

Real-Time Dispatcher for a Distributed Energy Resource Power Plant to Provide Grid Services [SWR-25-17]

This software dispatches the aggregated power of a distributed energy resource (DER) plant located on an electrical distribution network. It is designed to provide the following services to the grid in real-time: (i) voltage support of the distribution network, (ii) virtual power plant at the substation with power factor support, and (iii) operating reserves for automatic generator control for the transmission system. This dispatcher integrates with the local power plant controller and utilizes the battery energy storage system (BESS) to smooth the volatile net power output from the DERs. It can also integrate with a day-ahead scheduler to strategically charge and discharge.

Comden, Joshua [National Renewable Energy Laborato↗
DOE OSTI2025

Quality-Controlled Meteorological Data from the Flood Control District of Maricopa County (FCDMC) Network, Phoenix, Arizona (1987-2024)

This dataset contains 15- or 30-minute interval meteorological data from the Flood Control District of Maricopa County (FCDMC), Arizona, USA, covering eight key variables across multiple sensor stations between 1987 and 2024. Each variable is stored as a separate CSV file, containing time-series data that have undergone rigorous quality control (QC) procedures and, where appropriate, short-gap interpolation for consistency. The quality control (QC) pipeline consisted of four sequential tests: (1) a range test to ensure all values fall within physically realistic limits, (2) a step test to identify abrupt and implausible changes between consecutive records, (3) a proximity test that validates flagged values from step test using data from nearby stations and exceedance probability thresholds, and (4) a persistence test to detect and remove periods of unrealistically constant readings. These thresholds were calibrated to Arizona’s environmental conditions and sensor specifications. After QC, short gaps (≤2 hours) were linearly interpolated to ensure consistent temporal resolution, except for wind variables. Due to a major upgrade in FCDMC’s data transmission system, only ALERT-2 protocol data (2016–2024) for wind variables are included; earlier ALERT-1 data were excluded because of irregular sampling and high missing rates. This dataset supports regional climate and infrastructure resilience studies by providing standardized, high-resolution meteorological data for the greater Phoenix metropolitan area.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Subsurface Hydrogen and Natural Gas Storage (State of Knowledge and Research Recommendations Report)

Global efforts to decrease carbon dioxide (CO 2 ) emissions will result in increased reliance on renewable energy sources. One of the most significant obstacles to implementing this transition is the need for energy storage to compensate for varying, and sometimes intermittent, production rates and ever-increasing demand. An attractive solution is to use surplus energy to produce hydrogen gas (H 2 ), which can then be used to produce energy on demand without emitting CO 2 . This approach would require a vast H 2 network linking generators with consumers via transmission systems. Additionally, H 2 storage would be needed to support immediate needs, but larger storage reserves also will be required to ensure energy reliability and mitigate the impact of the mismatch between variable production rates and demand. Large-scale storage of H 2 may be achieved by using underground resources similar to how natural gas (NG) has been stored for the past century. While there is much experience in underground NG storage (UGS), significant technical challenges must be addressed to economically and safely store H 2 at the commercial scale. The purpose of this report is to assess the current state of knowledge and to identify technical research needs to facilitate deployment of large-scale underground hydrogen storage (UHS).

03 NATURAL GAS↗
DOE OSTI2022

High Voltage Regrown GaN P-N Diodes Enabled by Defect and Doping Control

This project studied and implemented methods to form GaN p-n diodes using selective area regrowth to achieve selective area doping. Successful selective area doping of GaN p-n diodes is an enabling factor to realize more advanced devices such as vertical transistors. The general challenge to selective area regrowth of GaN is that the primary etch method, inductively coupled plasma (ICP), damages the crystal and causes high leakage when didoes are formed by regrowth on the etched surface. Our approach used low damage etch methods following ICP etch to remove crystal damage and reduced leakage in the regrown diode. This project demonstrated 1.6 kV etched-and-regrown GaN p-n diodes using planar (non-selective) regrowth and 840 V etched-and-regrown p-n diodes using selective area regrown. Enabling factors were use of a low-damage reactive ion etch (RIE) to remove damage caused by the primary ICP etch combined with a multi-step junction terminal extension (JTE) process. Deep level defect investigation quantitatively correlated a deep level near the middle of the GaN band gap with ICP etch-induced leakage that was greatly mitigated by using a slow, low damage RIE process. This research is economically feasible for commercialization because the processes used in this project, including substrate type and source, epitaxial crystal growth and fabrication techniques are all standard to the GaN semiconductor industry. The fundamental understanding and foundational ability to produce kV-class GaN p-n diodes through etch-and-regrowth provides a path to realize high power, high efficiency GaN power switches that can significantly outperform commercial devices for next-generation electrical power conversion and transmission systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Multi-Scale Computational Platform for Predictive Modeling of Corrosion in Al-Steel Joints (Final Report)

