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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Grid Value Analysis of Medium-Voltage Back-to-Back Converter on DER Hosting Enhancement

This paper presents an analysis of the value that can be realized by medium-voltage back-to-back (MVB2B) converters in terms of the increased utilization rate of distributed energy resources (DERs) and the improvement in operational conditions. A systematic, transferrable, and scalable methodology has been designed to analyze and quantify the increased DER value from three perspectives: 1) curtailment reduction of the DER generation, 2) size reduction of the energy storage needed to otherwise realize DER hosting levels, and 3) hosting capacity improvement of the DERs compared to the base distribution circuit capability. In the case study, the proposed methodology is applied to two utility distribution systems for analysis and quantification of the grid value of the MVB2B converter, installed in the distribution circuit, and provided to the solar photovoltaic (PV) DERs. Here, the analysis results demonstrate that the MVB2B converter can deliver significant value to the PV hosting enhancement of two adjacent distribution systems when they are connected by the MVB2B converter. Based on this case study, this paper analyzes and summarizes the approximate realized grid value of the MVB2B converter for distribution systems dominated by different shares of customer classes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Evaluating Utility-Scale PV-Battery Hybrids in an Operational Model for the Bulk Power System

Systems that combine solar photovoltaic and battery energy storage technologies (PV-BES) are increasingly being proposed and deployed on the bulk power system. The operations and value of PV-BES systems have been extensively studied from the project developer's perspective through analyses that maximize plant-level revenue. However, PV-BES hybrids' operational characteristics are seldom studied from the perspective of bulk power system operators, who seek to optimize the performance of a suite of generation and storage assets that are connected via the transmission network. This work presents modeling approaches for representing and evaluating PV-BES hybrids in a model that optimizes operations across the bulk power system. Its novel contributions include demonstrating a technique to modify a unit commitment and dispatch model to represent the operational synergies of PV-BES hybrids. In particular, we describe the challenges and an approach for representing so-called DC-coupled PV-BES - which utilize a single bi-directional inverter - as a dispatchable resource in a commercial, production cost model (PCM), PLEXOS. We demonstrate this technique in a PCM study of the Los Angeles Department of Water and Power (LADWP) test system, by replacing existing PV and battery generators on the test system with our PV-BES hybrids. We then pursue scenario analysis that is designed to isolate the various drivers of operational strategies for DC-coupled PV-BES hybrids, including the nature of coupling, PV penetration on the system, and varying inverter loading ratios (or degrees of over-sizing of the PV field). Results from the analysis include utilization profiles for the PV DC energy across available pathways, dispatch profiles for the battery component, and the hybrid technologies' impacts on system-wide production costs. The approach presented in this paper can be used in any PCM that is looking to study PV-BES hybrids as a resource in different power system configurations and services.

14 SOLAR ENERGY↗
DOE OSTI2021

An Integrated Feasibility Study of Reservoir Thermal Energy Storage (RTES) in Portland, OR, USA

In regions with long cold overcast winters and sunny summers, Deep Direct-Use (DDU) can be coupled with Reservoir Thermal Energy Storage (RTES) technology to take advantage of pre-existing subsurface permeability to save summer heat for later use during cold seasons. Many aquifers worldwide are underlain by permeable regions (reservoirs) containing brackish or saline groundwater that has limited beneficial use due to poor water quality. We investigate the utility of these relatively deep, slow flowing reservoirs for RTES by conducting an integrated feasibility study in the Portland Basin, Oregon, USA, developing methods and obtaining results that can be widely applied to RTES systems elsewhere. As a case study, we have conducted an economic and social cost-benefit analysis for the Oregon Health and Science University (OHSU), a teaching hospital that is recognized as critical infrastructure in the Portland Metropolitan Area. Our investigation covers key factors that influence feasibility including 1) the geologic framework, 2) heat and fluid flow modeling, 3) capital and maintenance costs, 4) the regulatory framework, and 5) operational risks. By pairing a model of building seasonal heat demand with an integrated model of RTES resource supply, we determine that the most important factors that influence RTES efficacy in the study area are operational schedule, well spacing, the amount of summer heat stored (in our model, a function of solar array size), and longevity of the system. Generally, heat recovery efficiency increases as the reservoir and surrounding rocks warm, making RTES more economical with time. Selecting a base-case scenario, we estimate a levelized cost of heat (LCOH) to compare with other sources of heating available to OHSU and find that it is comparable to unsubsidized solar and nuclear, but more expensive than natural gas. Additional benefits of RTES include energy resiliency in the event that conventional energy supplies are disrupted (e.g., natural disaster) and a reduction in fossil fuel consumption resulting in a smaller carbon footprint. Key risks include reservoir heterogeneity and a possible reduction in permeability through time due to scaling (mineral precipitation). Lastly, a map of thermal energy storage capacity for the Portland Basin yields a total of 43,400 GWh, suggesting tremendous potential for RTES in the Portland Metropolitan Area.

