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At least 1,405 records · Page 78

Impacts of Regional Coordination on Transmission Needs for Power System Resource Adequacy [Slides]

Resource adequacy (RA) is an important component of bulk power system reliability that addresses whether there are sufficient resources available to meet electricity demand at all times. RA analysis is used to assess whether the planned power system will provide reliable electricity to consumers while accounting for equipment outages, weather variability, and load uncertainty. Coordination between regions can enable resource sharing to meet RA needs if sufficient transmission capacity exists. Transmission's role in RA coordination can be particularly pronounced for large power systems like the U.S. electricity grid which contains geographically diverse demand and weather-dependent resources. Depending on the level of coordination desired, existing inter-regional transmission capacity may not be sufficient. This study is designed to assess optimal pathways for the development of inter-regional transmission in the U.S. under varying levels of RA coordination. Results can inform long-term grid infrastructure planning and provide insights into potential benefits of greater coordination for generation and transmission planning between regional U.S. power systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Robust Scheduling of Networked Microgrids for Economics and Resilience Improvement

The benefits of networked microgrids in terms of economics and resilience are investigated and validated in this work. Considering the stochastic unintentional islanding conditions and conventional forecast errors of both renewable generation and loads, a two-stage adaptive robust optimization is proposed to minimize the total operating cost of networked microgrids in the worst scenario of the modeled uncertainties. By coordinating the dispatch of distributed energy resources (DERs) and responsive demand among networked microgrids, the total operating cost is minimized, which includes the start-up and shut-down cost of distributed generators (DGs), the operation and maintenance (O&M) cost of DGs, the cost of buying/selling power from/to the utility grid, the degradation cost of energy storage systems (ESSs), and the cost associated with load shedding. The proposed optimization is solved with the column and constraint generation (C&CG) algorithm. The results of case studies demonstrate the advantages of networked microgrids over independent microgrids in terms of reducing total operating cost and improving the resilience of power supply.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Investigation of Navier-Stokes Code Verification and Design Optimization

With rapid progress made in employing computational techniques for various complex Navier-Stokes fluid flow problems, design optimization problems traditionally based on empirical formulations and experiments are now being addressed with the aid of computational fluid dynamics (CFD). To be able to carry out an effective CFD-based optimization study, it is essential that the uncertainty and appropriate confidence limits of the CFD solutions be quantified over the chosen design space. The present dissertation investigates the issues related to code verification, surrogate model-based optimization and sensitivity evaluation. For Navier-Stokes (NS) CFD code verification a least square extrapolation (LSE) method is assessed. This method projects numerically computed NS solutions from multiple, coarser base grids onto a freer grid and improves solution accuracy by minimizing the residual of the discretized NS equations over the projected grid. In this dissertation, the finite volume (FV) formulation is focused on. The interplay between the xi concepts and the outcome of LSE, and the effects of solution gradients and singularities, nonlinear physics, and coupling of flow variables on the effectiveness of LSE are investigated. A CFD-based design optimization of a single element liquid rocket injector is conducted with surrogate models developed using response surface methodology (RSM) based on CFD solutions. The computational model consists of the NS equations, finite rate chemistry, and the k-6 turbulence closure. With the aid of these surrogate models, sensitivity and trade-off analyses are carried out for the injector design whose geometry (hydrogen flow angle, hydrogen and oxygen flow areas and oxygen post tip thickness) is optimized to attain desirable goals in performance (combustion length) and life/survivability (the maximum temperatures on the oxidizer post tip and injector face and a combustion chamber wall temperature). A preliminary multi-objective optimization study is carried out using a geometric mean approach. Following this, sensitivity analyses with the aid of variance-based non-parametric approach and partial correlation coefficients are conducted using data available from surrogate models of the objectives and the multi-objective optima to identify the contribution of the design variables to the objective variability and to analyze the variability of the design variables and the objectives. In summary the present dissertation offers insight into an improved coarse to fine grid extrapolation technique for Navier-Stokes computations and also suggests tools for a designer to conduct design optimization study and related sensitivity analyses for a given design problem.

Vaidyanathan, Rajkumar↗

Aerodynamic shape optimization of wing and wing-body configurations using control theory

This paper describes the implementation of optimization techniques based on control theory for wing and wing-body design. In previous studies it was shown that control theory could be used to devise an effective optimization procedure for airfoils and wings in which the shape and the surrounding body-fitted mesh are both generated analytically, and the control is the mapping function. Recently, the method has been implemented for both potential flows and flows governed by the Euler equations using an alternative formulation which employs numerically generated grids, so that it can more easily be extended to treat general configurations. Here results are presented both for the optimization of a swept wing using an analytic mapping, and for the optimization of wing and wing-body configurations using a general mesh.