The research team proposed to develop innovative multi-scale models to predict corrosion and the resulting mechanical performances in aluminum-steel joints. The methods of joining considered are resistance spot welding, self-piercing riveting, and rivet-welding, all suitable for mass production applications. The multi-scale models integrate high throughput first-principle calculations based on density functional theory (DFT), high throughput calculation of phase diagrams (CALPHAD) modeling, and finite element method (FEM) simulations. These models are to be validated through laboratory experiments. Furthermore, the models are available as open source so as to enable scientists and engineers in the community to adapt and contribute to the development and application. The approaches rely on the research team’s extensive experience on the prediction of properties of individual phases at finite temperatures and variable compositions through DFT calculations, and our broad expertise on dissimilar material joining and their corrosion. The proposed computational framework enables high throughput computations for improved predictions of corrosion and the associated mechanical performance in dissimilar material joints, resulting in significant reduction in computational time needed by the current state-of-the-art methods. With the participation of researchers from three universities, an auto manufacturer, two manufacturing technology/equipment suppliers, and a software developer/vendor, the interdisciplinary research team applies the technical development on both phase-based modeling and laboratory experiments into the automobile body joining processes for validation and technology demonstration. The global cost of corrosion was estimated at about 3.4% of the global GDP in 2013. By using available corrosion control practices, it is estimated a saving between 15-35% of the cost of corrosion. In the U.S., more than $276 billion is spent repairing corrosion damage. Prediction of the corrosion and its impact on performance of the dissimilar material joints is critical for reducing the massive number of the current corrosion-based recalls for automobiles. Thus, the project goal is to develop models to enable predictive maintenance and end-of-life planning of multi-metal joints with risk of corrosion under different conditions such as exposure to high temperatures in summer and salt solutions in winter, quantified through its pH. An academia-industry consortium led by the University of Michigan and including Pennsylvania State University, University of Illinois Urbana-Champaign, University of Georgia, General Motors Company, Livermore Software Technology Corporation, and Optimal Process Technologies, LLC. created multi-scale models for prediction of corrosion in aluminum-steel joint structures such of them used in vehicle subassemblies – chassis and transmission systems. Starting from the first principle calculations, the team developed mathematical and data-driven models to predict the metallic components, which are formed during joining of two metals, for example aluminum and steel - a lightweight multilateral system which is currently used in more than 60% car bodies. These models were used for simulating chemical reactions that are happening when the joining metallic components are exposed to high temperatures and different pH values. The team was able to predict how the corrosion installs on the metallic components and how they lead to a sudden failure of components in cars. Newly developed machine learning algorithms combining Science, Technology, Engineering and Math disciplines, advanced finite element simulation and experimental validations have been integrated in a platform for prediction of the corrosion evolution and prediction the failure of joints under mechanical loadings and fatigue. Moreover, based on machine learning and inverse analysis, the team proposed solutions for designing new metallic alloys less susceptible to corrosion when joining multi-material assembles. An average of 4% error compared with experiments was achieved for the most common joints that are used in vehicle subassemblies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Wind Energy Costs in Puerto Rico Through 2035

In 2019, Puerto Rico codified into law a 100% renewable electricity by 2050 target. Decision makers there need information about the costs and performance of wind energy technologies to incorporate into planning efforts for the future grid. After consulting with key technical stakeholders and accounting for unique conditions in Puerto Rico like increased hurricane risks, we customize NREL's Renewable Energy Potential model to calculate how capital expenditures, operational expenditures, net annual energy generation, and levelized cost of energy (LCOE) vary in time and space for wind energy projects around Puerto Rico. Wind turbines can add value by providing grid services through grid-forming inverters and complement solar energy generation with evening and nighttime electricity production, especially offshore. By 2035, we expect average costs of land-based and offshore wind energy in Puerto Rico to reach $\$$69/MWh (6.9 cents/kWh) and $\$$100/MWh (10 cents/kWh), respectively. While these projections do not include transmission system upgrade costs, they do suggest that low-cost, clean electricity is possible for Puerto Rico.

