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At least 721 records · Page 40

Islanding Detection in Rural Distribution Systems

This paper summarizes the literature on detection of islanding resulting from distributed generating capabilities in a power distribution system, with emphasis on the rural distribution systems. It is important to understand the legacy technology and equipment in the rural distribution electrical environment due to the growth of power electronics and the potential for adding the new generations of intelligent sensors. The survey identified four areas needing further research: 1. Robustness in the presence of distribution grid disturbances; 2. the future role of artificial intelligence in the islanding application; 3. more realistic standard tests for the emerging electrical environment; 4. smarter sensors. In addition, this paper presents a synchro-phasor-based islanding detection approach based on a wireless sensor network developed by the University of Texas at Austin. Initial test results in a control hardware-in-the-loop (CHIL) simulation environment suggest the effectiveness of the developed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Toward exascale whole-device modeling of fusion devices: Porting the GENE gyrokinetic microturbulence code to GPU

GENE solves the five-dimensional gyrokinetic equations to simulate the development and evolution of plasma microturbulence in magnetic fusion devices. The plasma model used is close to first principles and computationally very expensive to solve in the relevant physical regimes. In order to use the emerging computational capabilities to gain new physics insights, several new numerical and computational developments are required. Here, we focus on the fact that it is crucial to efficiently utilize GPUs (graphics processing units) that provide the vast majority of the computational power on such systems. In this paper, we describe the various porting approaches considered and given the constraints of the GENE code and its development model, justify the decisions made, and describe the path taken in porting GENE to GPUs. We introduce a novel library called gtensor that was developed along the way to support the process. Performance results are presented for the ported code, which in a single node of the Summit supercomputer achieves a speed-up of almost 15× compared to running on central processing unit (CPU) only. Typical GPU kernels are memory-bound, achieving about 90% of peak. Our analysis shows that there is still room for improvement if we can refactor/fuse kernels to achieve higher arithmetic intensity. We also performed a weak parallel scalability study, which shows that the code runs well on a massively parallel system, but communication costs start becoming a significant bottleneck.

Germaschewski, K. (ORCID:0000000284956354)↗

Deep Reinforcement Learning Based Control of Wind Turbines for Fast Frequency Response

In order to fulfill vital auxiliary grid services, such as load regulation, spin and non-spin reserve provision, and frequency support during emergencies, there is often a requirement for certain wind farms to operate in de-loaded modes. Leveraging the swift response capabilities of wind farms, this study demonstrates that reserving power in de-loaded modes can significantly enhance power grid stability and reliability during system contingencies. Controlling wind farms optimally for frequency support is intricate due to the nonlinearity of models and controllers and the complexity of wind farm interactions with power systems. Here, to address this challenge, this paper introduces a novel approach that integrates wind turbines into reinforcement learning-based solutions for frequency response. This innovative methodology utilizes the state-of-the-art reinforcement learning algorithm known as the surrogate-gradient-based evolutionary strategy. The proposed learning-based algorithm provides continuous control of wind farm output to rapidly stabilize system frequency and prevent unnecessary trips of under-frequency load shedding relays. To facilitate efficient training, parallel computing techniques are employed. The proposed methodology is evaluated on a modified IEEE-39 bus system, and simulation results reveal its efficacy in reliably supporting power system frequency and preventing the need for unnecessary load shedding.

