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At least 253 records · Page 14

Iron-based amorphous alloys and methods of synthesizing iron-based amorphous alloys

A method according to one embodiment includes combining an amorphous iron-based alloy and at least one metal selected from a group consisting of molybdenum, chromium, tungsten, boron, gadolinium, nickel phosphorous, yttrium, and alloys thereof to form a mixture, wherein the at least one metal is present in the mixture from about 5 atomic percent (at %) to about 55 at %; and ball milling the mixture at least until an amorphous alloy of the iron-based alloy and the at least one metal is formed. Several amorphous iron-based metal alloys are also presented, including corrosion-resistant amorphous iron-based metal alloys and radiation-shielding amorphous iron-based metal alloys.

36 MATERIALS SCIENCE↗

Use of Satellite, Surface Observations and Numerical Weather Prediction Model Data to Improve Cloud Base Height and Cloud Base Vertical Velocity Estimation

Cloud base height (CBH) and cloud base vertical velocity (CBVV) are important variables that impact the overall climate in a region as they influence the formulation, longevity, and evolution of clouds. Retrieval of both parameters have long used ground instrumentation (e.g., Doppler lidar (DL), ground base radar); however, retrieving CBH from satellites is particularly challenging given that space-based instruments only observe cloud tops. In this manuscript, CBH is retrieved using a multi-linear regression equation, while CBVV used a random forests model. Both retrievals combine satellite and numerical weather prediction data. The satellite data used are the Visible Infrared Imaging Radiometer Suite imagery, while measurements of CBH and CBVV include DL and radiosonde data at the Southern Great Plains (SGP) Atmospheric Radiation Measurement observatory. Data from 83 summer days (May-August) in 2018–2021 featuring cumulus clouds forced by solar heating were examined and used to train the models, with years 2022–2023 used for validation. Various spatial domains were defined with one large (2.4° longitude by 2.0° latitude) SGP domain being split into smaller sections (smallest being 0.99° and 0.61° longitude and latitude respectably). CBH and CBVV values obtained from the DL as compared to the models show root mean square errors between 150 and 200 m, with CBVV values between 0.45 and 1 ms -1 . Finally, it was found that the CBH formulation performs well over all domains, while the CBVV retrievals become less accurate due to more turbulence being introduced into the observations as the number of DL stations decreases in the smaller domains.

54 ENVIRONMENTAL SCIENCES↗

A Reversed Impedance-Based Stability Criterion for IBR Grids

The existing impedance-based stability criterion is effective for analyzing local control interactions; however, it is difficult to scale the existing criterion to analyze wide-area control interactions among numerous IBRs through a complex power system network. The scaled version of the existing criterion requires the impedance response of each IBR in the system as well as of the network looking from all the IBRs. It is quite challenging to obtain all these impedance responses because of the computational effort and the requirement of separately scanning the impedance of the network and the IBRs. We propose a reversed criterion for the impedance-based stability analysis to address these problems. In contrast to the existing criterion, the reversed criterion analyzes the stability of a power system when an IBR is disconnected from the system. The reversed criterion estimates the impact of an IBR on the frequency and damping of power system oscillation modes using the impedance scans of only the IBR and the grid at its terminal. It can be sequentially applied at different IBRs to evaluate their impact on the power system stability. In addition to scalability, the reversed criterion gives flexibility to focus only on a few selected IBRs, depending on their rating, the magnitude of oscillations observed at their terminals, and the vendor support available for implementing stabilizing control system updates. The reversed criterion is demonstrated on a 14-bus power system with 100% IBRs.

control interactions↗

Integrated Agent-Based and Production Cost Modeling Framework for Renewable Energy Studies

The agent-based framework for renewable energy studies (ARES) is an integrated approach that adds an agent-based model of industry actors to PLEXOS and combines the strengths of the two to overcome their individual shortcomings. It can examine existing and novel wholesale electricity markets under high penetrations of renewables. ARES is demonstrated by studying how increasing levels of wind will impact the operations and the exercise of market power of generation companies that exploit an economic withholding strategy. The analysis is carried out on a test system that represents the Electric Reliability Council of Texas energy-only market in the year 2020. The results more realistically reproduce the operations of an energy market under different and increasing penetrations of wind, and ARES can be extended to address pressing issues in current and future wholesale electricity markets.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Feature-Based Analysis of Plasma-Based Particle Acceleration Data

Plasma-based particle accelerators can produce and sustain thousands of times stronger acceleration fields than conventional particle accelerators, providing a potential solution to the problem of the growing size and cost of conventional particle accelerators. To facilitate scientific knowledge discovery from the ever growing collections of accelerator simulation data generated by accelerator physicists to investigate next-generation plasma-based particle accelerator designs, we describe a novel approach for automatic detection and classification of particle beams and beam substructures due to temporal differences in the acceleration process, here called acceleration features. The automatic feature detection in combination with a novel visualization tool for fast, intuitive, query-based exploration of acceleration features enables an effective top-down data exploration process, starting from a high-level, feature-based view down to the level of individual particles. We describe the application of our analysis in practice to analyze simulations of single pulse and dual and triple colliding pulse accelerator designs, and to study the formation and evolution of particle beams, to compare substructures of a beam and to investigate transverse particle loss.