14 SOLAR ENERGY↗
DOE OSTI2022

A Smart and Flexible Microgrid with a Low-cost Scalable Open-source Controller (Final Report)

This report contains information regarding the activities carried out in the project "A Smart and Flexible Microgrid with a Low-cost Scalable Open-source Controller. The project aims at developing a community-based flexible microgrid (FMG) with smart grid features, including multiple utility feeders and dynamic boundaries that utilize intelligent switches and ultra-high-speed communication links already in a smart grid. The project also aims at developing a corresponding controller for such an FMG with low cost and high scalability. With distributed renewable energy resources (DERs) and the intelligent microgrid controller, the FMG will achieve aggressive emission reduction, increased energy use efficiency, and reliability improvement goals. The FMG and its controller design will be scalable for different geographic areas, load sizes, distributed generation source number and types, and even multiple MGs within a distribution electric power system. In order to achieve these project objectives, three main development tasks were carried out: FMG design, FMG controller development, and FMG controller testing. The fourth task was technology to market.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Phylogenomics and Comparative Genomics Highlight Specific Genetic Features in Ganoderma Species

The Ganoderma species in Polyporales are ecologically and economically relevant wood decayers used in traditional medicine, but their genomic traits are still poorly documented. In the present study, we carried out a phylogenomic and comparative genomic analyses to better understand the genetic blueprint of this fungal lineage. We investigated seven Ganoderma genomes, including three new genomes, G. australe, G. leucocontextum, and G. lingzhi. The size of the newly sequenced genomes ranged from 60.34 to 84.27 Mb and they encoded 15,007 to 20,460 genes. A total of 58 species, including 40 white-rot fungi, 11 brown-rot fungi, four ectomycorrhizal fungi, one endophyte fungus, and two pathogens in Basidiomycota, were used for phylogenomic analyses based on 143 single-copy genes. It confirmed that Ganoderma species belong to the core polyporoid clade. Comparing to the other selected species, the genomes of the Ganoderma species encoded a larger set of genes involved in terpene metabolism and coding for secreted proteins (CAZymes, lipases, proteases and SSPs). Of note, G. australe has the largest genome size with no obvious genome wide duplication, but showed transposable elements (TEs) expansion and the largest set of terpene gene clusters, suggesting a high ability to produce terpenoids for medicinal treatment. G. australe also encoded the largest set of proteins containing domains for cytochrome P450s, heterokaryon incompatibility and major facilitator families. Besides, the size of G. australe secretome is the largest, including CAZymes (AA9, GH18, A01A), proteases G01, and lipases GGGX, which may enhance the catabolism of cell wall carbohydrates, proteins, and fats during hosts colonization. The current genomic resource will be used to develop further biotechnology and medicinal applications, together with ecological studies of the Ganoderma species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

MiGRIDS

MiGRIDS is a software that models islanded microgrid power systems with different controls and components. For example, using load and resource data from a microgrid, you could model it with additional wind turbines, battery etc. You could also try out different dispatch schemes to see which one worked best. MiGRIDS is designed to help optimize the size and dispatch of grid components in a microgrid. While a grid connect feature is expected to be added in the future, islanded operation is the focus. Note that this is a basic implementation and more features and functionality (such as a GUI) are coming! MiGRIDS runs time-step energy balance simulations for different grid components and controls. In smaller microgrid environments, dispatch decisions are being made on the order of seconds. In order to fully capture their effect, this tool lets you run simulations on the order of seconds. The end result is a more realistic representation of what can be achieved by integrating different components and control strategies in a grid.

Morgan, Tawna↗
DOE OSTI2021

Evaluating the Curtailment Risk of Non-Firm Utility-Scale Solar Photovoltaic Plants under a Novel Last-In First-Out Principle of Access Interconnection Agreement

With the increasing share of distributed energy resources on the electric grid, utility companies are facing significant decisions about infrastructure upgrades. An alternative to extensive and capital-intensive upgrades is to offer non-firm interconnection opportunities to distributed generators, via a coordinated operation of utility scale resources. This paper introduces a novel flexible interconnection option based on the last-in, first-out principles of access aimed at minimizing the unnecessary non-firm generation energy curtailment by balancing access rights and contribution to thermal overloads. Although we focus on solar photovoltaic (PV) plants in this work, the introduced flexible interconnection option applies to any distributed generation technology. The curtailment risk of individual non-firm PV units is evaluated across a range of PV penetration levels in a yearlong quasi-static time-series simulation on a real-world feeder. The results show the importance of the size of the curtailment zone in the curtailment risk distribution among flexible generation units as well as that of the “access right” defined by the order in which PV units connect to the grid. Case study results reveal that, with a proper selection of curtailment radius, utilities can reduce the total curtailment of flexible PV resources by up to more than 45%. Findings show that non-firm PV generators can effectively avoid all thermal limit-related upgrade costs.