Gao, Wei [Argonne National Laboratory (ANL), Argon↗

Extraction of Vibration Data with Imaging

To date, the primary sensing technology used to measure the vibration response has been accelerometers and strain gages mounted directly to the structure and using either wired or, more recently, wireless telemetry. Cost issues with these sensors and the associated data acquisition systems typically limit the numbers that are deployed on in situ structures. Although there are a few structures with larger sensing counts that in some cases exceed over 1000 sensors, more typical numbers range from ten to one hundred sensors resulting in low spatial resolution when they are applied to physically large systems. When one considers that nuclear power plant structures usually have complex geometries, material properties, connectivity and boundary conditions, it is clear these current approaches to vibration measurements can only provide limited information about a system’s dynamics response characteristics. As an alternative, many non-contact measurement technologies have emerged, including point wise measurement methods such as Global Positioning System (GPS), microwave interferometry, and laser Doppler vibrometry (LDV), as well as simultaneous full-field measurement methods such as electronic speckle pattern interferometry, holography interferometry, and muon tomography, some of which can provide high spatial resolution measurements. Among these methods, digital video imaging techniques have emerged as a feasible solution for full-field vibration measurements that provide significantly more detailed dynamic response information because every pixel becomes a measurement point. Furthermore, recent advances in image processing and computer vision algorithms have been successfully used to process video data for experimental and operational modal analysis. Such full-field measurements have the potential to significantly improve many current structural assessment procedures including system identification (modal parameter estimation), structural health monitoring, load reconstruction, model validation, and model updating. Furthermore, more recent full-field imaging techniques can be accomplished with relatively low-cost, commercially-available off-the-shelf cameras. However, these measurement procedures have other limitations that must be considered such as the ability to only measure visibly accessible points on a structure and a more limited dynamic range and bandwidth than can be achieved with accelerometers or strain gages.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Review of Unmanned Aerial Vehicle Technology in Power Line Inspection

The electric power industry is one of the heaviest adopters of Unmanned Aerial Vehicles (UAV) technology, utilizing their versatility to enhance power line maintenance programs. For reliable power grids, routine maintenance operations and rapid repair operations are required across substantial geographical distances. Both maintenance and repair decisions are driven by assessment operations, such as inspections of mechanical structures with visible-band sensors, inspections for the presence of high voltage coronas and hot spots with multispectral sensors, and surveying of equipment and adjacent features (particularly vegetation) with photogrammetric and Light Detection and Ranging (LiDAR) sensors. Assessment was historically accomplished with manned helicopter flights or foot patrols. Recently, this critical economic segment harnessed advances in Unmanned Aerial Systems (UAS)technology to accomplish assessment tasks with faster results, lower cost, and higher levels of safety than historical methods. Adoption of UAVs in high-voltage electric power transmission activities is well underway. Adoption of UAVs for low voltage distribution activities is still emerging, with the important exception of post-storm damage assessment following major hurricanes (Harvey and Maria in 2017 and Michael in 2018). This report reviews the broad UAS adoption in high-voltage electric power transmission operations and early attempts at adoption in distribution operations. The ability to fly beyond visual line of sight (BVLOS) may increase the advantages of UAV inspection over former options, and in the United States, regulators have approved two pilot projects to demonstrate BVLOS methods and their benefits in operating and maintaining the power grid.

UAV↗

Scalable Graph Analytics and HPC Operational Enhancement: Parallel Computing and ML/DL Innovations

Parallel computing plays a pivotal role in the efficient processing of large-scale graphs. Complex network analysis stands as a capti- vating research frontier, holding promise across diverse scientific domains such as sociology, biology, online media, and recommenda- tion systems. In this era, Machine Learning (ML) and Deep Learning (DL) have emerged as indispensable tools, underpinning remarkable technological achievements. Within this dynamic landscape, my research revolves around advancing parallel algorithms tailored for large-scale graph operations. To achieve this, I harness the power of cutting-edge technologies including OpenMP, MPI, HIP, and CUDA, on the High-Performance Computing (HPC) platforms to unlock optimal performance. I also apply ML/DL techniques to HPC operational data, to streamline the monitoring and maintenance of supercomputers, alleviating the complexities associated with their upkeep and enhancing user support. My research echoes the syn- ergy between parallel computing, large-scale graph analysis, and ML/DL, improving computational efficiency and user experience.

Sattar, Naw Safrin↗

Configuration and Data Management of the NASA Power and Propulsion Element MBSE Model(s)

Systems engineers worldwide have been working to implement Model-Based Systems Engineering (MBSE) environments, tools, and methodologies. A significant, expected benefit from MBSE is a reduction in the time commitment for all aspects of systems engineering. Although advances in MBSE have occurred, a gap has emerged between the traditional configuration management (CM) processes for documents and those needed in an MBSE environment.

