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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Introducing the 9500 Node Distribution Test System to Support Advanced Power Applications: An Operations-Focused Approach

The 9500 Node Test System is a representative section of distribution power system model developed as a part of the GridAPPS-D™ project, an effort funded by DOE as a part of the Grid Modernization Lab Consortium (GMLC) program. The test system was developed to fulfill a growing need to represent the rapidly evolving state of electric distribution systems by combining elements of legacy infrastructure systems, modern feeder topologies, and an anticipated future with smart grid technologies. It also provides a network model capable of supporting the simulation of operational scenarios such as the ones in a utility distribution control center. This test system allows the evaluation of the performance of advanced power applications in real-time, such as one that simulates the operations of an Advanced Distribution Management Systems (ADMS), Distributed Energy Resource Management Systems (DERMS), etc. in a Distribution control center. This model is an extension of the widely used IEEE 8500 Node Test Feeder and is currently being validated to become an IEEE test case to help increase adoption and widespread usage among both academia and industry. It is a full-size model representative of a section of a utility’s distribution system with multiple feeders fed from different substations. The model includes multiple distribution circuits, a sub-transmission system, multiple substations, behind the meter customer rooftop photovoltaics (PV), and multiple utility-scale distributed energy resources. To enable accurate simulations of operational scenarios, the 9500 Node Test System is designed to support procedure-based operations, with the ability to realistically demonstrate switching operations, feeder reconfiguration, adjustment of volt-var control equipment, dispatch of distributed generation, and response to planned and unplanned outages. The 9500 Node Test System includes three radial distribution feeders with 12.3 MVA of average load, consisting of both medium voltage and low voltage equipment each supplied by a different distribution substation. The three distribution feeders are connected to each other through Normally-Open switches which can be closed when needed to simulate restoration scenarios due to a fault. One feeder represents today’s grid with low penetration of customer-side renewables. The second represents a potential future grid with microgrids and 100% renewable penetration. The third has no customer generation resources, a district steam plant, and a utility-scale solar farm. The three diverse circuits were created to allow the simulation of both today’s situation as well as potential future scenarios. All three feeders have customers connected by low-voltage secondary triplex lines. This test system meets all requirements outlined in the report for creating a simulation environment that would enable discussion between key technical stakeholders as well as having the potential to accelerate operational application development and their subsequent testing and integration. The new model is a possible representation of what we believe the distribution grid may look like in the future: a high penetration of renewables, reconfigurable radial and mesh topology, numerous DERs, islanded microgrids, and significantly increased data and measurement density. The system supports both the solution of existing and newer algorithms but also enables the evaluation of applications in a realistic operational environment defined by task oriented procedural steps that represent the interaction between the control center operator and field personnel.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Feasibility of fusion plasma burn control via real-time, sub-divertor neutral gas isotopic and compositional analysis

The ability to provide fusion burn control without requiring physical access through the first wall and fuel breeding blankets, would be vital for any future, magnetically confined fusion power reactor. A multi-sensor, fusion fuel cycle exhaust, neutral gas analysis system on JET, capable of delivering real time data, and accessing only the sub-divertor region, provides an excellent example of such capability. Optimized for and operated during the deuterium–tritium experimental campaigns 2 and 3 (DTE2, DTE3), it is proving valuable for planning to explore fusion reactor burn control in ITER with a comparable diagnostic system called the Diagnostic Residual Gas Analyzer (DRGA). This paper aims to show feasibility of developing model-based controllers for ITER and next generation, reactor-relevant devices, by building both on the empirical experience in JET-DTE2, and on the already emerging experience on developing such models specifically for ITER. The paper begins with a specific use-case from JET-DTE2, pertaining to the observed sensitivity of the fusion neutron yield on the concentration of isotopic helium-3 ( 3 He), with data from one of the high-performance DT shots exhibited with emphasis on the 3 He measurement via the sub-divertor. Then, a first model is developed and then explored with simulations that aim to discover how well the controllers in the model react to either insufficient levels of 3 He or excessive levels of 3 He. The simulations then explore potential impact from a delay in the measurement (or the response) that would be comparable to the ∼1 s, conductance limited response for the ITER DRGA system, currently in its final design. The simulations show that control is feasible, and that its effectiveness is not significantly impacted by such delay.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Deep Reinforcement Learning for Resilient Power and Energy Systems: Progress, Prospects, and Future Avenues