14 SOLAR ENERGY↗
DOE OSTI2022

Forecasting distributed energy resources adoption for power systems

Failing to incorporate accurate distributed energy resource penetration forecasts into long-term resource and transmission planning can lead to cost inefficiencies at best and system failures at worst. We have developed an open-source tool that employs an advanced Bass specification to calibrate and forecast technology adoption. The advanced specification includes geographic clustering, exogenously estimated market size, and dynamic time steps. Training on historical adoption of rooftop photovoltaics at the U.S. county-level and using detailed techno-economic estimates, our model achieves a two-year average mean-absolute-percentage-error of 19% in predicting system counts at the county-level, weighted by population. Model error was negatively correlated with market maturity - the error was 12% for counties in states with at least 28 W-per-capita of installed capacity. The advanced specification significantly reduces unweighted forecasting percent error compared to a conventional Bass specification: from 196% to 25% for capacity and from 226% to 22% for system count.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Challenges and Technology-Driven Opportunities for Safeguarding Microreactors

Nuclear microreactors (MRs) represent a new class of reactors characterized by their compactness, portability, and low power output. These features enable MRs to supply electricity and process heat to remote areas like military bases; inaccessible locations; small grids, such as on islands; or disaster impacted areas. Compared to traditional light water reactors, MRs have a unique set of attributes that need to be considered for the implementation of safeguard strategies. Current safeguard methodologies are reactor technology specific and are employed on large, stationary reactors where there is easy access by safeguards inspectors and where safeguard equipment can be easily installed and retrofitted. While there are numerous benefits to MRs, their compact size, portability, scalability, and operational lifetime create challenges to the traditional safeguard approaches, thus needing novel safeguard strategies. Here, this paper addresses the unique challenges posed by MRs to the international nuclear safeguards regime, including limited human resources, and explores how technology advancements can help mitigate these challenges. Specifically, it examines novel technologies that could contribute to establishing a comprehensive safeguards framework for MRs. These safeguards-enabling technologies encompass safeguards by design, remote sensing and monitoring technologies, applications of artificial intelligence and machine learning algorithms, utilization of digital twins, and system of systems assessments. While each of these safeguards-enabling technologies offers partial solutions to the challenges posed by MRs for the international safeguards regime, none of them alone can entirely address these challenges. Consequently, a combination of the safeguards-enabling technologies outlined in this paper is recommended to establish a robust safeguards regime for MRs.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Cognitive IoT and Edge Computing for Intrusion Detection with Federated TinyML

Internet of Things (IoT) and Edge Computing (EC) are rapidly becoming an integral part of the modern society. By 2030, there is estimated to be over 40 billion active and connected IoT devices [1]. This rapid progress also comes with a significant implication on cybersecurity. Back-end infrastructure and systems have a much broader attack than they did previously due to vulnerable IoT/EC devices being connected to wireless networks. This expanding attack surface is a growing concern because IoT/EC are increasingly being used in critical systems such as power grids, health care, and smart homes. To effectively address a problem of this scale, cognitive cyber methods—which can autonomously detect and react to cyber attacks as they develop—are needed. To address this, we bring Artificial Intelligence (AI) and Machine Learning (ML) to IoT/EC devices, using tinyML to monitor voluminous IoT data against cyber threats, and using Federated Learning (FL) to share local detection knowledge across the system while preserving privacy. We propose a novel three-layer architecture: (1) an IoT layer for tinyML-based inference, (2) an edge layer for ML model training, and (3) a cloud layer for FL operations. Using the publicly available 11-class N-BaIoT dataset [2], we demonstrate that this architecture mitigates resource constraints at the IoT layer while improving detection accuracy over standard two-layer designs. An outlier-resistant scaler, feature reduction, and quantization enable the tinyML model to maintain detection accuracy with a reduced model size. Additionally, federated learning that only utilizes the intersection (across heterogenous devices) of the reduced feature set achieves superior detection accuracy compared to locally trained models.