Reuther, James↗

Controlling distributed energy resources via deep reinforcement learning for load flexibility and energy efficiency

Behind-the-meter distributed energy resources (DERs), including building solar photovoltaic (PV) technology and electric battery storage, are increasingly being considered as solutions to support carbon reduction goals and increase grid reliability and resiliency. However, dynamic control of these resources in concert with traditional building loads, to effect efficiency and demand flexibility, is not yet commonplace in commercial control products. Traditional rule-based control algorithms do not offer integrated closed-loop control to optimize across systems, and most often, PV and battery systems are operated for energy arbitrage and demand charge management, and not for the provision of grid services. More advanced control approaches, such as MPC control have not been widely adopted in industry because they require significant expertise to develop and deploy. Recent advances in deep reinforcement learning (DRL) offer a promising option to optimize the operation of DER systems and building loads with reduced setup effort. However, there are limited studies that evaluate the efficacy of these methods to control multiple building subsystems simultaneously. Additionally, most of the research has been conducted in simulated environments as opposed to real buildings. This paper proposes a DRL approach that uses a deep deterministic policy gradient algorithm for integrated control of HVAC and electric battery storage systems in the presence of on-site PV generation. The DRL algorithm, trained on synthetic data, was deployed in a physical test building and evaluated against a baseline that uses the current best-in-class rule-based control strategies. Performance in delivering energy efficiency, load shift, and load shed was tested using price-based signals. The results showed that the DRL-based controller can produce cost savings of up to 39.6% as compared to the baseline controller, while maintaining similar thermal comfort in the building. The project team has also integrated the simulation components developed during this work as an OpenAIGym environment and made it publicly available so that prospective DRL researchers can leverage this environment to evaluate alternate DRL algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Advanced Transmission Technologies (ATTs) Supplier Cohort Workshops Cohort Summary [Slides]

This Summary slide deck summarizes the key outcomes of the Advanced Transmission Technologies (ATTs) supplier cohort, part of Idaho National Laboratory’s (INL) Technical Assistance for Digital Assurance (TADA) program. The program aimed to strengthen grid resilience through cybersecurity controls, supply-chain security, and Cyber-Informed Engineering (CIE) for advanced transmission technologies. The cohort brought together vendors representing the full range of Grid-Enhancing Technologies (GETs), including providers of Dynamic Line Ratings (DLR), Advanced Power Flow Control (APFC), Transmission Topology Optimization (TTO), and High-Performance Conductors (HPCs). Discussions focused on institutional, integration, and operational barriers limiting GET adoption; cybersecurity risks at EMS/SCADA, cloud, and network integration points; and supply-chain transparency issues such as semiconductor dependence and SBOM/HBOM expectations. Participants also addressed operator trust, human-in-the-loop requirements, and challenges with utility adoption, while exploring how CIE can support secure deployment of GETs. This deck represents a consolidated summary of challenges and risks identified by vendors, cross-cutting themes and technology-specific insights from three cohort workshops, and actionable mitigations to guide utilities, vendors, and the Department of Energy in advancing secure, trusted deployment of GETs.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

PMU-data-driven Event Classification in Power Transmission Grids

This paper presents an event classification in transmission grids. The convolutional neural network (CNN)-based classifier is proposed to capture the temporal similarity of time-synchronized data stream from phasor measurement units (PMUs). The proposed CNN is trained using Bayesian optimization to search for the best hyperparameters. The effectiveness of the proposed event classification is validated through the real-world dataset from the U.S. transmission grids. This dataset includes line outage, transformer outage, frequency, and oscillation events. The validation process also includes different PMU outputs, such as voltage magnitude, phase angle, current magnitude, frequency, and rate of change of frequency (ROCOF). The results show that ROCOF gives the best classification performance compared to other PMU outputs. In addition, it is shown that the classifier trained with a larger dataset has higher accuracy. Moreover, the superiority of the proposed method is validated through comparison with other state-of-the-art classification methods.

Niazazari, Iman↗

SU-E-T-331: Dosimetric Impact of Multileaf Collimator Leaf Width On Stereotactic Radiosurgery (SRS) RapidArc Treatment Plans for Single and Multiple Brain Metastases

