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At least 667 records · Page 37

Dynamically robust coordinated set point tracking of distributed DERs at point of common coupling

Low-inertia operation of small-scale power systems, such as a microgrid or a portion of a long feeder, requires careful coordination of the controller performance of the constituting devices. This challenge is exacerbated in microgrids serving the functionalities of a conventional synchronous-based generation unit while comprised of smaller DERs operating mainly interfaced through power electronics converters. This paper builds on the idea of set point modulation and proposes a two-level control strategy that aims to achieve superior performance at the point of common coupling (PCC) of microgrids by combining a local control level with a distributed and coordinated level. Several case studies on both AC and DC systems, the CIGRE low-voltage benchmark system as the AC system and a test DC microgrid, validate the performance of the proposed approach. The real-world applicability of the approach is established via a high-fidelity power hardware-in-the-loop (PHIL) experimental setup and an application case study on grid frequency regulation. The proposed approach enables a microgrid to participate in ancillary service provisions where speed and quality of regulation are critical.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Numerical fluid dynamics for FRG flow equations: Zero-dimensional QFTs as numerical test cases. I. The O ( N ) model

The functional renormalization group (FRG) approach is a powerful tool for studies of a large variety of systems, ranging from statistical physics over the theory of the strong interaction to gravity. The practical application of this approach relies on the derivation of so-called flow equations, which describe the change of the quantum effective action under the variation of a coarse-graining parameter. In the present work, we discuss in detail a novel approach to solve such flow equations. This approach relies on the fact that RG equations can be rewritten such that they exhibit similarities with the conservation laws of fluid dynamics. This observation can be exploited in different ways. First of all, we show that this allows to employ powerful numerical techniques developed in the context of fluid dynamics to solve RG equations. In particular, it allows us to reliably treat the emergence of nonanalytic behavior in the RG flow of the effective action as it is expected to occur in studies of, e.g., spontaneous symmetry breaking. Second, the analogy between RG equations and fluid dynamics offers the opportunity to gain novel insights into RG flows and their interpretation in general, including the irreversibility of RG flows. Further, we work out this connection in practice by applying it to zero-dimensional quantum-field theoretical models. The generalization to higher-dimensional models is also discussed. Our findings are expected to help improving future FRG studies of quantum field theories in higher dimensions both on a qualitative and quantitative level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Strengthening the Security of Operational Technology: Understanding Contemporary Bill of Materials

The evolution of cyber-physical infrastructure has made its security more challenging. The last few years have witnessed a convergence of hardware and software segments in various domains, including operational technology (OT) which is responsible for carrying out critical tasks such as monitoring and controlling power grids, nuclear plants, transportation, and emergency services. Both hardware and software encapsulate numerous open source and proprietary subcomponents, making it crucial for end-users to understand the composition of the products they are using. For example, wind turbines incorporate thousands of lines of code (software) used for the turbine's design, planning, operation, and analytics in addition to the numerous hardware subcomponents that construct it. Due to the highly complex nature of software and hardware, knowledge of the components and subcomponents is required to mitigate cyber vulnerabilities and defend against cyberattacks. There has also been a transformation from a traditional linear supply chain into a global, dynamic, diverse, and interconnected system. The digitization of the supply chain makes it easier to find and exploit vulnerabilities. Critical infrastructures (e.g., power grids, oil, natural gas, water, and wastewater) rely on OT to function, and if the OT is compromised, equipment damage and potential interruption of services could result. A significant security measure to protect OT systems from disruption is to develop a supply chain bill of materials (BoM) corresponding to the software and hardware used in OT, along with attestations amongst vendors and asset owners. A supply chain BoM is a proactive way to understand the inherent vulnerabilities in the system and mitigate them in advance of being exploited. BoMs bolster the trust placed in the digital infrastructure and enhance software supply chain security by sustaining the management of component obsolescence and compliance, along with the seclusion of unsafe segments of a specific product. Adopting BoM tools is becoming increasingly important across various government sectors, as evidenced by the recent U.S. executive order on cybersecurity (NIST 2021). This paper aims to classify BoMs based on structure, functionality, component type, and architecture. The work also discusses case studies to further highlight the benefits of BoMs. In addition, it identifies missing pieces in existing BoM implementations so that future research may identify bounds on where it could expect to make improvements and directly enable researchers to identify promising areas for exploration. Further, the authors provide valuable recommendations to tool developers, researchers, and standardizing organizations (policymakers), additionally benefitting critical infrastructure owners and government executives. This aids in paving a path for future work, thereby, providing suggestions to determine a tool for consumers that best suit their needs.

