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At least 721 records · Page 40

Getting brighter: Impacts of improved day-ahead solar forecasts in high-solar, high-storage electricity systems

This paper analyzes the impacts of improved day-ahead solar forecasts on costs and dispatch in the solar-rich Southeast U.S. It uses an optimized high-solar, high-storage resource portfolio in which solar generation capacity accounts for 45 % of total installed capacity (34 %–36 % of generation) and energy storage capacity (43 GW) is equivalent to 33 % of peak demand. In a base scenario, improved day-ahead solar forecasts reduce production costs by $\$87$ million per year ($\$0.13$ per MWh load, $2023$$). This level of savings is within the range or lower than earlier studies of solar forecast improvements at lower levels of solar generation (<25 % of total generation). In this study, solar expansion was accompanied by two important sources of flexibility for managing solar forecast error: energy storage and day-ahead solar curtailment. Furthermore, the analysis finds that regional coordination complements day-ahead solar forecast improvements while natural gas commitment flexibility is a substitute for forecast improvements, as the improved solar forecast leads to sub-optimal commitment of thermal units. Day-ahead solar forecast improvements reduce reserves required to manage forecast error by 30 %. Fewer reserves to manage large, infrequent solar forecast errors could be an important benefit of improved solar forecasts.

14 SOLAR ENERGY↗

Optimizing fictitious states for Bell inequality violation in bipartite qubit systems with applications to the t t ¯ system

There is a significant interest in testing quantum entanglement and Bell inequality violation in high-energy experiments. Since the analyses in high-energy experiments are performed with events statistically averaged over phase space, the states used to determine observables depend on the choice of coordinates through an event-dependent basis and are thus not genuine quantum states, but rather “fictitious states.” We find that the basis which diagonalizes the spin-spin correlations is optimal for constructing fictitious states to test the violation of Bell’s inequality. This result is applied directly to the bipartite qubit system of a top and antitop produced at a hadron collider. We show that the beam axis is the optimal basis choice near the t t ¯ threshold production for measuring Bell inequality violation, while at high transverse momentum the basis that aligns along the momentum direction of the top is optimal. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

Peak Load Management in Distribution Systems Using Legacy Utility Equipment and Distributed Energy Resources: Preprint

The ability to perform peak load management in distribution systems has several benefits for utilities, including reduced demand charges and improved reliability, efficiency, and utilization of the network infrastructure. This paper demonstrates the coordinated operation of an advanced distribution management system (ADMS) and a distributed energy resource management system (DERMS) to achieve peak load management using a realistic laboratory test bed. A commercial ADMS reduces the peak demand by reducing system voltages using a dynamic voltage regulation (DVR) application. A prototype DERMS—based on real-time optimal power flow—controls distributed battery energy storage systems to further reduce the feeder power. Results from the experiments conducted using a model of a real distribution feeder show that the coordinated operation of the ADMS and DERMS is effective in accomplishing peak load management.

61 RADIATION PROTECTION AND DOSIMETRY↗

Multibody for Everybody (M4E): A Symbolic Dynamics Modeling Tool with Applications in Simulation, Control, and Optimization

Developing the analytical model of a multibody system is often the initial step in control and optimization. The analytical model (equations of motion) describes a system’s time evolution under specified forcing conditions. Although developing these equations is easy for simple systems, this process becomes more complex for systems composed of multiple bodies. Deriving equations of motion for complex multibody systems requires specialized expertise in multibody dynamics, is time-consuming, and is susceptible to error. To address this issue, this paper presents an open-source, easy-to-use, systematic framework to derive symbolic equations of motion in both Python and MATLAB using the joint coordinate formulation. This formulation results in a set of ordinary differential equations that use the minimum set of coordinates needed to model a system. The symbolic representation provides better insight into the influence of design parameters on system performance, facilitates sensitivity analysis and parameter studies, and supports direct implementation of control and optimization routines. The tool enables numerical simulation for specified parameter sets, is modular for straightforward integration with other tools and libraries, and allows incorporation of hydrodynamics, mooring, and other external forces. The result is a reproducible, extensible pipeline for modeling, simulation, and design of complex multibody systems. The proposed tool is versatile and can be applied to domains such as robotics, control, and design. In addition, we integrated external libraries that provide capabilities for modeling offshore systems such as underwater robots and marine energy converters.