43 PARTICLE ACCELERATORS↗

Comparison of Wind Farm Layout Optimization Results Using a Simple Wake Model and Gradient-Based Optimization to Large-Eddy Simulations: Preprint

Comparison of wind farm layout optimization results with simulations or wind tunnel tests is important because the models used during optimization use simplifying assumptions that can alter the design space. Some of the characteristics of the simple models may negatively influence the resulting layouts. In this paper we perform wind farm layout optimization and compare the resulting improvements to large eddy simulation (LES) results. We begin by describing the models used, including changes specific for use with gradient-based optimization. We then compare our version of the models with the original versions and large eddy simulation LES) data from previous publications. Using the models described, we performed gradient-based wind farm layout optimization, using exact gradients, and compare the results to LES simulations. The models predicted an improvement in annual energy production (AEP) of 7.4%, while the LES reported an AEP improvement of 9:9%. We conclude that the improvements found by optimizing with the simple models are not just an artifact of the models, but are real improvements.

17 WIND ENERGY↗

Application of the new IAPWS Guideline on the fast and accurate calculation of steam and water properties with the Spline-Based Table Look-Up Method (SBTL) in RELAP-7

The numerical simulation of thermalhydraulic processes in nuclear power plants requires very accurate and extremely fast algorithms for calculating the thermophysical properties of water and steam. In order to provide such algorithms, the International Association for the Properties of Water and Steam (IAPWS) has adopted the new “IAPWS Guideline on the Fast Calculation of Steam and Water Properties with the Spline-Based Table Look-Up Method (SBTL)”. In this article, the SBTL method is applied to property functions of specific volume and specific internal energy (v,e) based on the scientific formulation IAPWS-95 and the latest IAPWS formulations for transport properties. From the newly generated SBTL functions, thermodynamic and transport properties as well as their derivatives and inverse functions are calculable in the fluid range of state for pressures up to 100 MPa and for temperatures up to 1273 K, including the metastable liquid and the metastable vapor regions. The SBTL functions reproduce the underlying formulations with an accuracy of 10–100 ppm and significantly reduced computing times. The SBTL method has been implemented into the nuclear reactor system safety analysis code RELAP-7 [2] to consider the real fluid behavior of water and steam in a novel 7-equation two-phase flow model.

42 ENGINEERING↗

Enabling Renewable Energy While Protecting Wildlife: An Ecological Risk-Based Approach to Wind Energy Development Using Ecosystem-Based Management Values

Acceptance of wind energy development is challenged by stakeholders’ concerns about potential effects on the environment, specifically on wildlife, such as birds, bats, and (for offshore wind) marine animals, and the habitats that support them. Communities near wind energy developments are also concerned with social and economic impacts, as well as impacts on aesthetics, historical sites, and recreation and tourism. Lack of a systematic, widely accepted, and balanced approach for measuring the potential damage to wildlife, habitats, and communities continues to leave wind developers, regulators, and other stakeholders in an uncertain position. This paper explores ecological risk-based management (RBM) in wind energy development for land-based and offshore wind installations. This paper provides a framework for the adaptation of ecosystem-based management to wind energy development and examines that framework through a series of case studies and best management practices for applying risk-based principles to wind energy. Ten case studies indicate that wind farm monitoring is often driven by regulatory requirements that may not be underpinned by scientific questions. While each case applies principles of adaptive management, there is room for improvement in applying scientific principles to the data collection and analysis. Challenges and constraints for wind farm development to meet RBM framework criteria include collecting sufficient baseline and monitoring data year-round, engaging stakeholder facilitators, and bringing together large and diverse scientific teams. The RBM framework approach may provide insights for improved siting and consenting/permitting processes for regulators and their advisors, particularly in those nations where wind energy is still in the early development stages on land or at sea.