97 MATHEMATICS AND COMPUTING↗

Design and Engineering of LUPIN: A Test-Bed Radio-Frequency Ion Source for Enhanced Neutral Beam Injection on DIII-D

The Large, Uniform Plasma for Ionizing Neutrals (LUPIN) is a radio-frequency (RF) inductively coupled plasma (ICP) chamber for demonstrating plasma performance of an RF ICP positive ion source upgrade for the DIII-D neutral beam injection (NBI) system. LUPIN will be used to investigate ion source physics, including neutral gas dynamics, plasma density uniformity, interactions with Faraday shields, and power coupling to novel RF antenna designs. LUPIN has an RF generator capable of delivering 20 kW of power at 2 MHz, which is coupled into a cylindrical quartz vessel measuring 20 cm in length and 10 cm in radius. This configuration matches the power density requirements for a full-scale ion source. Target hydrogen and deuterium plasma densities exceeding 10 18 m -3 would relate to extracted ion current densities of 2100 A/m 2 for 10s. Vacuum conductance and gas flow calculations predict a maximum achievable neutral gas flow rate of 1675 Pa ⋅ L/s at 5 Pa of He, which mimics the gas flow of the DIII-D NBI system. Designs have been developed for an internal Faraday shield to mitigate heat flux and ion sputtering on the dielectric vessel. Thermomechanical finite element simulations demonstrated the Faraday shield design to be capable of withstanding anticipated heat loads from worst-case operation scenarios. Finally, results of upcoming experimental investigations on LUPIN will guide the design of a full-scale prototype for DIII-D integration.

Faraday shield↗

Discrete-Time Causal Control of a Wave Energy Converter With Finite Stroke in Stochastic Waves

We consider feedback control design for a wave energy converter (WEC) for which the power takeoff (PTO) system has a finite stroke limit. Stationary stochastic wave loading is assumed, with a known spectrum, and the plant dynamics are assumed to be linear. We develop a technique for the design of a discrete-time controller, which has three design stages. In the first stage, a linear controller is optimized while imposing a relaxation of the maximum stroke constraint on the design. In the second stage, a tandem nonlinear feedback loop is designed for the purpose of stroke protection. In the third stage, the two designs (linear and nonlinear) are fused in a manner that preserves the stability of the overall system. The technique is demonstrated in a simulation of a simple cylindrical buoy. We show that the controller may be tuned through the adjustment of scalar design parameters, which adjust the tradeoff between the mean generated power and the force levels required to protect the stroke.

16 TIDAL AND WAVE POWER↗

Design and Engineering of LUPIN: A Test-Bed Radiofrequency Ion Source for Enhanced Neutral Beam Injection on DIII-D

The Large, Uniform Plasma for Ionizing Neutrals (LUPIN) is an RF inductively coupled plasma (ICP) chamber for demonstrating plasma performance of an RF ICP positive ion source upgrade for the DIII-D Neutral Beam Injection (NBI) system. LUPIN will be used to investigate ion source physics, including neutral gas dynamics, plasma density uniformity, interactions with Faraday shields, and power coupling to novel RF antenna designs. LUPIN has an RF generator capable of delivering 20 kW of power at 2 MHz, which is coupled into a cylindrical quartz vessel measuring 20 cm in length and 10 cm in radius. This configuration matches the power density requirements for a full-scale ion source. Target hydrogen and deuterium plasma densities exceeding 10 18 m -3 would relate to extracted ion current densities of 2100 A/m 2 for 10 s. Vacuum conductance and gas flow calculations predict a maximum achievable neutral gas flow rate of 1675 Pa·L/s at 5 Pa of He, which mimics the gas flow of the DIII-D NBI system. Designs have been developed for an internal Faraday shield to mitigate heat flux and ion sputtering on the dielectric vessel. Thermomechanical finite element simulations demonstrated the Faraday shield design to be capable of withstanding anticipated heat loads from worst-case operation scenarios. Results of upcoming experimental investigations on LUPIN will guide the design of a full-scale prototype for DIII-D integration.

Faraday shield↗

Developing a Hybrid Electric Vehicle Eco-Cooperative Adaptive Cruise Control System at Signalized Intersections.

This study develops an eco-driving strategy for hybrid electric vehicles (HEVs) in the vicinity of signalized intersections, entitled HEV Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I). The proposed system computes real-time, energy-optimized vehicle trajectories using HEV vehicle dynamics and energy consumption models. In the proposed system, a simple HEV energy model is used to compute the instantaneous fuel consumption. This HEV energy model is selected since it is general, transferable, and can be easily used to compute instantaneous energy consumption levels for HEVs without the additional input of vehicle engine data or complicated power control strategies. In addition, a vehicle dynamics model is used to capture the relationship between speed, acceleration level, and tractive/resistance forces on vehicles. The energy-optimum problem is formulated as an optimization problem with constraints, which is solved using a moving-horizon dynamic programming approach. The proposed HEV Eco-CACC-I system was tested to evaluate its performance for various speed limits, roadway grades, and signal timings. Lastly, the proposed HEV controller was implemented in a microscopic traffic simulation software to test its network-wide performance. The test results from an arterial corridor with three signalized intersections demonstrate that the proposed system can effectively reduce stop-and-go traffic in the vicinity of signalized intersections producing savings of 7.4% in energy consumption, 5.8% in traffic delay and 23% vehicle stops, respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Molecular structure retrieval directly from laboratory-frame photoelectron spectra in laser-induced electron diffraction