16 TIDAL AND WAVE POWER↗

Nitrogen-Coordinated Single Cobalt Atom Catalysts for Oxygen Reduction in Proton Exchange Membrane Fuel Cells

Due to the Fenton reaction, the presence of Fe and peroxide in electrodes generates free radicals causing serious degradation of the organic ionomer and the membrane. Pt-free and Fe-free cathode catalysts therefore are urgently needed for durable and inexpensive proton exchange membrane fuel cells (PEMFCs). Herein, a high-performance nitrogen-coordinated single Co atom catalyst is derived from Co-doped metal-organic frameworks (MOFs) through a one-step thermal activation. Aberration-corrected electron micros-copy combined with X-ray absorption spectroscopy virtually verifies the CoN4 coordination at an atomic level in the catalysts. Through investigating effects of Co doping contents and thermal activation temperature, an atomically Co site dispersed catalyst with optimal chemical and structural properties has achieved respectable activity and stability for the oxygen reduction reaction (ORR) in challenging acidic media (e.g., half-wave potential of 0.80 V vs reversible hydrogen electrode (RHE). The performance is comparable to Fe-based catalysts and 60 mV lower than Pt/C -60 µg Pt cm-2). Fuel cell tests confirm that catalyst activity and stability can translate to high-performance cathodes in PEMFCs. The remarkably enhanced ORR performance is attrib-uted to the presence of well-dispersed CoN4 active sites embedded in 3D porous MOF-derived carbon particles, omitting any inactive Co aggregates.

Wang, Xiao X.↗

Peak Load Management in Distribution Systems Using Legacy Utility Equipment and Distributed Energy Resources

The ability to perform peak load management in distribution systems has several benefits for utilities, including reduced demand charges and improved reliability, efficiency, and utilization of the network infrastructure. This paper demonstrates the coordinated operation of an advanced distribution management system (ADMS) and a distributed energy resource management system (DERMS) to achieve peak load management using a realistic laboratory test bed. A commercial ADMS reduces the peak demand by reducing system voltages using a dynamic voltage regulation (DVR) application. A prototype DERMS-based on real-time optimal power flow-controls distributed battery energy storage systems to further reduce the feeder power. Results from the experiments conducted using a model of a real distribution feeder show that the coordinated operation of the ADMS and DERMS is effective in accomplishing peak load management.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Different binding modes of Cu and Pb vs. Cd, Ni, and Zn with the trihydroxamate siderophore desferrioxamine B at seawater ionic strength

The solution speciation in seawater of divalent trace metals (Cd, Cu, Ni, Pb, Zn) is dominated by strong, ostensibly metal-specific organic ligands that may play important roles in microbial metal acquisition and/or detoxification processes. We compare the effective stabilities of these metal-organic complexes to the stabilities of their complexes with a model siderophore, desferrioxamine B (DFOB). While metal-DFOB complexation has been studied in various dilute but often moderately coordinating media, for the purpose of this investigation we measured the stability constants in a non-coordinating background electrolyte at seawater ionic strength (0.7 M NaClO4). Potentiometric titrations of single metals (M) were performed in the presence of ligand (L) at different M:L molar ratios, whereupon the stability constants of multiple complexes were simultaneously determined by non-linear regression of the titration curves with FITEQL, using the optimal binding mode for each metal. Cadmium, Ni, and Zn, like trivalent Fe, sequentially form a bi-, tetra-, and hexadentate complex with DFOB as pH increases, consistent with their coordination number of 6 and regular octahedral geometry. Copper has a Jahn-Teller-distorted square-bipyramidal geometry whereas the geometry of Pb is cryptic, involving a range of bond lengths. Supported by a thermodynamic argument, our data suggest that this impedes binding of the third hydroxamate group and that the hexadentate Cu-DFOB and Pb-DFOB complex identified in earlier reports may instead be a deprotonated tetradentate complex. Absence of the hexadentate complex promotes the formation of a dinuclear (bidentate-tetradentate) complex, M2HL2+, albeit not for Pb in 0.7 M NaCl, evidently due to extensive complexation with chloride. Stabilities of the hexadentate Ni-DFOB, Zn-DFOB, and the tetradentate Pb-DFOB complex are nearly equal, yet about 2 orders of magnitude higher and 4 orders of magnitude lower than those of the hexadentate Cd-DFOB and tetradentate Cu-DFOB complex, respectively. Linear free-energy relations defined by the rare earth elements are able to predict stabilities of the Cd, Zn, and one of the Pb complexes, but underestimate those of the Ni and Cu complexes. The comparison with metal-specific organic ligands detected in seawater yields fair agreement for three of the five metals, implying that they could be siderophore-like. The Cd- and Ni-specific ligands are much stronger and may contain quite different functional groups. Calculations with MINEQL incorporating our new stability constants indicate that very high DFOB concentrations would be required to match the extent of metal-organic complexation observed in seawater, however DFOB may well represent a much broader class of structurally related ligands.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Trajectory Optimization via Unsupervised Probabilistic Learning On Manifolds