Purpose: To determine the effects of multileaf collimator (MLC) leaf width on normal-brain-tissue doses and dose conformity of SRS RapidArc treatment plans for brain tumors. Methods: Ten patients with 24 intracranial tumors (seven with 1–2 and three with 4–6 lesions) were planned using RapidArc for both Varian Millennium 120 MLC (5 mm leaf width) and high definition (HD) MLC (2.5 mm leaf width). Between 2 and 8 arcs were used with two full coplanar arcs and the rest non-coplanar half arcs. 6 MV beams were used and plans were optimized with a high priority to the Normal Tissue Objective (to achieve dose conformity and sharp dose fall-off) and normal brain tissue. Calculation was done using AAA on a 1 mm grid size. The prescription dose ranged from 14–22 Gy. Plans were normalized such that 99% of the target received the prescription dose. Identical beam geometries, optimizations, calculations, and normalizations were used for both plans. Paddick Conformity Index (PCI), V4, V8 and V12 Gy for normal brain tissue and Integral Dose were used for analysis. Results: In all cases, HD MLC plans performed better in sparing normal brain tissue, achieving a higher PCI with a lower Integral Dose. The average PCI for all 24 targets was 0.75±0.23 and 0.70±0.23 (p ≤0.0015) for HD MLC and Millennium MLC plans, respectively. The average ratio of normal brain doses for Millennium MLC to HD MLC plans was 1.30±0.16, 1.27±0.15, and 1.31±0.18 for the V4, V8, and V12, respectively. The differences in normal brain dose for all criteria were statistically significant with p-value < 0.02. On average Millennium MLC plans had a 16% higher integral dose than HD MLC plans. Conclusion: Significantly better dose conformity with reduced volume of normal brain tissue and integral dose was achieved with HD MLC plans compared to Millennium MLC plans.

60 APPLIED LIFE SCIENCES↗

Electrolyzers Enhancing Flexibility in Electric Grids

This paper presents a real-time simulation with hardware-in-the-loop (HIL) based approach for verifying the performance of electrolyzer systems in providing grid support. Hydrogen refueling stations premdominantly use electrolyzer systems to generate hydrogen, and are proposed to have the potential of becoming smarter loads which can pro-actively provide grid services. Based on experimental findings electrolyzer systems are observed to have a high level of controllability and hence can add flexibility to the grid from demand side. Greater awareness and controllability is proposed, developed, implemented, and tested by a 'frond end controller' in real-time environment. It can optimize the operation of electrolyzer systems based on the information collected by a communication module. Real-time tests are performed to verify the performance of front end controller driven electrolyzers to provide grid support that enables greater economic revenue and grid support for hydrogen producers under dynamic conditions. The front end controller proposed in this paper is tested with electrolyzers, however it is proposed as a generic control topology that is applicable to any load.

08 HYDROGEN↗

Design and dispatch optimization of packaged ice storage systems within a connected community

The traditional implementation of cool thermal energy storage (CTES) must be reimagined within the context of a dynamic grid and smart buildings operating as connected communities. As most buildings do not operate central chillers or connect to district cooling loops, this necessitates a broader use of packaged CTES. Our objective is to begin answering the question of how such packaged CTES should be implemented within a connected community. We do so by presenting a simulation–optimization workflow employing building energy modeling software and a mixed-integer linear program to design and dispatch a packaged CTES technology to achieve minimum total annual cost. We demonstrate this methodology on a seven-building case study using current utility rates and find that total annual cooling energy costs can be reduced by 17.8% compared to baseline, after accounting for the cost of storage. We perform three parametric sensitivity studies to evaluate modeling assumptions and obtain the prioritization of storage procurement as a function of annualized life-cycle cost of storage. We find that a community optimization approach provides significantly different results than individual building optimizations and provides greater savings compared to baseline.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Demand Response Resources for Energy and Ancillary Services (Presentation)

Demand response (DR) resources present a potentially important source of grid flexibility particularly on future systems with high penetrations of variable wind an solar power generation. However, DR in grid models is limited by data availability and modeling complexity. This presentation focuses on the co-optimization of DR resources to provide energy and ancillary services in a production cost model of the Colorado test system. We assume each DR resource can provide energy services by either shedding load or shifting its use between different times, as well as operating

14 SOLAR ENERGY↗

Scenario Creation and Power-Conditioning Strategies for Operating Power Grids with Two-Stage Stochastic Economic Dispatch: Preprint

A significant difficultly associated with the use of stochastic programming to solve optimal power flow problems on a 5-minute timescale is the quality of renewable energy scenarios input by the user. This is especially true when considering power systems with high penetrations of renewable energy, e.g. wind power. This paper introduces the use of stochastic programming to solve the DCOPF problem with scenarios drawn directly from high-fidelity data sets. Hence, the proposed method avoids the problem of lost physics by finding high-fidelity analogs that can describe future states of the system. Furthermore, this method can be simply extended to output multi-period scenarios to the stochastic program. We demonstrate the effectiveness of this technique on simulated dispatch operations of the RTS-GMLC over a week.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Electron attenuation in free, neutral ethane clusters