MBSE↗

Analytical Methods and Testbeds for Characterizing Adsorbents and Catalysts for Atmosphere Revitalization of Crewed Spacecraft

Spacecraft environmental control and life support systems (ECLSS) include a number of air revitalization (AR) technologies to provide breathable air and a comfortable living environment to the crew. Crew health and comfort is ensured by controlling human produced CO2 (1 kg person-1 day-1) and water vapor (~2 kg person-1 day-1), and by removing trace contaminants (TCs) from cabin air. These life support functions on-board the International Space Station (ISS) are carried out by the Carbon Dioxide Removal Assembly (CDRA), the Water Processor Assembly (WPA), and the trace contaminant control system (TCCS). During the development of the TCCS, new analytical and theoretical methods were developed in the 1970s for characterizing adsorption and desorption characteristics of activated carbons for the purpose of designing suitable AR technologies required for controlling airborne trace contaminants within spacecraft cabins during long exploration missions. The TCCS removes harmful volatile organic compounds and other trace contaminants from the circulating air. It consists of a granular activated carbon (GAC) bed for the removal of high molecular weight contaminants and ammonia followed by a heated catalytic bed for low molecular weight hydrocarbons. The high temperature catalytic oxidizer (HTCO) of the TCCS, which operates at 400°C and requires 120W average power, removes low molecular weight compounds such as carbon monoxide (CO), formaldehyde (CH2O), and methane (CH4), that pass through the GAC bed. The Air Revitalization Laboratory at the Kennedy Space Center (KSC) was established to develop new analytical methods for evaluating emerging ECLSS technologies for use in future AR architectures. General properties of adsorbents and catalysts are required for trace contaminant control system design calculations and vendor-supplied data are seldom available at relevant process conditions of interest to spacecraft cabin applications. To address this shortcoming, appropriate testbeds were developed to measure the desired properties of AR technologies being considered for use in ECLS architectures. Generally, the testbeds developed at KSC challenge the test media (activated carbon, impregnated activated carbon, catalysts, zeolites, solid amines, or pleated filters) with simulated spacecraft gas streams containing representative mixtures of trace contaminants (volatile organic compounds, ammonia, CO, CO2, or siloxanes) at the flow rates, temperatures, and relative humidity that will be encountered within manned spacecraft. Work performed at KSC funded by NASA’s Advanced Exploration (AES) Program has included: Identifying candidate sorbents to replace commercially obsolete impregnated carbons for NH3 control within the TCCS, characterizing their adsorptive capacities using simulated spacecraft gas streams, and ranking their appropriateness in various AR applications; evaluating novel low temperature catalysts for controlling CO and formaldehyde by traditional and photocatalytic methods for trace contaminant control; development of analytical methods to assess regenerable solid amine performance for CO2 control via pressure swing adsorption. The Air Revitalization lab was also funded to study trace contaminant control by other NASA programs. These include: screening of candidate sorbents for the design of new Charcoal HEPA Integrated Particle Scrubber (CHIPS) filters for removing siloxanes from cabin air; characterizing the performance of an impregnated activated carbon at low humidity for use in ORION ECLS; screening of sorbents for protecting the Sabatier 2.0 catalyst from DMSO2, siloxanes, NH3, and solid amine byproducts.

Monje, Oscar↗

High Altitude Long Endurance Air Vehicle Analysis of Alternatives and Technology Requirements Development

The objective of this study was to develop a variety of High Altitude Long Endurance (HALE) Unmanned Aerial Vehicle (UAV) conceptual designs for two operationally useful missions (hurricane science and communications relay) and compare their performance and cost characteristics. Sixteen potential HALE UAV configurations were initially developed, including heavier-than-air (HTA) and lighter-than-air (LTA) concepts with both consumable fuel and solar regenerative (SR) propulsion systems. Through an Analysis of Alternatives (AoA) down select process, the two leading consumable fuel configurations (one each from the HTA and LTA alternatives) and an HTA SR configuration were selected for further analysis. Cost effectiveness analysis of the consumable fuel configurations revealed that simply maximizing vehicle endurance can lead to a sub-optimum system solution. An LTA concept with a hybrid propulsion system (solar arrays and a hydrogen-air proton exchange membrane fuel cell) was found to have the best mission performance; however, an HTA diesel-fueled wing-body-tail configuration emerged as the preferred consumable fuel concept because of the large size and technical risk of the LTA concept. The baseline missions could not be performed by even the best HTA SR concept. Mission and SR technology trade studies were conducted to enhance understanding of the potential capabilities of such a vehicle. With near-term technology SR-powered HTA vehicles are limited to operation in favorable solar conditions, such as the long days and short nights of summer at higher latitudes. Energy storage system specific energy and solar cell efficiency were found to be the key technology areas for enhancing HTA SR performance.

