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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

Utility Perspective on Protection Challenges with High Penetration of IBRs

Utilities have seen rapid increase in Solar, Wind, and Battery Energy Storage Resources that interconnect to their electric system through Inverters. Inverter-Based Resources (IBRs) have fault current characteristics that are unlike the fault current response of traditional rotating-machine-based generators, which is well known and repeatable. IBR’s non-traditional fault current behavior is due to the IBR control scheme, which is configured to provide a clean AC output but also protect the inverter’s sensitive power electronics devices from damage, one source of which is overcurrent. This results in low fault current magnitude, low or no negative sequence current injection, the variability of sequence component currents, the variability of voltage with respect to current angles, and the lack of inertia. The control scheme also results in a fault current response that can vary between manufactures and between models of the same manufacturer. High penetration of IBRs can adversely affect the protection schemes applied in areas with high penetration of IBRs. With the proliferation of IBRs, utilities are finding out that conventional protection schemes are not adequately equipped to protect the electric systems. This is mainly because the existing protection elements and practices have been designed based on the fault current response of conventional rotating machines. In several cases, the available literature does not provide any clear solution for the issues when the protection scheme does not operate properly near IBRs. This report / presentation identifies various protection challenges due to IBRs that industry is facing, from the utility perspective. Instead of facing on one issue, this report looks broadly on all the challenges that system protection has experienced with high penetration of IBRs. Based on the IBR response from various utilities during real fault events and gathering perspective from different utility SMEs via questionnaire, the report summarizes on gathered data and internal experiences.

14 SOLAR ENERGY↗
DOE OSTI2024

Utility Perspective on Protection Challenges with High IBR Penetration [Slides]

Utilities have seen rapid increase in Solar, Wind, and Battery Energy Storage Resources that interconnect to their electric system through Inverters. Inverter-Based Resources (IBRs) have fault current characteristics that are unlike the fault current response of traditional rotating-machine-based generators, which is well known and repeatable. IBR’s non-traditional fault current behavior is due to the IBR control scheme, which is configured to provide a clean AC output but also protect the inverter’s sensitive power electronics devices from damage, one source of which is overcurrent. This results in low fault current magnitude, low or no negative sequence current injection, the variability of sequence component currents, the variability of voltage with respect to current angles, and the lack of inertia. The control scheme also results in a fault current response that can vary between manufactures and between models of the same manufacturer. High penetration of IBRs can adversely affect the protection schemes applied in areas with high penetration of IBRs. With the proliferation of IBRs, utilities are finding out that conventional protection schemes are not adequately equipped to protect the electric systems. This is mainly because the existing protection elements and practices have been designed based on the fault current response of conventional rotating machines. In several cases, the available literature does not provide any clear solution for the issues when the protection scheme does not operate properly near IBRs. This report identifies various protection challenges due to IBRs that industry is facing, from the utility perspective. Instead of facing on one issue, this report looks broadly on all the challenges that system protection has experienced with high penetration of IBRs. Based on the IBR response from various utilities during real fault events and gathering perspective from different utility SMEs via questionnaire, the report summarizes on gathered data and internal experiences.

14 SOLAR ENERGY↗
DOE OSTI2024

IBR Black Model Lessons Learned (C45)

Blackbox modelling for SC analysis is a possible solution. Accuracy can be acceptable even without having vendor control diagrams. Blackbox modelling is not as user friendly as a generic model. Is an NDA required to share a vendor Blackbox model for SC analysis? Difference in VRT detection and injection logics. Angle rotation is not addressed. Current limitation logic during unbalanced faults is not clear.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

SMART – A Comprehensive Research and Development Program to Demonstrate Application of Machine Learning for Supporting CCS Deployment

Presentation material for a paper presented at the GHGT-17 conference, Calgary, Canada, October 20-24, 2024. The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.

CO2 geologic storage↗
DOE OSTI2024

SMART – A Comprehensive Research and Development Program to Demonstrate Application of Machine Learning for Supporting CCS Deployment

The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.