The electron effective attenuation length (EAL) in free, neutral ethane clusters has been determined at 40 eV kinetic energy by combining carbon 1s x-ray photoelectron spectroscopy and theoretical lineshape modeling. More specifically, theory is employed to form model spectra on a grid in cluster size (N) and EAL (λ), allowing N and λ to be determined by optimizing the goodness-of-fit χ{sup 2}(N, λ) between model and observed spectra. Experimentally, the clusters were produced in an adiabatic-expansion setup using helium as the driving gas, spanning a range of 100–600 molecules in mean cluster size. The effective attenuation length was determined to be 8.4 ± 1.9 Å, in good agreement with an independent estimate of 10 Å formed on the basis of molecular electron-scattering data and Monte Carlo simulations. The aggregation state of the clusters as well as the cluster temperature and its importance to the derived EAL value are discussed in some depth.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Cross-Domain Optimization Framework of PMU and Communication Placement for Multidomain Resiliency and Cost Reduction

Phasor measurement units (PMUs) play a crucial role in real-time monitoring and control of power grids. They rely on a communication network to transfer measurement data to the phasor data concentrator (PDC) for further processing and analysis. In this paper, a resilient cross-domain PMU and communication link placement method for minimizing the overall installation cost of the wide-area measurement system (WAMS) is proposed. Here, the main idea is to break down the barrier between the power grid domain and the communication domain, and consider the impact of one when design the other. The PMU placement in the power grid domain takes into account the cost of communication links by generating multiple solutions with equally minimum PMU costs for communication link placement evaluation. On the other hand, the communication link placement problem reduces the cost by customizing the routing policies based on the different roles of PMUs in grid observability. The proposed WAMS design is capable of withstanding any single component failure in the power domain (PMU failure or power branch failure) or in the communication domain (communication link failure or PDC failure). Numerical study on the IEEE 57-bus system reveals that the developed cross-domain optimization framework can significantly reduce the overall installation cost of WAMS while attaining multi-domain resiliency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Optimal self-healing strategy for microgrid islanding

Renewable resource based microgrids provide reliable and cost-effective electricity with low carbon emissions. The flexibility of operating in grid-connected or islanded modes enables a microgrid to serve loads reliably. In the case of unexpected events happening to the main grid, the microgrid will isolate itself and operate in islanded mode to prevent any adversary impacts. The availability of renewable generation in the microgrid has significant impacts on the islanding strategy and different scenarios need to be considered. This study proposes a comprehensive microgrid self-healing strategy under different circumstances. The proposed strategy encompasses generation re-dispatch, network reconfiguration, and load shedding. The microgrid self-healing problem is formulated as a mixed-integer quadratic programming problem, which provides a globally optimal solution to facilitate smooth islanding of the microgrid. A modified Consortium for Electric Reliability Technology Solutions microgrid is used to conduct simulation under various scenarios. The simulation results demonstrate the efficiency of the proposed self-healing strategy in minimising costs of load shedding and generation with optimal switching actions.

optimal self-healing strategy↗

Numerical grid generation and flow simulation in SSME thrust chamber

The development of liquid and solid rocket engines for future space projects demands a detailed optimization process for highly efficient performance and cost reasons. Also, testing of full size engines may not be feasible when the large size requires test facilities which are cost prohibitive or if vacuum operation cannot be acquired. For such situations only scaling from small test scale measurements or accurate analytical predictions will provide the performance prior to actually flying the mission. A rigorous approach for simulating the combustion processes in liquid rocket engines by employing a direct solution of Navier-Stokes equations within the entire volume of the thrust chambers is presented. This method is illustrated in the solution of reactive flow in the Space Shuttle Main Engine (SSME) thrust chamber. The objective is to review recent improvements in the mathematical model and to present the grid generation methodology suitable for rocket thrust chamber geometries.

Gross, K. W.↗

Performance of 8 × 8 × 32 and 10 × 10 × 32 mm 3 CdZnTe position-sensitive virtual Frisch-grid detectors for high-energy gamma ray cameras

CdZnTe (CZT) crystals with thicknesses up to 20 mm and diameters up to 75 mm have become available from Redlen Technologies, Inc. for making large-volume gamma-ray detectors. The modified growth and optimized annealing conditions allowed Redlen to minimize the dark current and improve the uniformity of CZT crystals. Two detector designs, pixelated (H3D) and position-sensitive virtual Frisch-grid (VFG), have greatly benefitted from the availability of such big crystals. Encouraging results from testing of 40×40×15 mm 3 pixelated detectors were recently reported by the University of Michigan. In this work, we evaluated the spectroscopic properties of 8×8×32 and 10×10×32 mm 3 crystals configured as position-sensitive VFG detectors. Both digitized waveforms and an analog ASIC were used to read and process the signals from the detectors and test their spectral- and spatial-resolution. The VFG design provides the flexibility to scale-up the dimensions of the detectors for the desired efficiency, while the position information allows for correcting the detectors' response non-uniformity caused by crystal defects and devices geometry, thereby reducing the instrument cost and making them more feasible for emerging applications in gamma-ray astronomy, nonproliferation, portal screening and nuclear safeguards, where large detector arrays are often required.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