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At least 307 records · Page 17

Powering Up Secure and Reliable Operations at the Port of Honolulu's Kapalama Container Terminal

The National Laboratory of the Rockies (NLR) is providing resilience planning support to the Pasha Group, the operator of Kapalama Container Terminal (KCT) at the Port of Honolulu, by exploring how distributed clean energy resources could help the terminal sustain a 36-hour outage and continue emergency operations. The Department of Energy's Energy Transitions Initiative (ETI) aims to advance self-reliant island and remote communities by promoting resilient, affordable, and sustainable clean energy resources.

25 ENERGY STORAGE↗

A New Operational Snow Retrieval Algorithm Applied to Historical AMSR-E Brightness Temperatures

Snow is a key element of the water and energy cycles and the knowledge of spatio-temporal distribution of snow depth and snow water equivalent (SWE) is fundamental for hydrological and climatological applications. SWE and snow depth estimates can be obtained from spaceborne microwave brightness temperatures at global scale and high temporal resolution (daily). In this regard, the data recorded by the Advanced Microwave Scanning Radiometer-Earth Orbiting System (EOS) (AMSR-E) onboard the National Aeronautics and Space Administration's (NASA) AQUA spacecraft have been used to generate operational estimates of SWE and snow depth, complementing estimates generated with other microwave sensors flying on other platforms. In this study, we report the results concerning the development and assessment of a new operational algorithm applied to historical AMSR-E data. The new algorithm here proposed makes use of climatological data, electromagnetic modeling and artificial neural networks for estimating snow depth as well as a spatio-temporal dynamic density scheme to convert snow depth to SWE. The outputs of the new algorithm are compared with those of the current AMSR-E operational algorithm as well as in-situ measurements and other operational snow products, specifically the Canadian Meteorological Center (CMC) and GlobSnow datasets. Our results show that the AMSR-E algorithm here proposed generally performs better than the operational one and addresses some major issues identified in the spatial distribution of snow depth fields associated with the evolution of effective grain size.

passive microwave↗

Extending the Operating Envelope for an Extremely Low NOx Axial Stage Combustion System

The overall goal of this program is to develop a low NOx combustion system which enables a gas turbine combined cycle efficiency of > 65%. The proposed combustion system is a combination of three advanced technologies under development by the Recipient: advanced transition design, the Distributed Combustion System (DCS), and advanced head end. Of note is that the DCS and advanced transition were initially developed with DOE funding under previous Cooperative Agreements. The continued development of these designs has resulted in a proof of concept design which was successfully tested in the Recipient’s state-of-the-art high-pressure rig. The initial rig testing indicated a substantial benefit with respect to high firing temperature operation as well as low NOx operation for the advanced transition and the DCS. Even lower NOx and higher firing temperatures are possible with the addition of the advanced head end to the design. Potential hurdles to the combustion design have been identified, such as high pressure drop and acoustics. The goal of this program is to develop variations of this design which address these hurdles and create an optimized design for implementation into the Recipient’s new high efficiency gas turbine engine.

03 NATURAL GAS↗

Strengthening U.S. National Security Through Advanced Energy Innovation

NREL's work in strategic energy security is focused on keeping the United States secure and its citizens safe by applying expertise in advanced energy systems and technologies to prevent energy system disruptions from any source, natural or human. NREL pursues national security objectives by providing partners an accurate understanding of national and international security implications of global energy trends; novel installation, facility, and operational energy solutions; access to NREL R&D capabilities to incorporate advanced energy technologies and biomaterials into mission requirements; and the ability to test future technologies using large-scale grid modeling.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Advanced Distributed Wind Turbine Controls Series: Part 3-Wind Energy in Grid-Connected Deployments – Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL)