Nickol, Craig L.↗

BIL GRID-READY WIND: Reliable and Economical Grid Services Design, Implementation, and Demonstration at the Great Pathfinder Wind Power Plant

The GRID-READY WIND project aimed to demonstrate the ability of utility-scale wind power plants (WPPs) to deliver traditional and emerging grid services (GSs) in both grid-following (GFL) and grid-forming (GFM) modes through a centralized control framework, supplemented by local control adjustments at the wind turbine generator as needed. Throughout the project, the team offered recommendations on how the grid services demonstrated with WPPs could be applied to other inverter-based resources (IBRs), such as photovoltaic (PV) systems and battery energy storage systems (BESS), while considering the unique dynamics of these resources arising from their energy generation characteristics. The project sought to enhance the confidence of system operators (SOs) and planners in utilizing WPPs, alongside other IBRs such as PV plants and BESS, to provide essential grid services over extended periods under diverse operating conditions, thereby supporting their integration into the bulk power system.

17 WIND ENERGY↗

Can Food–Energy–Water Nexus Research Keep Pace with Agricultural Innovation?

The interconnection among food–energy–water (FEW) systems in meeting societal demands is broadly acknowledged. Similarly, competitive or synergistic allocations of water and energy resources for agricultural production, manufacturing, and human consumption are understood, and their economic impacts can be predicted. Far less appreciated and understood are the outcomes of the FEW nexus in response to operation changes in agricultural practices and the associated technological innovations for future generations. Also, the inter-scale and feedback effects of emerging technology-driven resource reallocation and decision-making on FEW systems are largely unknown. For example, how do the agroeconomic feedbacks of intelligent technologies influence the FEW nexus of agricultural production under environmental and demographic changes? How does the necessary water allocation for powering non-powered dams and pumped-storage hydropower generation influence agricultural production and municipal water supply maintenance? How do solar and wind energy farms influence land use for agriculture and the rural economy? In turn, how can the generated solar and wind energy help reduce the cost of groundwater extraction or water desalination?

42 ENGINEERING↗

SYMBIOSYS: A Methodology for Performance Analysis of Composable HPC Data Services

Microservices are a powerful new way of building, customizing, and deploying distributed services owing to their flexibility and maintainability. Several large-scale distributed platforms have emerged to serve the growing needs of data-centric workloads and services in commercial computing. Concurrently, high-performance computing (HPC) systems and software are rapidly evolving to meet the demands of diversified applications and heterogeneity. The interplay of hardware factors, software configuration parameters, and the flexibility offered with a microservice architecture makes it nontrivial to estimate the optimal service instantiation for a given application workload. Further, this problem is exacerbated when considering that these services operate in a dynamic and heterogeneous HPC environment. An optimally integrated service can be vastly more performant than a haphazardly integrated one. Existing performance tools for HPC either fail to understand the request-response model of communication inherent to microservices or they operate within a narrow scope, limiting the insight that can be gleaned from employing them in isolation. We propose a methodology for integrated performance analysis of HPC microservices frameworks and applications called SYMBIOSYS. We describe its design and implementation within the context of the Mochi framework. This integration is achieved by combining distributed callpath profiling and tracing with a performance data exchange strategy that collects fine-grained, low-level metrics from the RPC communication library and network layers. The result is a portable, low-overhead performance analysis setup that provides a holistic profile of the dependencies among microservices and how they interact with the Mochi RPC software stack. Using HEPnOS, a production-quality Mochi data service, we demonstrate the low-overhead operation of SYMBIOSYS at scale and use it to identify the root causes of poorly performing service configurations.

microservices↗

Valuing Resilience for Microgrids: Challenges, Innovative Approaches, and State Needs

