Results for “advanced distribution operations” — Page 34

DOE OSTI2023

Advanced Reactors Integrated Energy System: Thermal Energy Storage Island Design

The main topic of this research is integrated energy systems (IES) designed for pairing industrial thermal energy loads with advanced reactors (ARs). The Idaho National Laboratory (INL) Crosscutting Technology Development IES program and the National Reactor Innovation Center (NRIC) are seeking to develop, design, and construct an AR-IES demonstration platform that couples the thermal output from an AR operating at the INL/NRIC Demonstration of Microreactor Experiments (DOME) test bed in the Experimental Breeder II dome to a variable capacity load emulator (i.e., air-cooled radiator) and sensible thermal energy storage (TES) via a molten salt thermal energy transfer fluid. In the rapidly evolving landscape of energy supply and distribution, flexibility has emerged as a prized attribute, surpassing the traditional notions of stability and baseload generation capability. This shift in priorities is particularly evident in the context of nuclear power plants (NPPs), where adaptability over constant output is becoming more important. As our energy infrastructure and resources embraces the rise of distributed energy generation, the inherent variability in net demand continues to grow. Moreover, the use of nuclear energy as a source of heat for decarbonizing the industrial sector is becoming a very pressing topic. In such environment, advanced NPPs are poised to enter a more competitive energy market, delivering both, flexible electricity and heat. This shift motivates the exploration of TES systems, designed to empower NPPs with nimble responsiveness to market fluctuations, flexible heat delivery capabilities, and redefine their role in the energy field. TES systems offer the unique advantage of storing nuclear energy in its original form as heat, thereby affording unparalleled flexibility in its subsequent utilization.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Isolated Single Metal Atoms Supported on Silica for One Step Non-Oxidative Methane Upgrading to Hydrogen and Value-Added Hydrocarbons

Natural gas in the United States offers substantial economic opportunities due to its abundance but its transportation is challenging because its primary component, methane (CH 4 ), does not liquefy at ambient temperature and typical pressures. As a result, a significant portion of natural gas is either used for heat, flared in remote locations, or remains unutilized, presenting a lost economic opportunity and an environmental harm. Converting natural gas to larger hydrocarbons in an economically competitive manner would enable transportation of products and further boost the economy and reduce environmental footprint. Our research goal is to enable efficient non-oxidative methane conversion (NMC) via catalyst innovation to convert CH 4 in one-step to olefins and aromatics and hydrogen (H 2 ) co-product. The catalysts are made of supported single metal atoms and operated at medium-high temperatures. The single metal atoms achieve methane activation by heterogeneous surface dehydrogenation to generate a hydrocarbon pool and importantly limit coke formation. The integration of novel single atom catalysts in a short contact time microreactor enable unprecedented NMC performance that could lead to economically-feasible, distributed natural gas upgrading by advanced manufacturing and process intensification. Our innovated catalyst and reactor technology promise to tap into previously uneconomic natural gas resources, such as stranded, vented, and flared methane.

03 NATURAL GAS↗

NASA NTRS2000

Langmuir Probe Measurements in an Inductively Coupled Ar/CF4 Plasmas

Technological advancement in the microelectronics industry requires an understanding of the physical and chemical processes occurring in plasmas of fluorocarbon gases, such as carbon tetrafluoride (CF4) which is commonly used as an etchant, and their mixtures to optimize various operating parameters. In this paper we report data on electron number density (ne), electron temperature'(Te), electron energy distribution function (EEDF), mean electron energy, ion number density (ni), and plasma potential (Vp) measured by using Langmuir probe in an inductively coupled 13.56 MHz radio frequency plasmas generated in 50%Ar:50%CF4 mixture in the GEC cell. The probe data were recorded at various radial positions providing radial profiles of these plasma parameters at 10-50 mTorr pressures and 200 W and 300 W of RF power. Present measurements indicate that the electron and ion number densities increase with increase in pressure and power. Whereas the plasma potential and electron temperature decrease with increase in pressure, and they weakly depend on RF power. The radial profiles exhibit that the electron and ion number densities and the plasma potential peak at the center of the plasma with an exponential fall away from it, while the electron temperature has a minimum at the center and it increases steadily towards the electrode edge. The EEDFs have a characteristic drop near the low energy end at all pressures and pressures and their shapes represent non-Maxwellian plasma and exhibit more like Druyvesteyn energy distribution.v