In recent years the technical ability and requirement for distributed wind turbines to provide grid support services beyond maximum energy production has increased. Ancillary services leveraged through advance controls of a wind turbine support grid reliability and resilience. One ancillary service that is significant to a grid-connected wind turbine deployment is fault ride through (FRT) in response to the voltage and frequency events in the power system. As part of the Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) this paper demonstrates, through desktop simulations, the wind turbine's FRT capabilities to support stable grid operation. We establish that the wind turbine models exceed FRT performance requirements stipulated in IEEE 1547-2018, regarding interconnection and interoperability of distributed energy resources. Utilizing a standalone CART2 (600 kW) wind turbine connected to the NREL's Flatirons Campus grid, we study voltage and frequency FRT utilizing various test cases. One of the test cases under study is a Category III voltage fault defined in IEEE 1547-2018 and derived from CA Rule 21. Some distributed wind turbines were unable to connect to the grid following the Rule 21 enforcement in California. Even if this is not a general requirement elsewhere, the grid codes might evolve in this direction. This study illustrates how a distributed wind turbine can provide some of these FRT services and enable a pathway toward a higher contribution of renewable energy in a distribution grid.

17 WIND ENERGY↗

Adaptive Deep Reinforcement Learning Algorithm for Distribution System Cyber Attack Defense With High Penetration of DERs

With grid modernization, smart inverters are increasingly used to execute advanced controls for distribution network reliability. However, this also increases the cyber-attack space. Here this paper focuses on the defense approaches to restore the system to normal operation circumstances in the presence of cyber-attacks. A unique deep reinforcement learning (DRL) method is developed to minimize voltage violations and reduce power losses for impacted feeders. The defense problem is reformulated as a Markov decision-making process to dynamically control DERs while minimizing load shedding. This is achieved via an improved soft actor-critic (SAC)-based DRL algorithm, which can govern DER set points and load-shedding scenarios in discrete and continuous modes via the auto-tune entropy and Gaussian policy features. Numerical comparison results on the modified IEEE 123-node system with other control approaches, such as Volt-VAR (VV), Volt-Watt (VW), and model predictive control (MPC) show that the proposed method can eliminate voltage violations and provide feasible control actions that perform complete mitigation of cyber-threats.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Rotorcraft digital advanced avionics system (RODAAS) functional description

A functional design of a rotorcraft digital advanced avionics system (RODAAS) to transfer the technology developed for general aviation in the Demonstration Advanced Avionics System (DAAS) program to rotorcraft operation was undertaken. The objective was to develop an integrated avionics system design that enhances rotorcraft single pilot IFR operations without increasing the required pilot training/experience by exploiting advanced technology in computers, busing, displays and integrated systems design. A key element of the avionics system is the functionally distributed architecture that has the potential for high reliability with low weight, power and cost. A functional description of the RODAAS hardware and software functions is presented.

Peterson, E. M.↗

A multidisciplinary approach to the development of low-cost high-performance lightwave networks

Our research focuses on high-speed distributed systems. We anticipate that our results will allow the fabrication of low-cost networks employing multi-gigabit-per-second data links for space and military applications. The recent development of high-speed low-cost photonic components and new generations of microprocessors creates an opportunity to develop advanced large-scale distributed information systems. These systems currently involve hundreds of thousands of nodes and are made up of components and communications links that may fail during operation. In order to realize these systems, research is needed into technologies that foster adaptability and scaleability. Self-organizing mechanisms are needed to integrate a working fabric of large-scale distributed systems. The challenge is to fuse theory, technology, and development methodologies to construct a cost-effective, efficient, large-scale system.

Maitan, Jacek↗

Intermediate Levels of Autonomy within the SSM/PMAD Breadboard

The Space Station Module Power Management and Distribution (SSM/PMAD) bread-board is a test bed for the development of advanced power system control and automation. Software control in the SSM/PMAD breadboard is through co-operating systems, called Autonomous Agents. Agents can be a mixture of algorithmic software and expert systems. The early SSM/PMAD system was envisioned as being completely autonomous. It soon became apparent, though, that there would always be a need for human intervention, at least as long as a human interacts with the system in any way. In a system designed only for autonomous operation, manual intervention meant taking full control of the whole system, and loosing whatever expertise was in the system. Several methods for allowing humans to interact at an appropriate level of control were developed. This paper examines some of these intermediate modes of autonomy. The least humanly intrusive mode is simple monitoring. The ability to modify future behavior by altering a schedule involves high-level interaction. Modification of operating activities comes next. The coarsest mode of control is individual, unplanned operation of individual Power System components. Each of these levels is integrated into the SSM/PMAD breadboard, with support for the user (such as warnings of the consequences of control decisions) at every level.