The United States depends on the delivery of reliable, affordable, clean, and safe electricity. Electric utilities invest billions of dollars each year in generation, transmission, and distribution assets to meet this need. However, experiences with recent natural disasters of increasing frequency and duration demonstrate the shortcomings of this approach in the face of modern threats. Further, as customers rely on electricity for a broader range of important needs, such as transportation, as well as critical life-saving services and mission critical facilities such as water treatment, medical care, shelters, telecommunications, and more, the need to minimize the likelihood and impacts of outages grows. Against this backdrop, resilience has emerged as a key consideration to guide electricity spending, whether from utilities, customers, or taxpayers. Although reliability has been defined and measured for decades with broadly accepted metrics that measure how many customers lose power and at what frequency and duration, resilience considers the electricity system’s response to a disruption and its subsequent impacts on customers. Developing tools and methods to accurately assess the costs and benefits of resilience investments is a critical step toward the goal of mitigating the impacts of outages on customers and society. Today, electric system resilience is largely treated as an externality due to challenges estimating the costs of long-duration outages, impacts of outages on society, and increasing reliance on electricity for a growing set of interdependent services. These interdependencies include the water, wastewater, telecommunications, natural gas, and health sectors. Without knowing how much a given resilience investment will benefit customers or society more broadly, investors, policymakers, and regulators are less likely to make or approve such investments, and less able to prioritize those investments. State Energy Offices and public utility commissions (PUCs) lead the development of state-level energy policy and utility regulation, respectively, and each has interests in encouraging appropriate public and private investments in resilience. To this end, the National Association of State Energy Officials (NASEO) and National Association of Regulatory Utility Commissioners (NARUC), with the support of the U.S. Department of Energy (DOE) Office of Electricity (OE), formed a joint Microgrids State Working Group to explore the costs and benefits of microgrids, barriers to broader deployment of microgrids to meet resilience and other objectives, and policy and regulatory strategies to optimize investments in resilience, including but not limited to microgrids. Although no universally accepted valuation tool for resilience exists, National Laboratories, utilities, researchers, and state and federal agencies have collaborated to develop, apply, and improve a number of approaches to quantify resilience, several of which are still in progress at the time this report is published. This report seeks to share these important advances by discussing current definitions of resilience (Section 1), how microgrids are defined and used to meet resilience objectives (Section 2), new approaches to valuing resilience (Section 3), steps State Energy Offices and PUCs have taken to further resilience valuation efforts (Section 4), and finally, considerations and suggested next steps for State Energy Offices and PUCs (Section 5). Relevant examples of specific microgrid projects and resilience valuation efforts are included throughout the report. While this report is written specifically for NASEO and NARUC members, it may be useful for utilities, local governments, and individual customers interested in improving the way public and private dollars are spent to achieve resilience outcomes.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications: Fourth Edition

As the world increasingly seeks low-carbon energy solutions, solar power emerges as the most abundant resource on our planet. However, the challenge of effectively harnessing this energy is crucial in the coming years. Solar energy applications such as photovoltaics, solar heating and cooling, and concentrating solar power use different technologies to capitalize on sunlight. Each system has unique capabilities and requirements, underscoring the need for reliable information about solar resources across diverse installations, from residential rooftops to large-scale power plants. This is especially important for substantial projects, often exceeding $1 billion in construction costs. Before embarking on such ventures, it is imperative to obtain accurate data concerning solar resource quality and reliability at specific sites. Developers require detailed historical information, including seasonal, daily, hourly, and, ideally, subhourly variability to effectively predict a power plant's annual performance. Without these vital data, financial analyses fall short. Moreover, with the growing adoption of distributed photovoltaics, integrating these generation sources becomes critical to maintaining grid reliability and stability. By accurately forecasting generation patterns, utilities and system operators can facilitate greater integration of solar energy, thus ensuring the operational stability of the grid. The complexity and importance of these issues have prompted the foremost experts in the field to collaborate under the auspices of the International Energy Agency's (IEA's) Photovoltaic Power Systems Programme (PVPS) Task 16 to publish this handbook, which summarizes state-of-the-art information about all these topics. The efforts focus on providing reliable data and insights that can help shape our investments in solar energy and drive a sustainable future.