In recent years, deep reinforcement learning (DRL) has garnered substantial attention in the context of enhancing resilience in power and energy systems. Resilience, characterized by the ability to withstand, absorb, and quickly recover from natural disasters and human-induced disruptions, has become paramount in ensuring the stability and dependability of critical infrastructure. This comprehensive review delves into the latest advancements and applications of DRL in enhancing the resilience of power and energy systems, highlighting significant contributions and key insights. The exploration commences with a concise elucidation of the fundamental principles of DRL, highlighting the intricate interplay among reinforcement learning (RL), deep learning, and the emergence of DRL. Furthermore, it categorizes and describes various DRL algorithms, laying a robust foundation for comprehending the applicability of DRL. The linkage between DRL and power system resilience is forged through a systematic classification of DRL applications into five pivotal dimensions: dynamic response, recovery and restoration, energy management and control, communications and cybersecurity, and resilience planning and metrics development. This structured categorization facilitates a methodical exploration of how DRL methodologies can effectively tackle critical challenges within the domain of power and energy system resilience. The review meticulously examines the inherent challenges and limitations entailed in integrating DRL into power and energy system resilience, shedding light on practical challenges and potential pitfalls. Additionally, it offers insights into promising avenues for future research, with the aim of inspiring innovative solutions and further progress in this vital domain.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Strongly Coupled Plasmon and Phonon Polaritons as Seen by Photon and Electron Probes

The ability to control and modify infrared excitations in condensed matter is of both fundamental and applied interest. Here we explore a system supporting low-energy excitations, in particular, mid-infrared localized plasmon modes and phonon polaritons that are tuned to be strongly coupled. We study the coupled modes by using far-field infrared spectroscopy, state-of-the-art monochromated electron energy-loss spectroscopy, numerical simulations, and analytical modeling. Here we demonstrate that the electron probe facilitates a precise characterization of polaritons constituting the coupled system, and enables an active control over the coupling and the resulting sample response both in frequency and space. Although far-field optical spectra can be substantially different from near-field electron energy-loss spectra, we show that a direct comparison is possible via postprocessing and right positioning of the electron beam. The resulting spectra allow us to evaluate the key parameters of the coupled system, such as the coupling strength, which we demonstrate to be probe independent. Our work establishes a rigorous description of the spectral features observed in light- and localized electron-based spectroscopies, which can be extended to the analysis of analogous optical systems with applications in heat management and electromagnetic field concentration or nanofocusing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Improving Distribution System Operations Using Fleet Control of Electrolyzers

The proliferation of electrolyzers presents an opportunity for grid operators. Fast response times and the use of hydrogen as storage can be leveraged in a symbiotic way to support increasing penetration levels of photovoltaics (PV) in the distribution grid. This work presents the grid integration of an electrolyzer fleet and its control applications to minimize the impact of increasing solar PV penetration in the distribution network. The study involves a feeder model of a real utility circuit from a utility partner with an operational model of a fleet of electrolyzers. The operational improvements are quantified with performance metrics. The metrics show that the fleet control application of the electrolyzers can aid in reducing overvoltages, voltage fluctuations, and control device operations induced by intermittent solar generation. The locational dependence of electrolyzers are also discussed in terms of performance metrics.

39 EE - Hydrogen and Fuel Cell Technologies (EE-3F↗
DOE OSTI2024

System and method for in situ volumetric sensing of 3D cure state of resin being used in an additive manufacturing system

An in situ cure monitoring control system for use with a volumetric three dimensional (3D) printing system, wherein the volumetric 3D system includes a container defining a build volume, the container includes a photocurable resist used for making a 3D part, and the resist is responsive to an optical curing beam from a light source, which is controlled by a controller, and which is passed through the resist. The cure monitoring control system includes an optical signal source which generates optical signals having a wavelength selected in relation to a characteristic of the resist, and directed to pass through the build volume. A detector detects the optical signals and generates output signals in accordance therewith. Software monitors the output signals and uses the output signals to modify the curing beam to help optimize curing of the resist.