Dugal-Whitehead, Norma R.↗

A NASA Strategy for Leveraging Emerging Launch Vehicles for Routine, Small Payload Missions

Orbital flight opportunities for small payloads have always been few and far between, and then on February 1, 2002, the situation got worse. In the wake of the loss of the Columbia during STS- 107, changing NASA missions and priorities led to the termination of the Shuttle Small Payloads Projects, including Get-Away Special, Hitcbker, and Space Experiment Module. In spite of the limited opportunities, long queue, and restrictions associated with flying experiments on a man-rated transportation system; the carriers provided a sustained, high quality experiment services for education, science, and technology payloads, and was one of the few games in town. Attempts to establish routine opportunities aboard existing ELVs have been unsuccessful, as the cost-per-pound on small ELVs and conflicts with primary spacecraft on larger vehicles have proven prohibitive. Ths has led to a backlog of existing NASA-sponsored payloads and no prospects or plans for fbture opportunities within the NASA community. The prospects for breaking out of this paradigm appear promising as a result of NASA s partnership with DARPA in pursuit of low-cost, responsive small ELVs under the Falcon Program. Through this partnership several new small ELVs, providing 1000 lbs. to LEO will be demonstrated in less than two years that promise costs that are reasonable enough that NASA, DoD, and other sponsors can once again invest in small payload opportunities. Within NASA, planning has already begun. NASA will be populating one or more of the Falcon demonstration flights with small payloads that are already under development. To accommodate these experiments, Goddard s Wallops Flight Facility has been tasked to develop a multi-payload ejector (MPE) to accommodate the needs of these payloads. The MPE capabilities and design is described in detail in a separately submitted abstract. Beyond use of the demonstration flights however, Goddard has already begun developing strategies to leverage these new ELVs as elements of a larger system designed to provide routine, low-cost end-to-end services for small science, Exploration, and education payloads. The plan leverages the management approaches of the successful Sounding Rocket Program and Shuttle Small Payloads Projects. The strategy consists of using a systems implementation approach of elements, including 1) Falcon ELVs, 2) advanced launch site technologies and processes, 3) suite of experiment carriers accommodating different mission requirements, 4) streamlined integration and test operations, 5 ) experiment brokering and management, and 6) standardized, distributed payload operations. The envisioned suite of carriers includes the MPE, a standard interface experiment carrier, and potentially a reentry fieeflyer experiment carrier. Key to the success of this strategy is standard experiment interfaces within the carriers to limit mission- unique tasks, establishmg and managing a program of scheduled reoccurring flights rather than discrete missions, and streamlined, centralized implementation of the elements. These individual elements are each under development and Goddard will demonstrate the overall system strategy low-cost small payload missions on the initial Falcon demonstration launches from Wallops. goal is to show that this model should be converted to a sustained NASA program supporting science, technology, and education, with annual flight opportunities. The paper will define in detail the various elements of the overall program, as well as provide status, philosophy, and strategy for the program that will hopefully once-and-for-all provide low-cost, routine access to space for the small payloads community.

Underwood, Bruce E.↗

NASA Tech Briefs, June 2003

Topics covered include: Nulling Infrared Radiometer for Measuring Temperature; The Ames Power Monitoring System; Hot Films on Ceramic Substrates for Measuring Skin Friction; Probe Without Moving Parts Measures Flow Angle; Detecting Conductive Liquid Leaking from Nonconductive Pipe; Adaptive Suppression of Noise in Voice Communications; High-Performance Solid-State W-Band Power Amplifiers; Microbatteries for Combinatorial Studies of Conventional Lithium-Ion Batteries; Correcting for Beam Aberrations in a Beam-Waveguide Antenna; Advanced Rainbow Solar Photovoltaic Arrays; Metal Side Reflectors for Trapping Light in QWIPs; Software for Collaborative Engineering of Launch Rockets; Software Assists in Extensive Environmental Auditing; Software Supports Distributed Operations via the Internet; Software Estimates Costs of Testing Rocket Engines; yourSky: Custom Sky-Image Mosaics via the Internet; Software for Managing Inventory of Flight Hardware; Lower-Conductivity Thermal-Barrier Coatings; Process for Smoothing an Si Substrate after Etching of SiO2; Flexible Composite-Material Pressure Vessel; Treatment to Destroy Chlorohydrocarbon Liquids in the Ground; Noncircular Cross Sections Could Enhance Mixing in Sprays; Small, Untethered, Mobile Roots for Inspecting Gas Pipes; Paint-Overspray Catcher; Preparation of Regular Specimens for Atom Probes; Inverse Tomo-Lithography for Making Microscopic 3D Parts; Predicting and Preventing Incipient Flameout in Combustors; MEMS-Based Piezoelectric/Electrostatic Inchworm Actuator; Metallized Capillaries as Probes for Raman Spectroscopy; Adaptation of Mesoscale Weather Models to Local Forecasting; Aerodynamic Design using Neural Networks; Combining Multiple Gyroscope Outputs for Increased Accuracy; and Improved Collision-Detection Method for Robotic Manipulator.