Rao, M. V. V. S.↗

NASA NTRS2015

Retrieval of Aerosol Microphysical Properties from AERONET Photo-Polarimetric Measurements. 2: A New Research Algorithm and Case Demonstration

A new research algorithm is presented here as the second part of a two-part study to retrieve aerosol microphysical properties from the multispectral and multiangular photopolarimetric measurements taken by Aerosol Robotic Network's (AERONET's) new-generation Sun photometer. The algorithm uses an advanced UNified and Linearized Vector Radiative Transfer Model and incorporates a statistical optimization approach.While the new algorithmhas heritage from AERONET operational inversion algorithm in constraining a priori and retrieval smoothness, it has two new features. First, the new algorithmretrieves the effective radius, effective variance, and total volume of aerosols associated with a continuous bimodal particle size distribution (PSD) function, while the AERONET operational algorithm retrieves aerosol volume over 22 size bins. Second, our algorithm retrieves complex refractive indices for both fine and coarsemodes,while the AERONET operational algorithm assumes a size-independent aerosol refractive index. Mode-resolved refractive indices can improve the estimate of the single-scattering albedo (SSA) for each aerosol mode and thus facilitate the validation of satellite products and chemistry transport models. We applied the algorithm to a suite of real cases over Beijing_RADI site and found that our retrievals are overall consistent with AERONET operational inversions but can offer mode-resolved refractive index and SSA with acceptable accuracy for the aerosol composed by spherical particles. Along with the retrieval using both radiance and polarization, we also performed radiance-only retrieval to demonstrate the improvements by adding polarization in the inversion. Contrast analysis indicates that with polarization, retrieval error can be reduced by over 50% in PSD parameters, 10-30% in the refractive index, and 10-40% in SSA, which is consistent with theoretical analysis presented in the companion paper of this two-part study.

aerosol retrieval algorithm↗

NASA NTRS2016

Solar vs. Fission Surface Power for Mars

A multi-discipline team of experts from the National Aeronautics and Space Administration (NASA) developed Mars surface power system point design solutions for two conceptual missions. The primary goal of this study was to compare the relative merits of solar- versus fission-powered versions of each surface mission. First, the team compared three different solar power options against a fission power system concept for a sub-scale, uncrewed demonstration mission. The 4.5 meter (m) diameter pathfinder lander's primary mission would be to demonstrate Mars entry, descent, and landing techniques. Once on the Martian surface, the lander's In Situ Resource Utilization (ISRU) payload would demonstrate liquid oxygen propellant production using atmospheric resources. For the purpose of this exercise, location was assumed to be at the Martian equator. The three solar concepts considered included a system that only operated during daylight hours (at roughly half the daily propellant production rate of a round-the-clock fission design), a battery-augmented system that operated through the night (matching the fission concept's propellant production rate), and a system that operated only during daylight, but at a higher rate (again, matching the fission concept's propellant production rate). Including 30% mass growth allowance, total payload masses for the three solar concepts ranged from 1,116 to 2,396 kg, versus the 2,686 kg fission power scheme. However, solar power masses are expected to approach or exceed the fission payload mass at landing sites further from the equator, making landing site selection a key driver in the final power system decision. The team also noted that detailed reliability analysis should be performed on daytime-only solar power schemes to assess potential issues with frequent ISRU system on/off cycling. Next, the team developed a solar-powered point design solution for a conceptual four-crew, 500-day surface mission consisting of up to four landers per crewed expedition mission. Unlike the demonstration mission, a lengthy power outage due to the global dust storms that are known to occur on Mars would pose a safety hazard to a crewed mission. A similar fission versus solar power trade study performed by NASA in 2007 concluded that fission power was more reliable-with a much lower mass penalty-than solar power for this application. However, recent advances in solar cell and energy storage technologies and changes in operational assumptions prompted NASA to revisit the analysis. For the purpose of this exercise a particular landing site at Jezero Crater, located at 18o north latitude, was assumed. A fission power system consisting of four each 10 kW Kilopower fission reactors was compared to a distributed network of Orion-derived Ultraflex solar arrays and Lithium ion batteries mounted on every lander. The team found that a solar power system mass of about 9,800 kg would provide the 22 kilowatts (kW) keep-alive power needed to survive a dust storm lasting up to 120-days at average optical depth of 5, and 35 kW peak power for normal operations under clear skies. Although this is less than half the mass estimated during the 2007 work (which assumed latitudes up to 30o) it is still more than the 7,000 kg mass of the fission system which provides full power regardless of dust storm conditions.