Panas, Robert Matthew↗
DOE OSTI2022

Autonomous System Subversion Tactics: Prototypes and Recommended Countermeasures

One of the fielding requirements for Advanced and Small Modular Reactors (AR/SMR) is the ability to support remote and autonomous operations. Autonomous Control Systems (ACS) are found on platforms such as Autonomous Space Vehicles, Cruise Missiles, and advanced driver-assistance systems. Each of these ACS implementations depends upon a set of decision support subsystems responsible for supporting Autonomous Mission Managers (names vary based upon field and author preferences). These Autonomous Mission Managers receive inputs from system sensors (e.g., LIDAR collection from an automobile travelling down a street; transients from a nuclear reactor), and perform a set of classifications (e.g., Red Traffic Light; Small Pedestrian at 10m; Load Rejection; Single Coolant Pump Trip), and then use these classifications in combination with recommendation algorithms to achieve platform goals (e.g., Stop the Vehicle at the Traffic Light, Avoid the Small Pedestrian; Trip the Reactor to prevent a Safety Event). The design, implementation, and fielding of an ACS capability will alter the cyber-attack surface such that existing risk management plans will need to be updated to include how to protect and defend against data-science and decision-support-system attack classes. These attack classes would include protection of the design and training environments where algorithm selection and testing and training data would be obvious attack vectors. These attack classes would also require an informed set of detection and response procedures to identify anomalous behaviors and document best practices for anomaly assessment and vulnerability mitigation and remediation. Last year we published a Cyber Threat Assessment Methodology for Autonomous and Remote Operations for AR/SMRs along with a companion publication on Cyber Attack and Defense Use Cases. The focus of the methodology was on describing and enumerating ACS processes, components, and functions such that security engineers could: evaluate subversion options against the target; identify threat actor attributes and capabilities derived from each subversion option; and identify security controls and response countermeasures. The Use Cases document offered detailed methodology examples including an assessment of a Military Base SMR, an Autonomous System Decision Loop, and implementation of AR/SMR Machine Learning algorithms. Our proposal at the end of last year was to focus on implementation of subversion prototypes related to the last Use Case area: AR/SMR Machine Learning (ML) Algorithms. We included six attack scenarios in our Use Cases paper: a Poisoning Attack against ML functions implemented using an FPGA; a Trojaning Attack against ML classifiers exploiting the excitability of Nuclear Engineers; a Backdooring Attack against ML Training environments to ensure persistence of an attack vector; a False Positive Evasion Attack against multi-factor Access Control Systems using clever inputs; an Inference Attack against ML models by an Insider with access to the Operational environment; and an Adversarial Reprogramming Attack against a Material Access Control Video Surveillance System. At the beginning of this year these six attack scenarios were provided to our research teams at Georgia Tech and Idaho State University and each team successfully implemented a subversion attack against a ML implementation to include transient misclassifications. While this is a notable outcome from this type of research, this paper offers the reader insight into not only how to structure and execute these types of attacks, but into the thought process behind how the researcher investigated the problem space, performed initial algorithm implementation, and the trial-and-error behind arriving at the successful subversion prototypes. We include in this paper a set of associated Scenarios on how these subversion prototypes could be implemented and an initial set of guidance for AR/SMR architects, Nuclear Regulators, and Cyber Defenders to implement awareness and defense capabilities into their current operational portfolios.