Source record↗

Optimal PV Inverter Control in Distribution Systems via Data-Driven Distributionally Robust Optimization

Distribution systems with high penetration of uncertain solar generation call for advanced control strategies of photovoltaics (PVs) inverters. This paper proposes a data-driven distributionally robust optimization (DDDRO) approach to optimally controlling the PV inverters to improve the system operation performance under solar power uncertainties. In the proposed DDDRO approach, a Wasserstein ball-based method is proposed to construct the distributional ambiguity set to model the uncertainties of PV generation through partial observations of historical data without knowing exact probability distributions. We further reformulate the computationally intractable DDDRO model to a mixed integer second order cone programming (MISOCP) problem. The effectiveness and out-of-sample performance of the proposed approach have been demonstrated on a modified IEEE 33-node system. We conduct a comparative study to compare the proposed method with traditional chance constrained programming (CCP). It shows that the proposed DDDRO approach can provide a less conservative yet robust solution to minimize the worse-case expectation of the total network loss while maintaining nodal voltages in a secure range.

Xue, Yaosuo↗

Detecting False Data Injection Attacks in Smart Grids: A Semi-Supervised Deep Learning Approach

The dependence on advanced information and communication technology increases the vulnerability in smart grids under cyber-attacks. Recent research on unobservable false data injection attacks (FDIAs) reveals the high risk of secure system operation, since these attacks can bypass current bad data detection mechanisms. To mitigate this risk, this paper proposes a data-driven learning-based algorithm for detecting unobservable FDIAs in distribution systems. We use autoencoders for efficient dimension reduction and feature extraction of measurement datasets. Further, we integrate the autoencoders into an advanced generative adversarial network (GAN) framework, which successfully detects anomalies under FDIAs by capturing the unconformity between abnormal and secure measurements. Also, considering that the datasets collected from practical power systems are partially labeled due to expensive labeling costs and missing labels, the proposed method only requires a few labeled measurement data in addition to unlabeled data for training. Numerical simulations in three-phase unbalanced IEEE 13-bus and 123-bus distribution systems validate the detection accuracy and efficiency of this method.

97 MATHEMATICS AND COMPUTING↗

A curriculum for real-time computer and control systems engineering

An outline of a syllabus for the education of real-time-systems engineers is given. This comprises the treatment of basic concepts, real-time software engineering, and programming in high-level real-time languages, real-time operating systems with special emphasis on such topics as task scheduling, hardware architectures, and especially distributed automation structures, process interfacing, system reliability and fault-tolerance, and integrated project development support systems. Accompanying course material and laboratory work are outlined, and suggestions for establishing a laboratory with advanced, but low-cost, hardware and software are provided. How the curriculum can be extended into a second semester is discussed, and areas for possible graduate research are listed. The suitable selection of a high-level real-time language and supporting operating system for teaching purposes is considered.