Rucker, Michelle A.↗

NASA NTRS2022

Advancing Solar Energetic Particle Forecasting

With growing interest from the aviation and satellite industries, and for NASA’s upcoming Artemis lunar missions, the need for improved scientific understanding and accurate forecasting of solar energetic particle events has never been stronger. In this paper we discuss the observational, validation and model transition support required to achieve these goals. Well-calibrated, high-quality energetic electron, proton, and ion measurements are essential. Expansions to the fields of view offered by current X-ray, extreme ultraviolet and coronagraph instruments, to obtain increased coverage of the solar corona and heliosphere, from vantage points off the Sun-Earth line, are desired for model input. New observations of suprathermal particles are needed to characterize seed particle distributions and low latency space-based observations of solar radio emissions are also desired. Together, this observational suite should offer high cadence, low latency, reliable and accurate space weather data streams. Consistent, extensive and quantitative model validation is required to assess scientific advancements and pave the way for models transitioning to real-time forecast operations. Model performance and skill should be compared to observations and to current operational forecasting baselines. Finally, resources are required to support the significant effort of transitioning mature models into forecast operations.

solar energetic particles↗

DOE OSTI2024

Does practice make perfect? Lessons learned from full-scale power system incident response exercise

While threats to the energy sector occur daily, few utilities get the opportunity to fully test out their detection and response mechanisms to advanced threats in the real world. With the high demand for reliability, few grid operators would allow execution of simulated cyber-attacks on their live systems. The DOE-funded Liberty Eclipse project offers a unique opportunity for small and large utilities and coops to practice their combined IT/OT responses to a live red team executing attacks against an isolated power system on an island in New York. Both cyber teams and power operations teams must work together to detect and respond to attacks, even restoring the power system against extreme impacts. Lessons learned from these exercises reveal key takeaways for understanding what a real attack against the electric sector will look like, gaps in execution of the best-laid plans when the pressure of a real event is bearing down, and how organizations can better prepare for advanced attacks by optimizing participation in exercises. This presentation will discuss successes and opportunities for improvement both in how utilities can prepare for and respond to events, as well as how full-scale IT/OT exercises can be coordinated.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗

DOE OSTI2025

A Review of Quantum Computing Technologies in Power System Optimization

As modern power grids increasingly integrate variable renewable generation, distributed energy resources, and energy storage systems, classical optimization techniques are facing unprecedented challenges. This review examines the emerging application of quantum computing to overcome these challenges in power system optimization, including optimal power flow (OPF), unit commitment (UC), economic dispatch (ED), and intelligent switching and topology optimization (IS-TO). Recent research has introduced various quantum methodologies—such as gate-based, annealing-based, variational algorithms, and quantum-inspired algorithms—to address the combinatorial complexity inherent in grid reconfiguration and energy management. The review summaries the quantum algorithms, quantum devices and the power system test cases, highlighting hybrid quantum–classical strategies that leverage the complementary strengths of both paradigms. Some quantum advantages have been observed, including theoretical speedup, accurate simulation results, scalable qubit usage, efficient QUBO mapping. In particular, the review emphasizes the importance of integrating quantum optimization techniques with classical control frameworks, these hybrid approaches demonstrate the potential to improve real-time grid management and operational reliability. A significant portion of the analysis is devoted to the practical limitations of current quantum devices. Present-day quantum hardware, operating in the noisy intermediate-scale quantum (NISQ) era, remains highly sensitive to noise and limited in qubit connectivity, which constrains the scale and accuracy of implemented algorithms. The review delves into specific challenges such as the need for qubit-efficient encoding techniques and error mitigation strategies that are critical for handling real-world grid optimization problems. In addition, the work draws attention to the performance discrepancies between theoretical quantum speedups and experimental validations, underscoring the importance of rigorous benchmark studies using representative power grid test cases. In summary, this review highlights both the promise and limitations of quantum computing for power system optimization. It provides a comprehensive overview of the state-of-the-art technologies, categorizes recent advancements in algorithm design, and discusses practical considerations for implementation, and serves as an informative resource on current research. Future research directions include developing robust hybrid frameworks, advancing qubit-efficient formulations, and scaling up experimental demonstrations to confirm the theoretical advantages of quantum methods in large-scale power system operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Integration of a new Cryogenic Liquefier into the IB-1 Cryogenic Test Facility

The increase over the last years of the testing activities related to quantum systems, SRF cavities for the PIP-II and the LCLS-II projects, as well as superconducting magnets for the HL-LHC project and Fusion research activities, has required the addition of a new Helium cryogenic plant into the existing IB-1 Industrial Cryogenic Test Facility. The new cryogenic plant is composed of a cryogenic liquefier (Cold Box) able to provide up to 340 L/h, a 4 kL Dewar and two Mycom ® compressors providing up to 120 g/s. AL-AT (Air Liquide Advanced Technologies) has taken part of this project by designing and manufacturing the cryogenic liquefier. This new cryogenic plant is connected through a cryogenic distribution system to a 10 kL Dewar, which is part of the existing cryogenic test facility, itself composed of another Cold Box and a Sullair ® compressor. The new cryogenic plant has two main operating modes: one allows to transfer liquid helium at 1.7 bar between the two Dewars, the other allows to transfer supercritical Helium at 2 bar or more between the new Cold Box and the 10 kL Dewar. The entire industrial cryogenic facility is handled by a common Inventory Control System, composed of three control valves, and 9 tanks giving a total buffer volume of more than 1000 m3. This paper presents the technical features of the new Helium cryogenic plant, as well as the main results of the liquefier commissioning phase and details of the helium transfer between the two Dewars, making the connection between the cryogenic plants at the IB-1 Industrial Cryogenic Test Facility.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Integration of a new Cryogenic Liquefier into the IB-1 Cryogenic Test Facility

aThe increase over the last years of the testing activities related to superconducting quantum materials, SRF cavities for the PIP-II and the LCLS-II projects, as well as superconducting magnets for the HL-LHC project and Fusion research activities, has required the addition of a new Helium cryogenic plant into the existing IB-1 Industrial Cryogenic Test Facility. The new cryogenic plant is composed of a cryogenic liquefier (Cold Box) able to provide up to 340 L/h, a 4kL Dewar and two Mycom compressors providing up to 120 g/s. AL-AT (Air Liquide Advanced Technologies) has taken part of this project by designing and manufacturing the cryogenic liquefier. This new cryogenic plant is connected through a cryogenic distribution system to a 10 kL Dewar, which is part of the existing cryogenic test facility, itself composed of another Cold Box and a Sullair compressor. The new cryogenic plant has two main operating modes: one allows to transfer liquid helium at 1.7 bar between the two Dewars, the other allows to transfer supercritical Helium at 2 bar or more between the new Cold Box and the 10 kL Dewar. The entire industrial cryogenic facility is handled by a common Inventory Control System, composed of three regulatory valves, and 9 tanks giving a total buffer volume of more than 1000 m3. This paper presents the technical features of the new Helium cryogenic plant, as well as the main results of the liquefier commissioning phase and details of the helium transfer between the two dewars, making the connection between the cryogenic plants at the IB-1 Industrial Cryogenic Test Facility.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2017