42 ENGINEERING↗
DOE OSTI2025

Artificial intelligence-based predictive modeling for imaging neutral particle analyzers on the DIII-D tokamak

The Imaging Neutral Particle Analyzer (INPA) at DIII-D is a diagnostic system used to accurately resolve the energy and spatial distributions of fast ions in fusion plasmas. A novel artificial intelligence (AI) technique named INPA-net is based on Reservoir Computing Networks and developed here to predict active and passive signals produced by charge-exchange reactions from injected and edge-cold neutrals, respectively, in magnetically confined fusion plasmas. This model is trained using a set of 21 time domain signals between 0 s to 3.35 s that includes injected beam and thermal plasma information, and 6444 real 2D experimental images of the INPA in 12 plasma discharges at DIII-D. The trained neural network is able to forecast experimental images in real-time. The model achieves an R-squared value of 0.91, which is higher than the 0.83 value achieved by a simple linear regression model. This improvement highlights the model's enhanced predictive accuracy for measured images from the validation set. This AI approach is valuable due to its rapid response times and potential for integration into real-time plasma control systems. A version of this model capable of generating syntehic images would be useful for the real-time monitoring of fast-ion transport. A comprehensive sensitivity study reveals that INPA-net maintains high performance even with variations in the input parameters, indicating the model's robustness and reliability. While developed for the INPA, the underlying architecture is adaptable and may be applied to various 2D imaging diagnostics in fusion research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Integrate FARM with PID controllers: IES Simulation Ecosystem Control System Development

The FARM (Feasible Actuator Range Modifier) software module is a component of the RAVEN-based FORCE framework for analysis of Integrated Energy Systems (IES). FARM was designed to support the HERON software module in the solution of the optimal dispatch problem for IES units. As the result of HERON-FARM dispatch simulation, the set-point trajectories are optimized to meet constraints on both the production variables (i.e., the variables to be optimized such as the electrical power, the hydrogen production rate, etc.) and the process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.) at a coarse time resolution (every 10 or 100 seconds) over long time horizons (several days or weeks). In case the operational constraints need to be met at finer time resolution, the computational burden of HERON-FARM would linearly increase with the sampling rate, and sub-optimal solutions might be obtained. System responses characterized by overshoots and damped oscillations temporarily violating the imposed constraints might occur during abrupt power transients. In this report, a hierarchical control system architecture for the operation of the Dynamic Energy Technology and Integration Laboratory (DETAIL) facility constructed at INL was proposed. First, the preliminary studies on the proposed control strategy for operating the facility and the designed PI controllers were reviewed. In particular, the current approach for generating the set-point trajectories was studied, and its limits were identified. To this aim, the inclusion of a Supervisory Control layer embedding a modified version of the FARM algorithm for preserving the system safe operation over both long and real-time horizons was proposed. In this way, FARM would be applied twice, i.e., the original version (“FARM Validator”) aiding the solution of the power dispatch problem, and the modified version (“FARM Supervisory” coordinating the PI controllers to address the real-time control tasks. Despite the kernel of the two modules is the same algorithm, their roles, tasks, and capabilities are quite different. A detailed description of the role of FARM at addressing low-level control tasks is provided, along with tentative operational procedures for training the models embedded into the algorithm by using the collected experimental data.

42 ENGINEERING↗
DOE OSTI2024

eGridGPT: Trustworthy AI in the Control Room

This report outlines the synergy between human decision making and generative artificial intelligence (GenAI), where GenAI supports power system operators by analyzing procedures, suggesting actions, simulating scenarios with physics-based digital twins, and recommending optimal decisions. This report is the first research effort to apply large language models (LLMs), a type of GenAI, in the power grid control room. The authors describe the Electric Grid Generative Pretrained Transformer (eGridGPT), an LLM that virtually assists system operators. Developed with cybersecurity and regulatory requirements in mind, eGridGPT represents an opportunity to responsibly evolve control room technologies to meet the needs of a rapidly changing grid. As an innovative concept, eGridGPT seeks to spearhead productive discussions about the advanced technologies in the control room of the future amid the transition to clean energy.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Shape-constrained Input Estimation for Efficient Multi-shaker Vibration Testing