Siriwardane, Hema↗
DOE OSTI2025

Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties

This project developed machine learning (ML) methods, lab data sets, and field data to advance geothermal exploration and geothermal energy production. The work had three focus areas. One involved the development of ML methods to use microearthquakes (MEQs) for imaging geothermal reservoir properties and improving subsurface characterization – most importantly the evolution of permeability within the evolving reservoir. This part of the work included development of ML approaches for automated MEQ location, focal mechanism determination and identification of earthquake precursors. The second area focused on using MEQ signals generated by geothermal exploration and production to predict the relationship between fluid injection and seismicity. Here, we extended to reservoir scale our success in using ML to predict laboratory earthquakes and fault zone stress state. The third focus area was on lab experiments. Here, we developed new ML models for lab earthquake prediction and identification of precursors to failure to improve earthquake forecasting and early warning in geothermal settings. Major outcomes of our work include ML models that learn from MEQ signals during geothermal exploration and production to predict induced seismicity. MEQs occur naturally in connection with drilling and energy production. We developed ML methods to use the seismic waves from these events to characterize the elastic, hydraulic and poromechanical properties of reservoirs. Our work illuminated fracture geometry and the evolution of fracture permeability by incorporating seismic coda wave analysis and ML methods to relate fluid injection and seismicity. We significantly expanded laboratory earthquake prediction to include methods that use both passive measurements of microearthquakes within the lab fault zones and also active source acoustic measurements of fault zone elastic properties. These methods can now predict fault zone stress state, time to failure and the magnitude of lab earthquakes. Our work showed that repetitive stick- slip failure events during frictional sliding (the lab equivalent of earthquakes) are preceded by a cascade of micro-failure events that radiate energy in a manner that foretells unstable failure – manifest as laboratory MEQs. We documented a mapping between fracture properties and statistical attributes of elastic radiation. We extended existing works to geothermal reservoir scale and developed ML methods to determine reservoir permeability, fracture properties, and their evolution during geothermal energy production. An attractive feature of ML algorithms is their ability to handle big datasets and reveal patterns and correlations that may remain invisible to conventional analyses. Our work connected data from field, laboratory and intermediate scales to study permeability, stress, strength, fracture stiffness and geometry. At the field scale we used data from the Newberry Volcano field site, UtahFORGE, EGS Collab, and also the Bedretto underground research lab in Switzerland. These data sets are bridging the gap between the lab scale, theory, and reservoir scale. Our work produced plain language summaries to improve public understanding of DOE research. We also developed openly distributed ML and seismicity datasets for use by all researchers and we published connections between induced seismicity in geothermal areas and reservoir properties including permeability, fracture properties, and stress state. Our models are designed for the large data sets of induced seismicity typically associated with geothermal sites. We produced labeled event catalogs and used them on geothermal data to assess how ML can facilitate geothermal production and exploration. All datasets are available on the GDR Productivity: The project produced 32 publications in peer reviewed journals (two are in review). It supported the work of 6 PhD students, 40 conference presentations, 6 keynote talks at national meetings, and mentoring and professional development for 4 postdoctoral fellows.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

MRCI Subtask 2.2: Precambrian Basement Structure, Faulting, and Stress Final Technical Summary Report

Subtask 2.2 was largely focused on compiling information about the Precambrian basement rock that underlies the MRCI region. Understanding the nature and extent of the basement rock is important in order to mitigate certain risks associated with CO2 injection. For example, this information will provide a resource for defining areas where a storage reservoir is in direct contact with the Precambrian or indirectly via a fault. Also, an understanding of the stress field in addition to fault orientations will help determine which faults may be subject to reactivation under increased pore pressures.

Battelle,CCS,CCUS,Carbon storage,MRCI,Midwest Regi↗
DOE OSTI2024

Model of Inverter-Based Resources

Blackbox modelling for SC analysis is a possible solution. Accuracy can be acceptable even without having vendor control diagrams. Is an NDA required to share a vendor Blackbox model for SC analysis? Differences in VRT detection and injection logics. Angle rotation is not addressed in control logics of most vendors. Current limitation logic during unbalanced faults is not clear. Model IBR as a current source with shunt to improve convergence