17 WIND ENERGY↗

Bismuth-Based Perovskite-Inspired Solar Cells: In Situ Diagnostics Reveal Similarities and Differences in the Film Formation of Bismuth- and Lead-Based Films

Organic–inorganic lead-based halide perovskite compounds currently yield thin film solar cells with a power conversion efficiency (PCE) of >23%. However, replacing the lead with less-toxic elements while maintaining a high PCE remains a challenge. For this reason, there has been significant effort to develop Pb-free compounds, including methylammonium bismuth iodide (MA 3 Bi 2 I 9 ), but such systems severely underperform when compared with the prototypical Pb-based methylammonium lead iodide (MAPbI 3 ). For the latter, it is known that lead complexes with polar solvents, such as dimethyl sulfoxide (DMSO) and dimethylformamide (DMF), to form iodoplumbates which can co-crystallize into solvated phases. Herein, the solidification and growth behaviors of Bi- and Pb-based films is investigated using multi-probe in situ characterization methods. It is shown that the Bi-based compound crystallizes directly and rapidly into a textured polycrystalline microstructure from a precursor solution without evolving through intermediate crystalline solvated phases, in contrast to MAPbI 3 . This solidification process produces isolated crystals and challenges the growth of continuous and crystalline films required for solar cells. Further, it is revealed that solvent engineering with antisolvent dripping is crucial to enable the formation of continuous polycrystalline films of MA 3 Bi 2 I 9 and functional solar cells thereof.

36 MATERIALS SCIENCE↗

Equation-based object-oriented modeling and simulation of data center cooling systems

In this paper, we introduce a newly developed open source data center package in the Modelica Buildings library to support modeling and simulation of cooling and control systems of data centers. The data center package contains major thermal and control component models, such as Computer Room Air Handler, Computer Room Air Conditioner, models of different subsystem configurations such as chillers with differently configured waterside economizers, as well as templates for different systems. Two case studies based on this package are performed to investigate the performances of the cooling and electrical system under normal conditions and emergency situations such as a blackout: one is for a data center powered by conventional energy, and the other is for a data center powered by renewable energy. Simulation results show that the dynamic modeling and multi-domain simulation in the Modelica-based tool make it convenient for users to investigate both normal and emergent operations for conventional and renewable data centers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Assessment of Impacts of Dissolved Organic Matter and Dissolved Iron on the Performance of Amidoxime-Based Adsorbents for Seawater Uranium Extraction

Research on extraction of uranium from seawater has been active in recent years because this technology can provide an additional supply of uranium for nuclear fuel from a much larger uranium reservoir (the oceans) and the processes are more environment friendly. One critical challenge of the development of this technology is to make uranium adsorbents perform well not just in the oversimplified laboratory system (e.g. artificial seawater) but also in the complex real seawater matrix, which is comprised of many competing ions and natural organic substances. Here, we conducted a systematic study using a continuous-flow seawater flume system to assess the potential impacts of dissolved organic matter (DOM) and dissolved iron on the uranium uptake performance (including adsorbent reusability) of amidoxime-based adsorbents. In the 28-day exposure, the adsorbent exposed in dissolved Fe-spiked seawater (low DOM/high Fe) and humic acid-spiked seawater (high DOM/high Fe) showed lower uranium adsorption loadings (73% and 56% of adsorption loading, respectively) than the same adsorbent exposed in seawater without spiking (low DOM/low Fe). Interestingly, the uranium adsorption loading of the reused adsorbent (after uranium stripping by a mild bicarbonate elution) in the dissolved Fe-spiked seawater dropped substantially to only 24% of the loading in the unspiked clean seawater counterpart; while not much change was observed in the performance of adsorbent exposed to the humic acid-spiked seawater. From comparison of FTIR signatures of adsorbent before and after the seawater exposure, we found that the amidoxime ligands in the adsorbent exposed to dissolved Fe-spiked seawater had severer degradation than the adsorbents exposed to humic acid-spiked seawater and unspiked clean seawater. Notably, unlike the adsorbent exposed to dissolved Fe-spiked seawater, the adsorbent exposed to humic acid-spiked seawater didn’t adsorb elevated level of Fe compared to the adsorbent in the unspiked clean seawater. This suggests that the species of Fe in the humic acid-spiked seawater (primarily humic acid bound Fe) didn’t interact with amidoxime-based adsorbent; while the Fe species in the Fe-spiked seawater strongly interacted with adsorbent and caused significant degradation of amidoxime ligands. On the other hand, highly variable uranium adsorption loadings were observed in adsorbent in contact with humic acid-spiked seawater, but not in the adsorbents exposed to dissolved Fe-spiked seawater and seawater without spike. Our observations thus indicate that seawater receiving high inputs of DOM and dissolved Fe, such as coastal waters, is not ideal for efficient extraction of uranium.