Multi-shaker vibration testing is gaining interest from structural dynamics test engineers as it can provide a much more accurate match to complicated field vibration responses than traditional single-axis shaker tests. However, the force capabilities of the small modal shakers typically used in multi-shaker vibration tests has limited the achievable response levels. To date, most multi-shaker vibration tests have been performed using a variety of standard, commercially-available control systems. While these control systems are adequate for a wide range of multiple-input/multiple-output tests, their control algorithms have not been tailored for the specific problem of multi-shaker vibration tests: efficiently coordinating the various shakers to work together to achieve a desired response. Here, a new input estimation algorithm is developed and demonstrated using simulations and actual test data. This algorithm, dubbed shape-constrained input estimation, is shown to effectively coordinate multiple shakers using a set of constraint vectors based on the deflection shapes of the test structure. This is accomplished by using the singular vector shapes of the system frequency response matrix, which allows the constraint vectors to automatically change as a function of frequency. Simulation and test results indicate a significant reduction in the input forces required to achieve a desired response. Finally, the results indicate that shape-constrained input estimation is an effective method to achieve higher response levels from limited shaker forces which will enable higher level multi-shaker vibration tests to be performed.

42 ENGINEERING↗
DOE OSTI2022

Port Impedance Measurement and Current Injection Response Analysis for PLCs

Programmable Logic Controllers (PLCs) are used to control devices throughout the power system since they have fast control capabilities and can utilize multiple types of communication interfaces. Therefore, studying and mitigating their vulnerabilities to electromagnetic pulse is important for the reliability of PLC operations. Here, in this paper, an effective impedance measurement scheme is proposed and demonstrated for three PLCs to estimate their susceptibility to an electromagnetic pulse. The equivalent non-uniform transmission line model is established to eliminate the impact of the fixture in the de-embedding process. Then different parameters of the impedance measurement setup are explored. Based on the measured impedance, the equivalent circuit is established to calculate the response of the device when subjected to the electromagnetic pulse. The voltage and current responses of different interfaces are compared utilizing the developed pulsed Current Injection (CI) method. Finally, the impedance measurement scheme is verified through testing using three measuring instruments. And the CI simulation experiments reveal the characteristics and susceptibilities of different PLCs interfaces, indicating that some protection measures are required for the reliable operation of the PLC.

42 ENGINEERING↗
DOE OSTI2022

CRADA Number NFE-19-07846 with Grid Fruit, LLC (CRADA Final Report)

Cooperative Research and Development Agreement (CRADA) NFE-19-07846 between Oak Ridge National Laboratory (ORNL) and Grid Fruit, LLC (Grid Fruit) focused on simulating, monitoring, and adjusting controls of commercial refrigerator and freezer systems to provide load flexibility and demand response services from these machines. Viewing these medium and low-temp coolers as thermal masses, the volumes of chilled air in these coolers make them time-shiftable loads ripe for deployment at optimal times. Grid Fruit is a startup company developing methods to schedule the chilling cycles (e.g., in “build load” and “shed load” grid events) to provide energy efficiency, peak shifting, and other benefits both to the grid and the broader environment. These benefits can be magnified by coordinating chillers with HVAC, lights, computers, and other loads. Grid Fruit completed simulations and then selected and ordered controls hardware to prove the technology were successful, but the diversity of chiller models in the field without digital controls, as well as limited market demand at present, make further exploration necessary before commercialization.

42 ENGINEERING↗
DOE OSTI2022

Sizing Considerations for EV Dynamic Wireless Charging Systems with Integrated Energy Storage

Roadways with dynamic wireless charging systems (DWCS) enable charge-sustaining in-motion EV charging, which can reduce charging idle time while increasing range capabilities. Spatially distributed transmitter coils are controlled in response to traffic load that varies significantly minute to minute with high power levels, very short charging time, and low system utilization like wind turbine power. Traffic load estimation and localized analysis may guide effective sizing and topology adoption for feasible and scalable DWCS deployment. DWCS traffic load approximation is reviewed with measured Automated Traffic Recorder (ATR) data and statistical distributions being used to create a synthetic load analyzed using proposed metrics quantifying system utilization over time. Lumped coil section segmentation is compared between second-based distance and spatial density analysis methods, offering 17-27% greater system utilization. A peak load shifting method is proposed for traffic redirection across two tracks with optional BESS integration increasing system utilization by 50-60% depending on time-based and power reserve-based sizing and control.