Li, Mingyan [ORNL] (ORCID:0009000569532640)↗
DOE OSTI2020

Evaluation of residue management practices on barley residue decomposition

Optimizing barley (hordeum vulgare L.) production in Idaho and other parts of the Pacific Northwest (PNW) should focus on farm resource management. The effect of post-harvest residue management on barley residue decomposition has not been adequately studied. Thus, the objective of this study was to determine the effect of residue placement (surface vs. incorporated), residue size (chopped vs. ground-sieved) and soil type (sand and sandy loam) on barley residue decomposition. A 50-day(d) laboratory incubation experiment was conducted at a temperature of 25°C at the Aberdeen Research and Extension Center, Aberdeen, Idaho, USA. Following the study, a Markov-Chain Monte Carlo (MCMC) modeling approach was applied to investigate the first-order decay kinetics of barley residue. An accelerated initial flush of residue carbon(C)-mineralization was measured for the sieved (Day 1) compared to chopped (Day 3 to 5) residues for both surface incorporated applications. The highest evolution of carbon dioxide (CO 2 )-C of 8.3 g kg -1 dry residue was observed on Day 1 from the incorporated-sieved application for both soils. The highest and lowest amount of cumulative CO 2 -C released and percentage residue decomposed over 50-d was observed for surface-chopped (107 g kg -1 dry residue and 27%, respectively) and incorporated-sieved (69 g kg -1 dry residue and 18%, respectively) residues, respectively. There were no significant differences in C-mineralization from barley residue based on soil type or its interactions with residue placement and size (p >0.05). The largest decay constant k of 0.0083 d -1 was calculated for surface-chopped residue where the predicted half-life was 80 d, which did not differ from surface sieved or incorporated chopped. In contrast, incorporated-sieved treatments only resulted in a k of 0.0054 d -1 and would need an additional 48 d to decompose 50% of the residue. Future residue decomposition studies under field conditions are warranted to verify the residue C-mineralization and its impact on residue management.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Surface Atmosphere Integrated Field Laboratory (SAIL) Science Plan

Mountains are the natural water towers of the world, effectively turning water vapor into readily available fresh water through precipitation, snowpack, and runoff. Unfortunately, Earth system models (ESMs) have persistently been unable to predict the timing and availability of water resources from mountains because the source(s) of model error are difficult to isolate in complex terrain with limited atmospheric or land-surface observations. Further complications arise from the gross scale mismatch between ESM grid box sizes and the relevant scales of mountainous hydrological processes. The mountain hydrometeorology community has repeatedly called for integrated atmospheric and land observations of water and energy budgets in complex terrain that span these scales to establish benchmarks against which scale-dependent models can be further developed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Abstract for CRADA between NETL and H2 Resources Pty Ltd.

NETL and H2 Resources Pty Ltd. will collaborate under this CRADA project to evaluate and design a scaled-up microwave assisted coal gasification process on Australian low-rank coal. This project will include parametric studies on the top size of feed coal using continuous feed microwave capabilities at NETL.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Reticular Materials and AI-Driven Computer Simulations for Seawater Mining of Valuable Metals (Final Technical Report)

This Final Technical Report describes our exploratory efforts that combine reticular materials synthesis (hydrolytically robust metal–organic frameworks, MOFs) with AI‑enabled molecular simulations to develop mechanistic, quantitative design rules for recovering lithium and other alkali-metal ions from highly dilute, competitive aqueous resources (e.g., seawater). The central outcome is a joint experimental–computational study of ion uptake in MOF‑808 (Chemical Science, 2025) that quantifies both thermodynamics and kinetics of Li + , Na + , and K + uptake and identifies how pore size, pore hydration state, dehydration penalties, and pore-window transport barriers govern selectivity. Guided by these insights, we synthesized and tested functionalized MOF‑808 and multivariate MOFs incorporating ion-recognition motifs (including carboxylates and crown-ether linkers) and evaluated uptake in synthetic seawater, highlighting framework topology and pore chemistry as levers for improved Li + /Na + discrimination. We also developed transferable simulation models, enhanced-sampling protocols, and automated workflows that enable systematic screening of porous sorbents.