Recent Developments in X-Ray Diagnostics for Cryogenic and Optically Dense Coaxial Rocket Sprays

The mixing and atomization of propellants is often characterized by optically dense flow fields and complex breakup dynamics. In the development of propulsion systems, the complexity of relevant physics and the range of spatio-temporal scales often makes computational simulation impractical for full scale injector elements; consequently, continued research into improved systems for experimental flow diagnostics is ongoing. One area of non-invasive flow diagnostics which has seen widespread growth is using synchrotron based x-ray diagostics. Over the past 3 years, a series of water and cryogenic based experiments were performed at the Advanced Photon Source, Argonne National Lab, on a NASA in-house designed swirl co-axial rocket injector, designed for operation using liquid oxygen and liquid methane in support of Project Morpheus. A range of techniques, such as x-ray fluorescence and time-averaged radiography were performed providing qualitative and quantitative mass and phase distributions, and were complemented by investigations using time-resolved radiography and white beam imaging, which provided information on breakup and mixing dynamics. Results of these investigations are presented, and conclusions regarding the viability of x-ray based diagnostics are discussed.

Radke, Christopher D.↗

NASA NTRSDate not supplied

LA-8 Computational Analysis and Validation Studies Using FlightStream

With the emerging market of Urban Air Mobility and the associated unique new flight vehicles with the capability of vertical takeoff and landing, design tools need to be calibrated to assist in the development of these new flight vehicle concepts. Distributed electric propulsion (DEP) covers these vehicles with high-energy flow from the array of motors, which leads to extensive propulsion/airframe interaction effects. With limited experimental data of vehicles using DEP and vehicle operation across a large range of angles of attack, including post-stall conditions, there is a lack of validated design tools to advance new vehicle concepts that have blown wings and operate in multiple flight modes. Although some CFD tools can handle the integration of multiple propulsors and unique geometries, the computational time with a full vehicle is extraordinary. FlightStream, a surface vorticity flow solver that can run in a fraction of the time of other CFD methods, has been evaluated using the Langley Aerodrome No. 8 (LA-8) vehicle as a test case. The LA-8 vehicle is a DEP tandem tilt-wing research vehicle that was designed, built, and tested at NASA Langley Research Center. The LA-8 design features both high-performance and high-technical risks aspects. The vehicle has gone through extensive design of experiments wind tunnel testing in the NASA Langley 12-Foot Low-Speed Wind Tunnel in order to capture all modes of operation. In addition, the LA-8 vehicle has undergone wind tunnel testing with and without propellers, which contributes to the validation of FlightStream for aerodynamic performance in blown and unblown wing cases. This study shows that FlightStream can produce trends and magnitudes of the lift and drag coefficients similar to the data collected from the wind tunnel testing of LA-8. The test cases were both blown and unblown wing cases and with and without high lift control surface deflections.

Steven Curtis Geuther↗

NASA NTRSDate not supplied

Simplified Applied Loads of a Transonic Truss-Braced Wing Derived from Computational Fluid Dynamics

The transonic truss-braced wing (TTBW) concept is under consideration by the NASA Advanced Air Transport Technology (AATT) project due to its potential to reduce fuel consumption of transport aircraft. To properly evaluate the TTBW concept, detailed structural modeling and subsequent test planning is underway, which requires a simplified set of discrete applied loads that simulate the distributed aerodynamic pressures. Given the unique architecture of the TTBW and its intended operation in the transonic regime, computational fluid dynamics (CFD) is the ideal approach to employ to ensure the aerodynamics of this configuration are sufficiently captured. To convert aerodynamic results into input for structural models, application of a data transfer tool, Discrete Data Transfer Between Dissimilar Meshes (DDTBDM), is presented to resolve aerodynamic pressures from CFD into single load vectors at hardpoints along both the wing and the strut. Evaluation of mapping the aerodynamic forces to hardpoints at rib and spar intersections in a structural model is performed, and the results are also compared with a linear static aeroelastic analysis. The structural responses indicate that distributing forces along only the wing and strut forward spars is insufficient for simulating the distributed aerodynamic loads. Adding moments along the forward spars improved the global response of the wing, but the point moments created unrealistic local rotations within the structure. When distributing loads along both the forward and aft spars of the wing and strut, the global response was less sensitive to the inclusion of point moments, which indicated the arrangement of point forces alone was sufficient input for structural design work and testing and provided a more continuous loading profile.