Ubiquitous to most molecular scattering methods is the challenge to retrieve bond distance and angle from the scattering signals since this requires convergence of pattern matching algorithms or fitting methods. This problem is typically exacerbated when imaging larger molecules or for dynamic systems with little a priori knowledge. Here, we employ laser-induced electron diffraction (LIED) which is a powerful means to determine the precise atomic configuration of an isolated gas-phase molecule with picometre spatial and attosecond temporal precision. We introduce a simple molecular retrieval method, which is based only on the identification of critical points in the oscillating molecular interference scattering signal that is extracted directly from the laboratory-frame photoelectron spectrum. The method is compared with a Fourier-based retrieval method, and we show that both methods correctly retrieve the asymmetrically stretched and bent field-dressed configuration of the asymmetric top molecule carbonyl sulfide (OCS), which is confirmed by our quantum-classical calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Active liquid crystals powered by force-sensing DNA-motor clusters

Significance Single-molecule techniques have elucidated how isolated molecular motors generate piconewton forces with unprecedented detail. However, in diverse biological and synthetic settings, force-generating proteins collectively power nonequilibrium dynamics, including continuous large-scale rearrangements and persistent fluid flows. Characterizing motor-generated forces in these dense and dynamical environments remains a challenge. We assembled a reversible DNA-based force-sensing probe that, by an optical readout, reveals the molecular arrangements and the force loads experienced by kinesin motors. These probes provide insight into motor-generated forces that collectively power the unique dynamics of microtubule-based active nematics, a noteworthy example of an internally driven active matter system. DNA-based force probes can be extended to study forces and stresses in various synthetic systems as well as diverse cellular environments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Self-Organizing Nano Grid (SONG) for Energy Access Clusters

In this paper, a bottom-up dc Self-Organizing Nano Grid (SONG) for rural electrification at ultra-low-cost through a flexible and scalable topology is presented. The proposed nano grid requires no communication and uses dc-bus signaling to convey excess energy in the system through the bus voltage, allowing independent agents to conduct energy transactions based on their needs in a decentralized manner. Moreover, this article proposes a concept that uses a novel multi-source, multi-segment droop control strategy with demand coordination, allowing for dynamic self-balancing of the system under fluctuating operating conditions. The unique use of a surplus photovoltaic (PV) power droop mode precisely estimates energy availability to minimize load chattering that helps in stabilizing the dc-bus. In addition, this architecture uses standard dc/dc converters for a low-cost, modular, Plug and Play ( PnP ) solution with highly automated operation, enabling local assembly, operation, and maintenance by non-technical personnel. The proposed SONG concept was validated in simulation and with a 700W, laboratory-scale, custom made nano grid system. The simulation and experimental test cases show the feasibility of the SONG system by demonstrating the proposed multi-source, multi-segment droop control strategy without load chattering under varying operating conditions.

dc-dc converter↗

Exploring the Frontiers of Energy Efficiency using Power Management at System Scale

In the face of surging power demands for exascale HPC systems, this work tackles the critical challenge of understanding the impact of software-driven power management techniques like Dynamic Voltage and Frequency Scaling (DVFS) and Power Capping. These techniques have been actively developed over the past few decades. By combining insights from GPU benchmarking to understand application power profiles, we present a telemetry data-driven approach for deriving energy savings projections. This approach has been demonstrably applied to the Frontier supercomputer at scale. Our findings based on three months of telemetry data indicate that, for certain resource-constrained jobs, significant energy savings (up to 8.5%) can be achieved without compromising performance. This translates to a substantial cost reduction, equivalent to 1438 MWh of energy saved. The key contribution of this work lies in the methodology for establishing an upper limit for these best-case scenarios and its successful application. This work enables HPC professionals to optimize the power-performance trade-off within constrained power budgets, not only for the exascale era but also beyond.