IBRs, Model of IBRs, Short Circuit Analysis, Class↗
DOE OSTI2026

Prairie State Generating Company 2D Seismic Interpretation

The objectives of the Illinois Storage Corridor (ISC) project are to accelerate commercial deployment of carbon capture utilization and storage at two individual sites and receive approvals for Underground Injection Control (UIC) Class VI permits for construction at each site (ISC Project Narrative, 2020). As part of this project, and as part of the subsurface geologic characterization, two-dimensional (2D) seismic data was acquired at both sites. This report summarizes the findings from two phases of 2D acquisition and seismic interpretation at the Prairie State Generating Company site near Marissa, Illinois. The seismic data indicates the presence of three faults that completely transect the storage and confining units. The initial 2021 2D seismic acquisition revealed the presence of a feature two miles east of the Lively Grove #1 characterization well. The feature is a polyphase fault with a component of strike-slip motion, forming a small positive flower structure. The second phase of 2D seismic acquisition in 2022 constrained the maximum extent of the fault, indicating it has a relatively limited length. Other 2022 seismic lines revealed the presence of two other faults that transect the storage and confining units in the southwest and northeast portions of the 2D seismic acquisition area. The 2021 and 2022 2D seismic surveys have identified three specific locations within the project area that may have an elevated risk of out of zone CO 2 migration due to faulting. Further technical work will be needed to quantify this risk and determine how and if this risk will impact the placement of CO 2 injection wells across the project area.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

SDN-Based Dynamic Cybersecurity Framework of IEC-61850 Communications in Smart Grid

In recent years, critical infrastructure and power grids have experienced a series of cyber-attacks, leading to temporary, widespread blackouts of considerable magnitude. Since most substations are unmanned and have limited physical security protection, cyber breaches into power grid substations present a risk. Nowadays, the susceptibility of SDN architecture to cyber-attacks has exhibited a notable increase in recent years, as indicated by research findings. This suggests a growing concern regarding the potential for cybersecurity breaches within the SDN framework. In this paper, we propose a hybrid intrusion detection system (IDS)-integrated SDN architecture for detecting and preventing the injection of malicious IEC 61850-based generic object-oriented system event (GOOSE) messages in a digital substation. Additionally, this program locates the fault’s location and, as a form of mitigation, disables a certain port. Furthermore, implementation examples are demonstrated and verified using a hardware-in-the-loop (HIL) testbed that mimics the functioning of a digital substation.

Liu, Chen-Ching [Virginia Tech] (ORCID:00000002894↗
DOE OSTI2025

Development of advanced vacuum technologies for extending plasma pulse duration on EAST

Advanced vacuum technologies, including pumping, fueling and wall conditioning, have been successfully developed or upgraded to efficiently control the fuel and impurity particles to extend the plasma pulse duration in the experimental advanced superconducting tokamak (EAST). To improve the particle exhaust rate cryopumps with a 60% increase in pumping speed and ∼2 times increase in saturation capacity have been developed, and molecular pumps with a ∼30% increase in pumping speed have been upgraded. In order to monitor the molecular pump status while avoiding bearing faults and overload accidents, a fault detection system has been built which can offer an early warning to avoid more losses within the fusion device. A series of fueling technologies have been developed including gas injection system, supersonic molecular beam injector, pellet injector (PI), massive gas injector and shattered pellet injector, installed at the midplane and divertor positions at different ports to improve fueling uniformity and efficiency. Meanwhile, routine wall conditioning such as electric and hot N 2 baking, ion cyclotron wall conditioning and glow discharge cleaning have been successfully developed to remove the impurity particles from the inner component and materials. The low Z material wall coating and real-time powder injection during plasma discharge are also designed and applied to further improve particle control capability. Finally, by using these advanced vacuum related technologies, good vacuum (<2 × 10 −6 Pa) and wall conditions are realized, and the fuel and impurity particles can be effectively and stably controlled, which promotes the achievement of the record plasma of ∼1056 s pulse duration with the line-averaged electron density of 1.8 × 10 19 m −3 on EAST. They provide a very important reference for vacuum system design and operation for future fusion devices.