17 WIND ENERGY↗
DOE OSTI2023

5G Energy FRAME: The Design and Implementation of Data, Model, and Use Case (Year 2 Report)

This report summarizes the Year 2 work of Pacific Northwest National Laboratory’s (PNNL’s) 5G Fabricated Resource and Asset Management Encompassment for energy infrastructure (Energy FRAME) project funded by the Department of Energy Office of Science’s Advanced Scientific Computing Research (ASCR) Program. In this report, newest 5G equipment testing results are presented, along with two 5G-enabled AI/ML examples for grid applications; in addition, the work flow of grid edge, cloud, and High Performance Computing (HPC) platform is introduced, to support and interface the cross-domain simulation for power system transmission, distribution, and communication networks. Last but not least, the outlook for Year 3 work and the overarching impact of 5G Energy FRAME work to a multitude of stakeholders are provided. Additional 5G performance data now is shared through the publicly available weblink, https://www.pnnl.gov/projects/5g-energy-frame/publications

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Evolving Competitive Markets in SAPP: Leveraging Competitive Wholesale Electricity Markets to Drive Renewable Generation Capacity in the Southern African Power Pool (SAPP)

The SADC region has significant natural resource potential to increase renewable energy generation, improve electricity reliability, and support economic development. This research finds an apparent lack of confidence from electricity infrastructure investors in SAPP wholesale electricity markets, which increases risk perception and lowers the likelihood of capital deployment. With respect to free market fundamentals, competitive market obstacles and renewable energy development obstacles are characterized. Stakeholders identified the top obstacles to well-functioning competitive markets as insufficient transmission infrastructure for interconnection and regional movement of electricity, dominance of national single-buyer markets, and lack of or weak nation-state regulatory frameworks. Stakeholders prioritized the top three obstacles for renewable energy development as a lack of viable commercial arrangements for variable renewable energy (VRE) balancing, lack of functional and consistent nation-level regulations, and higher project costs related to reliance on imported equipment. With respect to potential solution options, stakeholders prioritized the development of new cost allocation and finance methods to facilitate new transmission expansion, training to educate new or potential new market entrants on SAPP processes, as well as modeling and analysis of regional SAPP participation benefits disaggregated to the nation-state level. From these perspectives, this research identified strategy options for consideration including transitioning SAPP to a regional transmission operator (RTO) for operation and planning of cross-border transmission facilities and market administration, shifting operations of SAPP member transmission systems to Independent System Operators (ISOs), establishing a regional regulatory authority and enhancing market data transparency. Implementing these reforms is expected to be challenging, but not insurmountable, given the domestic political, legal, and jurisdictional complexities of the SADC region.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Space Charge Effects on Spin Polarization in High-Intensity Preinjector

This analytical study investigates the space charge impact on electron beam polarization within the low-energy range, spanning from the polarized electron gun up to the linac. The research study three sections: the gun-to-Wien filter interface, the Wien filter section, and the bunching section. We will comprehensively assess polarization degradation mechanisms in each region characterized by space charge effects. We are planning to simulate the spin tracking through the entire low-energy transmission system using Generalized Particle Tracer (GPT) to validate our analytical findings and includes the higher order components.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Examples of State and Utility Actions on Proactive Planning and Investments

As states across the U.S. confront rising electricity demand, clean energy deployment, grid modernization imperatives, and the integration of large new loads, some regulators and utilities are shifting away from reactive, “just-in-time” investment approaches toward more proactive planning and investment frameworks. This report compiles examples of jurisdictional and utility actions that reshape planning processes, cost recovery mechanisms, and performance oversight to anticipate—rather than simply respond to—future grid needs. Several themes emerge from state actions examined in this report. First, legislatures and commissions are increasingly directing utilities to proactively upgrade their distribution and transmission systems, reflecting a shift toward a forward-looking system that aligns planning with state policy goals. Second, states are establishing long-term, iterative planning frameworks that often feature multi-year horizons, biannual or annual compliance reporting, structured opportunities for stakeholder engagement, and emphasis on collaboration among utilities, regulators, and stakeholders. Third, states are actively investigating innovative cost recovery mechanisms designed to support accelerated electrification and grid modernization, while balancing consumer advocates’ concerns regarding the ratepayer financial risks of premature investments. Fourth, performance metrics and reporting requirements are being developed to ensure transparency and accountability for proactive investments. Fifth, methodological improvements in planning—such as aligning load forecasting assumptions, incorporating sensitivities, and considering load management potential across building, vehicles, storage, and demand response—are recurring areas of stakeholder focus across jurisdictions. Overall, these developments signify a growing recognition among state regulators, utilities, and stakeholders that proactive planning—supported by clear definitions, consistent and transparent methodologies, robust performance metrics, and innovative cost recovery mechanisms—is a tool that can be used to address the scale and urgency of contemporary grid needs.

electricity market↗
DOE OSTI2024

Convex Relaxations of Maximal Load Delivery for Multi-Contingency Analysis of Joint Electric Power and Natural Gas Transmission Networks