This report investigates the use of unsupervised probabilistic learning techniques for the analysis of hypersonic trajectories. The algorithm first extracts the intrinsic structure in the data via a diffusion map approach. Using the diffusion coordinates on the graph of training samples, the probabilistic framework augments the original data with samples that are statistically consistent with the original set. The augmented samples are then used to construct conditional statistics that are ultimately assembled in a path-planing algorithm. In this framework the controls are determined stage by stage during the flight to adapt to changing mission objectives in real-time. A 3DOF model was employed to generate optimal hypersonic trajectories that comprise the training datasets. The diffusion map algorithm identfied that data resides on manifolds of much lower dimensionality compared to the high-dimensional state space that describes each trajectory. In addition to the path-planing worflow we also propose an algorithm that utilizes the diffusion map coordinates along the manifold to label and possibly remove outlier samples from the training data. This algorithm can be used to both identify edge cases for further analysis as well as to remove them from the training set to create a more robust set of samples to be used for the path-planing process.

42 ENGINEERING↗

Large-scale optimal control of interconnected natural gas and electrical transmission systems

We present a detailed optimal control model that captures spatiotemporal interactions between gas and electric transmission networks. We use the model to study flexibility and economic opportunities provided by coordination. A large-scale case study in the Illinois system reveals that coordination can enable the delivery of significantly larger amounts of natural gas to the power grid. In particular, under a coordinated setting, gas-fired generators act as distributed demand response resources that can be controlled by the gas pipeline operator. This enables more efficient control of pressures and flows in space and time and overcomes delivery bottlenecks. We demonstrate that the additional flexibility not only can benefit the gas operator but can also lead to more efficient power grid operations and results in increased revenue for gas-fired power plants. We also use the optimal control model to analyze computational issues arising in these complex models. We demonstrate that the interconnected Illinois system with full physical resolution gives rise to a highly nonlinear optimal control problem with 4400 differential and algebraic equations and 1040 controls that can be solved with a state-of-the-art sparse optimization solver. (C) 2016 Elsevier Ltd. All rights reserved.

Chiang, Nai-Yuan↗

Bidding strategy for microgrid in day-ahead market based on hybrid stochastic/robust optimization

In this paper, we propose an optimal bidding strategy in the day-ahead market of a microgrid consisting of intermittent distributed generation (DG), storage, dispatchable DG and price responsive loads. The microgrid coordinates the energy consumption or production of its components and trades electricity in both the day-ahead and real-time markets to minimize its operating cost as a single entity. The bidding problem is challenging due to a variety of uncertainties, including power output of intermittent DG, load variation, day-ahead and real-time market prices. A hybrid stochastic/robust optimization model is proposed to minimize the expected net cost, i.e., expected total cost of operation minus total benefit of demand. This formulation can be solved by mixed integer linear programming. The uncertain output of intermittent DG and day-ahead market price are modeled via scenarios based on forecast results, while a robust optimization is proposed to limit the unbalanced power in real-time market taking account of the uncertainty of real-time market price. Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, a micro-turbine, a diesel generator, a battery and a responsive load show the advantage of stochastic optimization in addition to robust optimization.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Quantum optimal control pathways of ozone isomerization dynamics subject to competing dissociation: A two-state one-dimensional model