Finite Element↗

NASA NTRSDate not supplied

Simplified Applied Loads of a Transonic Truss-Braced Wing Derived from Computational Fluid Dynamic

The transonic truss-braced wing (TTBW) concept is under consideration by the NASA Advanced Air Transport Technology (AATT) project due to its potential to reduce fuel consumption of transport aircraft. To properly evaluate the TTBW concept, detailed structural modeling and subsequent test planning is underway, which requires a simplified set of discrete applied loads that simulate the distributed aerodynamic pressures. Given the unique architecture of the TTBW and its intended operation in the transonic regime, computational fluid dynamics (CFD) is the ideal approach to employ to ensure the aerodynamics of this configuration are sufficiently captured. To convert aerodynamic results into input for structural models, application of a data transfer tool, Discrete Data Transfer Between Dissimilar Meshes (DDTBDM), is presented to resolve aerodynamic pressures from CFD into single load vectors at hardpoints along both the wing and the strut. Evaluation of mapping the aerodynamic forces to hardpoints at rib and spar intersections in a structural model is performed, and the results are also compared with a linear static aeroelastic analysis. The structural responses indicate that distributing forces along only the wing and strut forward spars is insufficient for simulating the distributed aerodynamic loads. Adding moments along the forward spars improved the global response of the wing, but the point moments created unrealistic local rotations within the structure. When distributing loads along both the forward and aft spars of the wing and strut, the global response was less sensitive to the inclusion of point moments, which indicated the arrangement of point forces alone was sufficient input for structural design work and testing and provided a more continuous loading profile.

Finite Element↗

DOE OSTI2024

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

SCUC-DER Integration Report: Integrating Distributed Energy Resources (DER) Using Advanced Unit Commitment Models and DER Aggregation Methodologies

Distributed energy resources (DERs) are continuing to grow due to regulatory, policy, and market shifts, and it needs to be ensured that small DERs are given a level playing field with traditional resources. Legacy market processes such as unit-commitment problems were designed for a power grid consisting largely of centralized power plants. In contrast, DERs consist of many small devices with distinct operating characteristics that may or may not be connected at the transmission interconnection points, limiting their visibility to the independent system operators (ISOs) who operate wholesale electricity markets. This report details the development and initial results from a simulation platform that integrates state-of-the-art security-constrained unit commitment software, detailed feeder models, and a DER aggregator model to quantify potential DER integration issues. Quantitative results to date illustrate potential infeasible scheduling solutions from SCUC when the DERA includes aggregations of energy-limited energy storage resources. Likewise, if aggregations are not penalized for dispatch deviations, they may have incentives to deviate from the SCUC-determined resource schedules. Assumptions about the amount of aggregated demand response resources (DRRs) and the ability of DERAs to follow profit incentives have an important impact – DRRs have significant flexibility and can typically feasibly meet their SCUC schedule, but on the other hand, their profit incentives can cause unscheduled increases in load before and after DRR dispatch. Computation time results on the SCUC solver and simulation platform only show a modest increase in SCUC solution time as the number of DERAs is increased, but results to date only reflect the RTS-GMLC test system; results may show more significant solver slowdown in larger transmission systems. The largest contribution to simulation time is attributed to the DERA offer generation method, which is suggested for future improvements.

24 POWER TRANSMISSION AND DISTRIBUTION↗