EAST↗
DOE OSTI2025

Stratigraphy‐Induced Localization of Microseismicity During CO 2 Injection in Illinois Basin

Abstract Subsurface fluid injection stimulates complex hydromechanical interaction, necessitating the integration of geomechanical data across spatial and temporal scales to consider the sophisticated behavior. Induced seismic response is usually associated with the complex reservoir architecture and pre‐existing features that are three‐dimensional, such as local stratigraphy, fractures, faults, and other discontinuities. This study encompasses laboratory characterization of the coupled hydromechanical response of cores extracted from rock formations in Illinois Basin: reservoir ‐ Mt. Simon sandstone, basal seal ‐ Argenta sandstone, and crystalline basement ‐ Precambrian rhyolite. High‐resolution numerical modeling allows considering the three‐dimensional complexity of the Illinois Basin Decatur Project with spatial resolution comparable to one of the active seismic surveys. A detailed reconstruction of the evolving state of stress in formations lacking direct stress measurements is achieved by numerical modeling that integrated laboratory‐derived hydromechanical properties, a porosity‐permeability relationship, active seismic data, and an inverted three‐dimensional porosity distribution. It appears that the microseismic clusters, mainly observed in the crystalline basement during the injection, are linked to zones experiencing more critically stressed conditions prior to injection. These zones have a potential for reactivation during the injection and are attributed to the specific local stratigraphy of the injection site, as well as transfer of triggering perturbations during the injection.

Bondarenko, N. [University of Illinois Urbana‐Cham↗
DOE OSTI2024

Utah FORGE: Fluid Injection Induced Shearing Experiments on Fractured Granitoid at Elevated Temperatures

This repository contains experimental data from a series of fluid injection-induced shearing tests conducted on Utah FORGE granitoid. The experiments were performed using an aluminum triaxial pressure vessel (TEMCO) apparatus at Pennsylvania State University. The primary aim was to investigate the impact of temperature on fault seismicity and to explore how different pre-stress ratios influence shearing behavior. The data includes results from experiments conducted under varying conditions of temperature, pre-stress ratios, and pore pressure increments. The rock samples used in these experiments were 60-grit granitoid with a single inclined fracture oriented at 60 degrees with respect to the horizontal cross-section. The dataset also includes measurements of normal stiffness at different temperatures and images of the experimental apparatus. The included README file details each experiential setup and outlines which data files represent which experimental conditions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Innovations in underground hydrogen storage with multiphysics simulations, optimization, and monitoring: A review

Underground Hydrogen Storage (UHS) is a promising solution for large-scale energy storage and a critical component in advancing low-carbon energy system. Ensuring the safety and efficiency of UHS necessitates a comprehensive understanding of multiphysical interactions driven by cyclic pore fluid pressure fluctuations and coupled physicochemical processes. Here, this review examines the key geomechanical responses in UHS, including rock property variations under cyclic loading, fracture evolution and propagation, reservoir stress sensitivity, and fault stability. It also explores the impact of geochemical and microbial reactions on geomechanical characteristics. We provide an in-depth analysis of Thermal-Hydraulic-Mechanical-Chemical (THMC) coupled numerical simulations, highlighting their potential for future multi-scale modeling. Limitations of current machine learning (ML) approaches in addressing UHS challenges are highlighted, emphasizing the need for innovative ML-based methodologies. Operational strategies for hydrogen injection and production are reviewed, focusing on safety, efficiency, and economic viability. The necessity for multi-objective optimization (MOO) to balance storage efficiency, risk mitigation, and cost-effectiveness is also discussed. Current monitoring technologies are evaluated to ensure safe and efficient UHS operations. Finally, this review identifies critical knowledge gaps and underscores the importance of advancing geomechanical understanding under multiphysics-coupling. We highlight the need for ML-driven multiphysics theories, enhanced modeling techniques, and robust optimization strategies to improve UHS performance. This study serves as a comprehensive reference for future research and the large-scale implementation of UHS systems.

25 ENERGY STORAGE↗
DOE OSTI2026

One Earth Energy Seismic Interpretation

The objectives of the Illinois Storage Corridor (ISC) project are to accelerate commercial deployment of carbon capture utilization and storage at two individual sites and receive approvals for Underground Injection Control (UIC) Class VI permits for construction at each site (ISC Project Narrative, 2020). As part of this project, and as part of the subsurface geologic characterization, 2D seismic data was acquired at both sites. This report summarizes the findings from the 2D and 3D seismic interpretation at the One Earth Energy site near Gibson City, Illinois. The seismic data confirms the stratigraphic continuity of the Mt. Simon Arkose Zone storage interval and the Eau Claire confining unit across the project area. The seismic data also indicates that there are faults that transect the Mt. Simon Arkose Zone Sandstone storage reservoir within the modeled CO 2 plume (for more detailed information, see Faults and Fractures section of One Earth Energy Class VI Permit applications). However, the seismic data also shows that there are no faults within the modeled CO 2 plume that transect the confining unit Eau Claire Formation. The faults that transect the Mt. Simon Arkose Zone Sandstone storage reservoir all tip out in the Lower Mt. Simon Formation and do not reach the overlying Eau Claire confining unit. A small 3D survey acquired around the One Earth Energy #1 characterization well confirms these findings.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Optimizing Alabama’s CO 2 Storage in Shelby County (Project OASIS) Milestone 6.0: Evaluation of Class VI Readiness