Lewis, Donovin D.↗
DOE OSTI2026

EASY-SHIFT v Alpha

The software is a generic, price- and load-responsive control algorithm integrating heat pumps with thermal energy storage. The algorithm leverages simple models of the system and easily accessible data to schedule operation of heat pumps and thermal energy storage in ways that minimize the cost of operating the heating/cooling system. This tool is specifically designed to be easy to interact with, and something that industry partners are able to adopt. There are two current state of the art approaches. Industry tends to develop very simple algorithms, with predetermined schedules that are not capable of changing operation in response to changes in operating environment. For example, a control designed to avoid high-price electricity from 5-8 PM will not be able to adapt if the high-price period changes to 4-9 PM. Academia commonly develops algorithms called Model predictive control (MPC). MPC requires extensive data and highly trained staff to develop a specific type of simulation model of the building, connect the building to optimization algorithms, and leverage powerful computers. Industry, with limited time/finance budgets for any project, is resistant to adopting MPC due to the associated high complexity and cost.

Grant, Peter [Lawrence Berkeley National Laborator↗
DOE OSTI2020

Renewable Integration in Hybrid ac-dc Systems using Multi-port Autonomous Reconfigurable Solar power plant (MARS)

To increase inertia and improve primary frequency response of future grids, grid-forming inverters connecting PV to grid and energy storage systems (ESSs) are likely to play an important role. Moreover, high-voltage direct current (HVdc) links will also be an enabler to transfer remote PV generation and for improved grid stability. That is, with increased penetration of PV, discrete development of PV and ESS connecting to transmission ac grid and HVdc links is one of the solutions for stable operation of grid. Here, an integrated concept for integration of PV and ESS to transmission ac grid and HVdc links is proposed that is named as multi-port autonomous reconfigurable solar power plant (MARS). The proposed integrated development reduces the cost associated with respect to discrete development of PV-ESS systems connecting to transmission ac grid and HVdc links. The integrated development incorporates advanced control methods to provide inertial and primary frequency response, reactive power support, and transient stability to manage PV and ESS resources. In this paper, high-fidelity switched system model of the integrated system and grids are developed and detailed simulation results are provided to showcase the stable operation of the integrated system and provision of grid support functions.

14 SOLAR ENERGY↗
DOE OSTI2021

Final Scientific Technical Report for "Microgrid RD&D and Testing of PIDC and PWD Systems"

Alstom Grid Inc’s (ALSTOM Grid) Research Design and Development (RD&D) project, “Microgrid RD&D and Testing for PIDC and PWD” was conducted in partnership with Philadelphia Industrial Development Corporation (PIDC) in its role as owner’s representative and manager of a vibrant commercial and industrial community, involving critical loads in one of the nation’s largest unregulated, non-military electric distribution systems. PIDC needed to develop solutions to address the planned considerable growth in Distributed Energy Resources (DER) Combined Heat Plan (CHP), Renewables, Distributed Generation (DG), Demand Response (DR) and Storage. In supporting the corporate objective, PIDC needed a new class of control systems for achieving enhanced energy resilience of their critical infrastructure operation during adverse conditions together with carbon emission reduction and optimization of the overall system operation economics through system energy efficiency during normal and emergency operating conditions. Additionally, PIDC anticipated the need to support a new class of commercial agreements with tenants, such as those for Urban Outfitters, for guaranteed one hundred percent (100%) grid resilience and electric power supply in case of utility outage conditions. The project was designed to address the challenges for the commercial & industrial (C&I) communities. But more importantly, the project included development of scalable and replicable solutions intended to target a multitude of the nation’s electric distribution communities. The project researched and developed a fully comprehensive prototype consisting of microgrid operation and control functions including islanding, synchronization and reconnection, protection, voltage, frequency, and power quality management, dispatch, and system resiliency. The project provided the foundation required to significantly enhance the overall national objectives set by the DOE for energy resilience, emission reduction and system energy efficiency improvement, including protection of critical infrastructure and public resources.

14 SOLAR ENERGY↗