We construct a two-state one-dimensional reaction-path model for ozone open → cyclic isomerization dynamics. The model is based on the intrinsic reaction coordinate connecting the cyclic and open isomers with the O{sub 2} + O asymptote on the ground-state {sup 1}A{sup ′} potential energy surface obtained with the high-level ab initio method. Using this two-state model time-dependent wave packet optimal control simulations are carried out. Two possible pathways are identified along with their respective band-limited optimal control fields; for pathway 1 the wave packet initially associated with the open isomer is first pumped into a shallow well on the excited electronic state potential curve and then driven back to the ground electronic state to form the cyclic isomer, whereas for pathway 2 the corresponding wave packet is excited directly to the primary well of the excited state potential curve. The simulations reveal that the optimal field for pathway 1 produces a final yield of nearly 100% with substantially smaller intensity than that obtained in a previous study [Y. Kurosaki, M. Artamonov, T.-S. Ho, and H. Rabitz, J. Chem. Phys. 131, 044306 (2009)] using a single-state one-dimensional model. Pathway 2, due to its strong coupling to the dissociation channel, is less effective than pathway 1. The simulations also show that nonlinear field effects due to molecular polarizability and hyperpolarizability are small for pathway 1 but could become significant for pathway 2 because much higher field intensity is involved in the latter. The results suggest that a practical control may be feasible with the aid of a few lowly excited electronic states for ozone isomerization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Strain-Induced asymmetry and on-site dynamics of silicon defects in graphene

In the last decade, the atomically-focused electron beams utilized in scanning transmission electron microscopes (STEMs) have been shown to induce a broad set of local structural transformations in materials, opening pathways for directing material synthesis and modification atom-by-atom. The mechanisms underlying these transformations remain largely unknown, due to the intractability of modeling the myriad of reaction pathways that can be accessed through high-energy electron scattering. The information on materials’ structure and dynamics that can be extracted from STEM images is similarly left underexplored. Here, we report the observation of anomalous on-site dynamics of individual silicon impurity atoms in graphene during STEM imaging. Density functional theory-based structural optimizations of anisotropically-strained molecular nanographenes reveal two distinct (but nearly degenerate) stable structures for four-fold coordinated silicon impurities, where interconversion between the two structures manifests slight changes of the silicon position within the lattice site. Implications for defect-based strain engineering in graphene are discussed.

36 MATERIALS SCIENCE↗

The state of the art for neutron irradiation experiments from the perspective of the High Flux Isotope Reactor (HFIR)

Irradiation experiment campaigns are critical to advancing nuclear energy technologies by providing data on material performance under relevant radiation conditions. Successful irradiation experiments require integrated design efforts that balance technical goals with facility constraints. Here, this paper presents an expert-informed overview of irradiation experiment design at the High Flux Isotope Reactor. It addresses the nuclear materials research and irradiation experiment communities to guide them toward developing technically sound, facility-compatible campaigns. The High Flux Isotope Reactor is a multipurpose reactor supporting isotope production, neutron scattering, and materials testing. Its high, steady-state neutron flux is ideal for irradiation experiments, but successful execution demands coordinated thermal, structural, and reactor physics analyses. The paper outlines the complete development workflow from concept definition and design optimization to safety qualification and post-irradiation examination. Standardized capsule platforms are also discussed in terms of flexibility, specimen capacity, and thermal performance. Common failure modes such as unanticipated geometric variations, can impact temperature-dose profiles and compromise data reliability. Therefore, detailed thermal modeling and accurate as-built characterization are essential for meaningful post-irradiation data interpretation. Key recommendations include early engagement all stakeholders, clearly defined design expectations, and alignment of specimen geometries with post-irradiation examination capabilities. This approach reduces design iterations, enhances data quality, and supports more efficient use of irradiation resources. Strategic and well-planned irradiation testing not only improves individual campaign success but also accelerates the deployment of advanced nuclear technologies. By closing critical data gaps and reducing development risks, the nuclear materials community can more effectively contribute to the future of clean, resilient energy systems.