Introduction. Project OASIS is approximately 30 miles southeast of Birmingham, Alabama, and approximately 5 miles north-northwest of Alabama Power Company's Plant Gaston. Geologically, the Project area is in the Alabama fold and thrust belt province. This work builds on the initiatives of the Southeast Regional Carbon Utilization and Storage Acceleration Partnership (SECARB-USA, DE-FE0031830) that identified nearly 500 million metric tonnes of CO 2 emitted on an annual basis that is not collocated with prospective storage geology (the Coastal Plain of the Southeastern US in this context). This observation suggests costly investments in connective infrastructure (e.g., pipelines) or exploratory well drilling campaigns to identify CO 2 storage opportunities in under explored areas. While not traditionally thought of for saline storage, these studies suggest that storage prospects in the Valley and Ridge Province occur in relatively flat lying structural panels between thrust faults. For the Project OASIS region, available geologic studies related to hydrocarbon exploration suggest that Cambro-Ordovician carbonates and Cambrian clastic units offer multiple potential storage intervals, and that regional confining systems are present, such as the tectonically thickened Floyd-Parkwood Shale. The Project OASIS surface property is owned by a timber and land stewardship company, The Westervelt Company, Inc., who worked with the Project Team to select and prepare adequate sites for geologic assessment. The purpose of drilling the Westover Stratigraphic Test Well #2 was to collect geologic data to model the feasibility of commercial scale CO 2 injection and storage in an under explored region. This initiative benefits the regions emitters as the data generated from this study can inform their own internal decision making. The field program included geological and geophysical evaluations, reservoir engineering analyses, and risk assessments. This report evaluates existing data, as well as a variety of modeling scenarios to evaluate project readiness. Importantly, the impact of this study is not limited to Alabama as there are numerous large emitters throughout Appalachia, in similar geologic settings, contemplating their decarbonization options.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

FracML: A Machine Learning Based Tool to Quantify Reservoir Scale Fracture Network for CO2 Storage

Poster on “FRACML: A Machine Learning Based Tool to Quantify Reservoir Scale Fracture Network for CO2 Storage” for the CCUS 2025 conference held in Houston, Texas March 3-5, 2025. The accurate characterization of subsurface fracture networks is essential for the secure operation of carbon capture, utilization, and storage (CCUS) projects. A thorough understanding of the spatial distribution of subsurface faults and fractures is crucial for predicting CO2 plume evolution and minimizing risks such as potential leakage into overlying formations or induced seismicity. In this context, robust fracture network quantification plays a pivotal role in reservoir management, providing the data necessary to fine-tune operational parameters, and ensure the environmental and economic viability of CCUS projects. As part of the U.S. Department of Energy’s SMART (Science-informed Machine Learning for Accelerating Real-time Decisions in Subsurface Applications) initiative, we focused on the development and application of a machine learning-based tool (FRACML) designed to quantify and map fracture networks using real-world (non-synthetic) data from an active CO2 injection site. Our objective is to demonstrate the utility of this tool in improving operational efficiency and safety across CCUS sites.

artifical intelligence / machine learning (AI/ML)↗
DOE OSTI2025

Critical Clearing Time for Droop-Controlled Grid-Forming Inverters With Circular Current Limiting and Virtual Impedance Current Limiting

The critical clearing time is a crucial parameter for assessing the large-signal stability of grid-forming (GFM) inverters. Variations in current limiters can significantly impact an inverter's transient behavior during large disturbances. Here, this letter introduces a method based on the power-angle relationship to evaluate the fault recovery of a droop-controlled GFM inverter under a three-phase bolted fault scenario, considering both the circular current limiter and the virtual impedance method. High-fidelity simulations validate the accuracy of the proposed formulas in estimating the critical clearing time of the GFM inverter.

42 ENGINEERING↗