Recent increases in gas-fired power generation have engendered increased interdependencies between natural gas and power transmission systems. These interdependencies have amplified existing vulnerabilities in gas and power grids, where disruptions can require the curtailment of load in one or both systems. Although typically operated independently, coordination of these systems during severe disruptions can allow for targeted delivery to lifeline services, including gas delivery for residential heating and power delivery for critical facilities. To address the challenge of estimating maximum joint network capacities under such disruptions, we consider the task of determining feasible steady-state operating points for severely damaged systems while ensuring the maximal delivery of gas and power loads simultaneously, represented mathematically as the nonconvex joint Maximal Load Delivery (MLD) problem. To increase its tractability, we present a mixed-integer convex relaxation of the MLD problem. Then, to demonstrate the relaxation’s effectiveness in determining bounds on network capacities, exact and relaxed MLD formulations are compared across various multi-contingency scenarios on nine joint networks ranging in size from 25 to 1191 nodes. The relaxation-based methodology is observed to accurately and efficiently estimate the impacts of severe joint network disruptions, often converging to the relaxed MLD problem’s globally optimal solution within ten seconds.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Stochastic Look Ahead Commitment: A Computational Perspective

This presentation gives an overview of a stochastic look ahead commitment (SLAC) problem for managing transmission grid uncertainty in the near- to medium-term (15 minutes to a few hours). We discuss formulation and solution methods, as well as application to transmission system operations.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2021

Prototype and Codesign of Nascent Flexible Wave Energy Converter Concepts

Prevailing mainstream ocean wave energy converter (WEC) archetypes are often relatively large monolithic rigid bodies with singular means of power take-off (e.g., relative motion between rigid bodies) and solo prime mover mechanisms (e.g. a rotary generator, a hydraulic piston). These mainstream WEC archetypes have existed for decades with some having histories spanning more than a century of significant investments and interests. As an alternative to the domain of mainstream WEC archetypes is the domain of distributed embedded energy converter technologies (also known as DEEC-Tec). Use of DEEC-Tec to create WECs - often called flexWECs - is a nascent domain of research and development that centers itself upon the interconnection of many relatively small energy converters - very small energy transducers - that interconnect and combine to create a much larger, overall, energy converting structure. The DEEC-Tec domain enables promising possibilities such as: direct in situ ocean wave energy harvesting and conversion throughout the volume of an entire flexWEC; inherent broad-banded ocean wave energy capture and conversion arising from near semi-continuous structural degrees of freedom; an innate absence of focusing and concentrating of ocean wave energy into a single prime mover and/or transmission system; and built-in implicit redundancy. As such, the DEEC-Tec domain could revolutionize how we conceptualize ocean wave energy conversion - both in terms of ocean wave energy converter design and what we view as viable environments and circumstances for ocean wave energy conversion. The research and development opportunities for the DEEC-Tec domain, therefore, are vast compared to the prevailing mainstream ocean wave energy converter domain. Correspondingly, there are ample opportunities to invest time and money into the DEEC-Tec domain with an aim to enable a paradigm shift in how ocean waves can be utilized as a more viable form of renewable energy. To that end, two seedling efforts have been enacted providing a very cursory investigation into the DEEC-Tec domain: (1) a preliminary simple fabrication/prototyping effort and (2) a preliminary co-design effort. The prototype seedling centers upon the design of a fabrication and evaluation rig for individual DEEC-Tec transducers; e.g., dielectric elastomer generators. The co-design seedling centers upon the analysis of those methods suitable for DEEC-Tec, ocean wave energy conversion, and fluid-structure interaction co-design efforts.

50 EE - Wind and Water Power Program - Water (EE-4↗
DOE OSTI2022

DC compensation for power transformer through neutral DC injection

A power transmission system can include a transformer and compensator circuit(s), each coupled between a node of the transformer and a ground connection. The compensator circuit(s) can each be configured to counteract a DC signal component of an AC signal at the transformer. The compensator circuit(s) can include a converter circuit having an AC side and a DC side and configured to convert a DC voltage on the DC side to an AC signal at the AC side. The compensator circuit(s) can include a DC link coupled to the DC side of the converter circuit. The compensator circuit(s) can include a controller configured to measure a DC signal component between the load and the ground; to determine, based at least in part on the DC signal component, a compensating signal configured to counteract the DC signal component; and to inject, by the converter circuit, the compensating signal to counteract the DC signal component.

Burkes, Klaehn W.↗
DOE OSTI2023

Computationally Robust Line Outage Detection and Identification in Three-Phase Networks

Detection and identification of individual phase outages remains a challenging problem due to insufficient metering in three-phase unbalanced power networks. This problem was tackled for the transmission systems in our previous work as documented in [1]. In this paper, this work is extended to detect phase outages in three-phase unbalanced systems using only the sparse estimation method. In addition, further improvements are introduced to increase the estimation accuracy for the virtual power injections at the terminal buses of disconnected lines, once the disconnected line is identified by sparse estimation methods. Simulation results are provided to experimentally validate the increased accuracy in detecting phase outages while decreasing the computational time by using the proposed approach.

Sparse Estimation, Line Outage, Phase Outage, LASS↗