Halang, Wolfgang A.↗

Artificial Intelligence-Driven Management of Sustainable Energy Resources: Visibility, Operation, and Control

The rapid global transition toward sustainable energy resources (SERs) is reshaping how modern power systems are observed, optimized, and controlled. While SERs have significantly advanced decarbonization, their weather dependence, variability, and inverter-dominated characteristics challenge traditional, centralized, and deterministic grid operation. At the same time, the proliferation of high-resolution data from inverters, smart meters, and sensors offers unprecedented visibility into system dynamics. Yet, it also exceeds the analytical capability of conventional model-based approaches. Artificial intelligence (AI) provides a new foundation for addressing these challenges by bridging physical laws with data-driven learning, enabling accurate state awareness, adaptive operation, and coordinated control across distributed assets. This article examines how AI transforms the management of SER-rich power systems along three critical dimensions: 1) enhancing visibility by inferring behind-the-meter (BTM) activities, assessing SER flexibility, and reconstructing system states from sparse or noisy measurements; 2) improving operation through AI-enhanced SER service provision, volt/var control (VVC), and dynamic operating envelopes (DOE) for efficiency and security; and 3) advancing control by embedding learning-based intelligence into inverter coordination, voltage and frequency regulation, and long-term dispatch. Together, these developments reveal how AI can convert the variability of SERs from an operational challenge into a source of flexibility, resilience, and intelligence, paving the way toward sustainable, adaptive, and self-optimizing power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A digital twin platform for building performance monitoring and optimization: Performance simulation and case studies

Advancements in sensor technology, data analytics, affordable compute, and communication infrastructure have paved the way for Digital Twin technology in optimizing building operations and controls. This study presents the development of an open and interoperable web-based Digital Twin platform for integrating diverse data streams and facilitating effective user interactions. The platform utilizes modern technologies for the web framework and time-series data management, ensuring scalability and responsiveness. The backend supports seamless integration of diverse data sources and emulators, incorporating data from building sensors and meters, external weather Application Programming Interfaces, and advanced EnergyPlus simulation models of the building and its energy systems including the Distributed Energy Resources that are formulated in Functional Mockup Units. A simulation case study was conducted with FlexLab, a test facility on Lawrence Berkeley National Laboratory campus. The case study includes normal operations, Distributed Energy Resource integration, and power outage scenarios, to illustrate the Digital Twin’s ability to provide critical insights into energy performance and thermal resilience. The results demonstrated the platform’s potential as a decision-support tool for optimizing building energy performance and enhancing resilience against extreme weather events. Future work will focus on deploying the Digital Twin platform to a real building for field validation, extending its capabilities to cover more scenarios such as bidirectional Electric Vehicle interactions, and enhancing user engagement.

EnergyPlus↗

Optical Fuel Injector Patternation Measurements in Advanced Liquid-Fueled, High Pressure, Gas Turbine Combustors

Planar laser-induced fluorescence (PLIF) imaging and planar Mie scattering are used to examine the fuel distribution pattern (patternation) for advanced fuel injector concepts in kerosene burning, high pressure gas turbine combustors. Three fuel injector concepts for aerospace applications were investigated under a broad range of operating conditions. Fuel PLIF patternation results are contrasted with those obtained by planar Mie scattering. For one injector, further comparison is also made with data obtained through phase Doppler measurements. Differences in spray patterns for diverse conditions and fuel injector configurations are readily discernible. An examination of the data has shown that a direct determination of the fuel spray angle at realistic conditions is also possible. The results obtained in this study demonstrate the applicability and usefulness of these nonintrusive optical techniques for investigating fuel spray patternation under actual combustor conditions.

Locke, R. J.↗

Investigating the Nature of and Methods for Managing Metroplex Operations

A combination of traffic demand growth, Next Generation Air Transportation System (NextGen) technologies and operational concepts, and increased utilization of regional airports is expected to increase the occurrence and severity of coupling between operations at proximate airports. These metroplex phenomena constrain the efficiency and/or capacity of airport operations and, in NextGen, have the potential to reduce safety and prevent environmental benefits. Without understanding the nature of metroplexes and developing solutions that provide efficient coordination of operations between closely-spaced airports, the use of NextGen technologies and distribution of demand to regional airports may provide little increase in the overall metroplex capacity. However, the characteristics and control of metroplex operations have not received significant study. This project advanced the state of knowledge about metroplexes by completing three objectives: 1. developed a foundational understand of the nature of metroplexes; 2. provided a framework for discussing metroplexes; 3. suggested and studied an approach for optimally managing metroplexes that is consistent with other NextGen concepts

Atkins, Stephen↗