42 ENGINEERING↗
DOE OSTI2026

Performance Characterization of InCharge™ ICE-66 V2X Bidirectional DC Fast Charger

Vehicle-to-grid (V2G) technology extends the role of Plug-in Hybrid Vehicle’s (PHEV) and Battery Electric Vehicle’s (BEV) batteries beyond transportation by enabling bidirectional power transfer between the vehicle's onboard energy storage and the utility grid. Modern battery-powered vehicles are equipped with high-capacity battery packs that remain stationary and underutilized for the majority of their operational life. A vehicle used for daily commuting may be parked and connected to charging infrastructure for 18–20 hours per day, representing a significant untapped energy resource. When considered at scale, the aggregated storage capacity of a modest fleet of 10–15 vehicles within a single parking facility can reach the MWh range, sufficient to partially offset peak demand for a mid-size commercial building or contribute meaningful ancillary services to the local grid. The ability to charge during off-peak periods when electricity prices are low and discharge during peak demand when prices are high positions EV batteries as distributed energy arbitrage assets, with the potential to offset vehicle ownership and charging costs. Beyond energy arbitrage, V2G-capable assets can provide ancillary grid services through active and reactive power injections. Active power supports grid frequency regulation, while reactive power supports local voltage regulation. Together, these capabilities establish V2G as a technically promising and economically relevant pathway toward greater integration of battery-powered vehicles into the broader energy system.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Maximizing the Benefits of On-Site Renewable Energy Generation Using On-Site Energy Storage

The commercial and industrial building sectors have a major role to play in a U.S. low-carbon future. Building owners can make a difference by deploying on-site renewable generation and storage technologies, which facilitates future-proofing their buildings as well as more effectively meeting the service requirements of the building. This resource provides an overview of common generation, storage, and load management technologies in behind-the-meter systems, and serves as a primer to demonstrate the impact on net building loads required from the grid for different sizes of renewable generation along with on-site electrical and thermal storage. These discussions can help commercial building owners communicate the value of these systems to project teams and develop innovative behind-the-meter solutions to achieve their energy goals.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2023

Impact of system parameters and geospatial variables on the reliability of residential systems with PV and energy storage

A reliable power supply is the foundation of modern society, enabling technologies used to function within a society. Residential systems are places where the end users directly consume power, enabling technologies to sustain life. With the emergence of behind-the-meter resources, the end-users have some control over power supply reliability. The intermittency and variability of these resources impact residential system reliability. In this work, we study the reliability performance of a grid-supplemented residential system with behind-the-meter Distributed Energy Resources(DER) subject to various system parameters and geospatial variables. We propose a multistate reliability model for the behind-the-meter microinverter-based Photo Voltaic (PV) system and integrated inverter-based energy storage (ES) system. A sequential Monte Carlo method is then presented to evaluate the reliability indices for the residential system with behind-the-meter DERs as the main supply and the grid as the backup. The sequential Monte Carlo method is used to analyze the reliability performance of the residential model at the top 100 populous counties of the United States, where actual load and solar irradiance data at the counties is used. In the analysis, the sensitivity of indices to system parameters such as DER size and the sensitivity of the indices to climate zone and gross horizontal irradiation (GHI), which affects the load conditions and the PV output of the residential system, is performed. The analysis results show that the system parameters and the geospatial variables significantly impact the residential system’s reliability. The insights from this analysis will be of immense value to the distribution system planners to provide zone-specific guidelines for DER system sizing and toward the evolution of utility business models. Finally, the methodology developed can be used to extend the analysis to other locations.

14 SOLAR ENERGY↗
DOE OSTI2022

Wind and Solar Hybrid Power Plants for Energy Resilience

Wind-solar-storage hybrid power plants represent a significant and growing share of new proposed projects in the United States (U.S.). Their uptake is supported by increasing renewable energy market share, technical abilities for dispatch and control, and decreasing wind, solar, and battery storage costs. Simultaneously, generation and storage resources are increasingly used in distributed power systems. While concerns around the reliability of the aging, transforming U.S. electric grid are growing, diversifying energy resources through hybridization or spatial distribution provides an opportunity to enhance power system resilience compared to single-source generation. Understanding where to build hybrids for resilience value, rather than bulk power supply, has not been fully explored in previous studies. Therefore, in this study, we complete a national complementarity analysis to identify areas in the U.S. that are particularly suited for wind-solar hybrid power plant development. We show the importance of seasonal and diurnal patterns in assessing complementarity, and identify that regions in the Great Plains, Midwest, and Southeast are particularly suited for hybrid power plants. We demonstrate the resilience value of hybridization for a reference system based near Memphis, Tennessee, and show optimal sizing of wind, solar, and storage assets given 1.0 and 0.9 critical load factors. Results indicate that pairing wind and solar assets better meet constant load demand and reduce storage requirements compared to solar alone. These results enable future work integrating complementarity metrics in resilience frameworks and indicate a need for more finer resolution of local resource, demand, and hazard data.

14 SOLAR ENERGY↗