Experiments↗

Zeolitic Imidazole Framework Decorated Substrates for Lead Removal From Water

Lead contamination in water supplies necessitates efficient and mechanistically understood removal strategies. Zeolitic imidazole frameworks (ZIFs) are promising adsorbents; however, ZIF-67 (Co-based) is more susceptible to hydrolysis than its zinc analogue ZIF-8, raising questions about stability during metal uptake. In this study, we systematically compare ZIF-8 and ZIF-67 under controlled pH conditions and evaluate how substrate anchoring influences hydrolytic stability and Pb 2+ adsorption behavior. By integrating adsorption capacity measurements, kinetic analysis, metal-node leaching data, and structural characterization, we distinguish ion exchange from framework degradation and clarify the temporal interplay between adsorption and hydrolysis. Although ZIF-67 exhibits greater hydrolytic sensitivity, coordination with phosphoryl-bearing Mucor hiemalis membranes significantly reduces Co 2+ leaching and enhances structural retention. Under the optimized conditions (pH 5), ZIF-67@Mucor achieves a maximum Pb 2+ adsorption capacity of 867 mg g −1 . These findings demonstrate that substrate-dependent stabilization enables controlled exploitation of ZIF reactivity for aqueous metal remediation.

Adsorption↗

Incorporating energy storage and user experience in isolated microgrid dispatch using a multi-objective model

In order to coordinate multiple different scheduling objectives from the perspectives of economy, environment, and users, a practical multi-objective dynamic optimal dispatch model incorporating energy storage and user experience is proposed for isolated microgrids. In this model, besides microturbine units, energy storage is employed to provide spinning reserve services for microgirds; and furthermore, from the perspective of demand side management, a consumer satisfaction indicator is developed to measure the quality of user experience. A two-step solution methodology incorporating multi-objective optimisation and decision analysis is put forward to address this model. First, a powerful heuristic optimisation algorithm, called the -dominance based evolutionary algorithm, is used to find a well-distributed set of Pareto-optimal solutions of the problem. Thereby, the best compromise solutions are identified from the entire solutions with the use of decision analysis by integrating fuzzy C-means clustering and grey relation projection. The simulation results on the modified Oak Ridge National Laboratory Distributed Energy Control and Communication lab microgrid test system demonstrate the effectiveness of the proposed approach.

Li, Yang↗

Structure of the 2, 4′-dihydroxyacetophenone dioxygenase from Alcaligenes sp. 4HAP

The first X-ray structure of a 2, 4′-dihydroxyacetophenone dioxygenase from Alcaligenes sp. 4HAP at a resolution of 2.2 Å is reported. This structure establishes that the enzyme adopts the cupin-fold, forming compact dimers with a pronounced hydrophobic interface between the monomers. Each monomer possesses a catalytic ferrous iron that is coordinated by three histidines (76, 78 and 114) and an additional ligand which has been putatively assigned as a carbonate, although formate and acetate are possibilities. The enzyme 2, 4′-dihydroxyacetophenone dioxygenase (DAD) catalyses the conversion of 2, 4′-dihydroxyacetophenone to 4-hydroxybenzoic acid and formic acid with the incorporation of molecular oxygen. Whilst the vast majority of dioxygenases cleave within the aromatic ring of the substrate, DAD is very unusual in that it is involved in C—C bond cleavage in a substituent of the aromatic ring. There is evidence that the enzyme is a homotetramer of 20.3 kDa subunits, each containing nonhaem iron, and its sequence suggests that it belongs to the cupin family of dioxygenases. In this paper, the first X-ray structure of a DAD enzyme from the Gram-negative bacterium Alcaligenes sp. 4HAP is reported, at a resolution of 2.2 Å. The structure establishes that the enzyme adopts a cupin fold, forming dimers with a pronounced hydrophobic interface between the monomers. The catalytic iron is coordinated by three histidine residues (76, 78 and 114) within a buried active-site cavity. The iron also appears to be tightly coordinated by an additional ligand which was putatively assigned as a carbonate dianion since this fits the electron density optimally, although it might also be the product formate. The modelled carbonate is located in a position which is highly likely to be occupied by the α-hydroxyketone group of the bound substrate during catalysis. Modelling of a substrate molecule in this position indicates that it will interact with many conserved amino acids in the predominantly hydrophobic active-site pocket where it undergoes peroxide radical-mediated heterolysis.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Python STXM Control (pystxmcontrol) v0.1

The software is a complete solution for controlling scanning microscopes. It provides a low level interface to device hardware via drivers, communication and coordination layers for managing scan execution and data acquisition, a graphical interface and scripting interface for user interaction. With optimized hardware drivers and low software overhead this software is 10 times faster than the legacy software it is replacing.

Shapiro, David [Lawrence Berkeley National Laborat↗