Karimi, Ahmad Maroof↗

Voltage Regulation Performance Evaluation of Distributed Energy Resource Management via Advanced Hardware-in-the-Loop Simulation

This paper evaluates the performance of coordinated control across advanced distribution management systems (ADMS), distributed energy resources (DERs), and distributed energy resource management systems (DERMS) using an advanced hardware-in-the-loop (HIL) platform. This platform provides a realistic laboratory testing environment, including accurate dynamic modeling of a real-world distribution system from a utility partner, real controllers (ADMS and DERMS), physical power hardware (DERs), and standard communications protocols. One grid service—voltage regulation—is evaluated to show the performance of the coordinated grid automation system. The testing results demonstrate that the coordinated DERMS and ADMS system can effectively regulate system voltages within target operation limits using DERs. The realistic laboratory HIL testing results give utilities confidence in adopting the grid automation systems to manage DERs to achieve system-level control and operation objectives (e.g., voltage regulation). This helps utilities mitigate potential risks (e.g., instability) prior to field deployment.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Novel Multiagent Resource Sharing Algorithm for Control of Advanced Energy Systems

This paper implements a novel resource sharing control strategy on a fuel cell–gas turbine hybrid power system at the National Energy Technology Laboratory’s Hybrid Performance Facility (Hyper). In a fuel cell–gas turbine hybrid power system, the simultaneous interaction of the gas turbine and the fuel cell creates a tightly coupled environment characterized by conflicting dynamics. In this paper, a model-free control approach is applied to solve the tightly coupled control problem posed by this challenging environment. Specifically, this control problem is presented as a resource sharing problem that can be solved using a resource sharing algorithm that is defined based on the distribution construction concept. This algorithm creates computational agents and solves the problem through the distribution and redistribution of shared resources defined as blocks. Furthermore, two agents were created; the first agent (agent 1) controls the gas turbine speed by adjusting the electric load, and the second agent (agent 2) controls the cathode mass flow through the fuel cell using the cold-air bypass valve. A parametric study was performed over the course of 15 experimental tests for both agents 1 and 2 through an evaluation of the responses based on setpoint changes. The algorithm was shown to have behavior comparable to a previously implemented multi-input multioutput state-space controller, which was designed through a model-based control approach. The resource sharing algorithm was able to find stable performance during run-time operations without any prior system knowledge identification on the power plant and without creating models used in traditional control strategies.

25 ENERGY STORAGE↗

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↗

A Persistence Meter for Nimble Alarming Using Ambient Synchrophasor Data

Persistent oscillations in the power grid are often indicative of fragility, and may be harbingers of systemic or cascading failures. Modernization of the grid, including increased penetration of intermittent renewables and integration of new power electronics, is making the oscillatory swing dynamics of the network both more complex and variable. In this project researchers from the University of Wisconsin-Madison (Bernard Lesieutre, lead), Washington State University (Sandip Roy, lead), and the Electric Power Group (Neeraj Nayak, lead) have developed technologies that monitor persistent oscillations in the grid and provide operators with alarms and analytics when concerning oscillations are detected. Some of the algorithms have already been implemented in EPG’s PGDA software and integrated into their RTDMS system for use in control rooms.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Synergistic Integration of Multiple Wave Energy Converters with Adaptive Resonance and Offshore Floating Wind Turbines through Bayesian Optimization

We developed a synergistic ocean renewable system where an array of Wave Energy Converters (WEC) with adaptive resonance was collocated with a Floating Offshore Wind Turbine (FOWT) such that the WECs, capturing wave energy through the resonance adapting to varying irregular waves, consequently reduced FOWFT loads and turbine motions. Combining Surface-Riding WECs (SR-WEC) individually designed to feasibly relocate their natural frequency at the peak of the wave excitation spectrum for each sea state, and to obtain the highest capture width ratio at one of the frequent sea states for annual average power in a tens of kilowatts scale with a 15 MW FOWT based on a semi-submersible, Bayesian Optimization is implemented to determine the arrangement of WECs that minimize the annual representation of FOWT’s wave excitation spectra. The time-domain simulation of the system in the optimized arrangement is performed, including two sets of interactions: one set is the wind turbine dynamics, mooring lines, and floating body dynamics for FOWT, and the other set is the nonlinear power-take-off dynamics, linear mooring, and individual WECs’ floating body dynamics. Those two sets of interactions are further coupled through the hydrodynamics of diffraction and radiation. For sea states comprising Annual Energy Production, we investigate the capture width ratio of WECs, wave excitation on FOWT, and nacelle acceleration of the turbine compared to their single unit operations. We find that the optimally arranged SR-WECs reduce the wave excitation spectral area of FOWT by up to 60% and lower the turbine’s peak nacelle acceleration by nearly 44% in highly occurring sea states, while multiple WECs often produce more than the single operation, achieving adaptive resonance with a larger wave excitation spectra for those sea states. The synergistic system improves the total Annual Energy Production (AEP) by 1440 MWh, and we address which costs of Levelized Cost Of Energy (LCOE) can be reduced by the collocation.

Engineering↗