14 SOLAR ENERGY↗

Defensive Cybersecurity Architecture Design Using Force-on-Force Cyber-Physical Modeling

Currently, nuclear power plant physical security systems are highly dependent on air-gaps as a protective measure against cyber-threats. Cyber-physical threats become more likely as advanced cyber-threat capabilities to jump air-gaps transition into common use. Defending against the emerging threat of cyber-enabled physical intrusions is poorly understood. The consequence of these cyber-physical attacks has no quantitative analysis method to inform risk-informed, performance-based cybersecurity approaches. By modifying the physical security simulation tool Dante, cyber-physical threat consequence was able to be analyzed on a notional facility. The results of this analysis are used to design a Defensive Cybersecurity Architecture (DCSA) for the physical security system to produce example resilience measures for this notional facility. A DCSA defines security levels to provide a graded approach for defending plant functions, and security zones for trusted communication between systems. This approach can be applied to real world systems to produce physical protection systems and response measures that are resilient to cyber-physical threats.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Flexible wings for transportation.

The possible uses of flexible wings for transportation of passengers and cargo from point to point on earth are discussed along with emergency applications of flexible wings in connection with conventional aircraft. Topics considered include gliding and soaring as a sport, towing of flexible-wing gliders for cargo delivery, powered flight with small aircraft having folding flexible wings, aerial dropping of personnel and cargo on flexible wings instead of parachutes, landing and recovery of rocket payloads by means of flexible wings, and use of flexible wings with ejection seats and as an emergency landing system for conventional aircraft.

Rogallo, F. M.↗

Application of Solar-Electric Propulsion to Robotic and Human Missions in Near-Earth Space

Solar-electric propulsion (SEP) is becoming of interest for application to a wide range of missions. The benefits of SEP are strongly influenced by system element performance, especially that for the power system. Solar array performance is increasing rapidly and promises to continue to do so for another 10 to 20 years (Fig. 1). At the same time, cost per watt is decreasing. Radiation hardness is increasing. New concepts for how to design a SEP are emerging. These improvements lead to changes in the best ways to apply SEP technology to missions, and broadening of the practical uses of SEP technology compared to competing technologies. This paper addresses the evolving characteristics of SEP technology from the point of view of mission design, and how mission profile characteristics can be designed to best take advantage of evolving SEP characteristics. Mission concepts include robotic lunar landers and orbiters; scientific planetary spacecraft; delivery of spacecraft to geosynchronous orbit from inclined and low-inclination launch orbits; and lunar cargo delivery from Earth orbit to lunar orbit. Expendable and re-usable SEP profiles are considered. Flight control considerations are abstracted from recent papers by the author to describe how these influence SEP design and operations.

Woodcock, Gordon↗

NLR HPC Facility Power Usage Effectiveness (PUE) Data

Timeseries of Energy Systems Integration Facility (ESIF) Data Center Power Usage Effectiveness (PUE) Data provided in Parquet and compressed CSV formats Power Metrics Timeseries Fields: ts: Timestamp cooling_kw: Cooling (kilowatts) - Captures the power used by fans and pipe trace heaters associated with outdoor cooling equipment. The dedicated tower filter pump power is also captured as cooling load. energy_reuse: Energy Reuse Effectiveness hvac_kw: Heating, ventilation, and air conditioning (kilowatts) - Captures fan walls, fan coils that support the data center electrical rooms, and the make-up air unit. it_power_kw: IT equipment (kilowatts) - Captures power used by the IT equipment on the data center floor. plug_and_light_kw: Lights and utility plugs (kilowatts) - Captures power associated with the data center and dedicated mechanical room. The crank-case heater for the emergency standby generator is also captured as light and plug load. pue: Power Usage Effectiveness pump_kw: Pumps (kilowatts) - Captures power from pumps that move water in the data center Energy Recover Water loop and the Tower Water loops, and also captures power used by the boost pumps that circulate water through the fan walls. Note: The tower filter pump runs constantly to filter water from the data center cooling tower system, so 2.67 kilowatts are attributed to this pump and that is not reflected in this data field. day: Day of month Outside Weather Station Timeseries Fields: ts: Timestamp outside_air_humidity: Outside air humidity - Relative humidity percent outside_air_temp: Outside air temperature - Degrees Fahrenheit day: Day of month More detail: High-Performance Computing Data Center Power Usage Effectiveness

97 MATHEMATICS AND COMPUTING↗