Uranium, Seawater, amidoxime-based adsorbents, dis↗

An Efficient Copper-Based Redox Shuttle Bearing a Hexadentate Polypyridyl Ligand for DSCs under Low-Light Conditions

A Cu complex featuring a hexadentate ligand was synthesized and evaluated as a redox shuttle in dye-sensitized solar cell (DSC) devices, which exhibited excellent performance under low-light conditions. Cu-based redox shuttles (RSs) have been shown to perform remarkably well under low-light conditions; however, most of the known Cu-based RSs employ bidentate pyridyl ligands and often require bulky flanking groups adjacent to the nitrogen donors of these ligands to prevent distortion and binding of exogenous Lewis bases such as 4- tert -butylpyridine (TBP) that are added to enhance cell performance. Without the bulky substituents, the bidentate ligands are susceptible to ligand exchange with TBP. In this context, we have developed a Cu-based RS with a preorganized multidentate ligand designed to facilitate efficient electron transfer kinetics and high stability via the chelate effect. The Cu system, [Cu(bpyPY4)] 2+/+ , reported here is supported by the hexadentate polypyridyl ligand bpyPY4 (6,6'-bis(1,1-di(pyridine-2-yl)ethyl)-2,2'-bipyridine) and examined as a RS in DSCs. From X-ray crystallography and variable-temperature 1 H NMR studies, bpyPY4 provides a dynamic coordination environment around the metal center. Cyclic voltammetry and UV–visible and NMR spectroscopy indicate that noncoordinated pyridyl donors block binding of TBP to copper. DSC devices using [Cu(bpyPY4)] 2+/+ as the redox electrolyte gave a power conversion efficiency (PCE) value of 4.9% under 1 sun illumination (100 mW/cm 2 ). Strikingly, the device performance increased to 11.11% when irradiated with 2400 lux (0.5 mW/cm 2 ) via a fluorescent lamp light source and improved further to 15.2% PCE at 13500 lux (2.10 mW/cm 2 ). In conclusion, the Cu redox shuttle is an intriguing candidate for implementation with narrow band gap sensitizers with low oxidation potentials, which are important for high photocurrent DSC devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Participation Factor-Based Approach for Defining the EMT Model Boundary for Power System Simulations with Inverter-Based Resources

The increasing penetration of inverter-based resources (IBRs) introduces new challenges to power system simulations, particularly with the emergence of fast electromagnetic transient (EMT) dynamics and sub-synchronous oscillations (SSO) that require time-consuming EMT simulations. To reduce the time cost for simulating a large-scale power grid with IBRs, this paper proposes a novel participation factor-based approach for defining a critical zone for detailed EMT modeling and simulations, which includes the IBRs, synchronous generators, and the network components participating significantly in simulated contingencies. Both model-based and response-based methods are introduced for the estimation of participation factors (PFs). The case study on the 240-bus Western Electricity Coordinating Council (WECC) system demonstrates that the EMT zone determined by the proposed approach can effectively capture power system dynamics involving IBRs.

EMT simulation↗

Robust Stabilization of Inverter-Based Resources Using Virtual Resistance-Based Control

This letter proposes a virtual resistance-based nonlinear control to stabilize and robustify the current layer of inverter-based resources, subject to the grid voltage disturbances, and the grid parameter uncertainties. A class of virtual resistances is proposed and analyzed using concepts from dissipative systems theory. Moreover, specific nonlinear virtual resistance-based controllers are derived, with their corresponding performance analytically bounded. Here, the theoretical and simulation results show that the proposed nonlinear virtual resistance-based controllers significantly reduce the L 2 gain of the closed-loop error system to grid voltage variation and parametric uncertainties. Significant improvements of the transient and steady-state current responses are also demonstrated over linear virtual resistance counterparts.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Optimal Power System Black start using Inverter-Based Generation

Power system black start readiness is part of the system planning. Utility planners perform periodic studies to assess if their power system is capable of total restoration following a black out. Hydro and diesel generators are the most commonly used black start capable resources by power utilities. However, with increasing penetration of solar generation, inverter-based resources can be considered to provide black start capability. Since the solar inverters can be located at multiple locations throughout the power system, and in view of their unique characteristics, an optimal real-time capable plan is helpful for system operators for faster black start. Black start optimization is a multi stage mixed-integer non-linear optimization which is extremely hard to solve. In this paper, we propose an optimal black start methodology that is easier to solve and scalable in real-time. We demonstrate the proposed methodology on two test systems and illustrate how inverter-based resources can contribute and improve power system restoration.

power system restoration, blackstart, Inverter-bas↗

Decentralized Distribution System Restoration with Grid-Forming/Following Inverter-Based Resources

The high penetration of distributed energy resources (DERs) in active distribution systems has posed challenges to the centralized distribution system restoration (DSR) strategies in current practice. On the other hand, the advancement in smart inverter technologies enables the bottom-up restoration capability. This paper is motivated to develop a 3-layered hierarchical framework for decentralized DSR, based on the grid-forming (GFM) and grid-following (GFL) grid-edge inverters. The first layer presents the tertiary control, which determines the load pickup schedule and generation dispatch of DERs, using the alternating direction method of the multipliers algorithm. The second layer consists of two control functions: GFM control, which regulates voltage and frequency, establishing a stable grid for GFL inverters to follow; and GFL control, which regulates the real and reactive power. In the third layer, the primary control is proposed to regulate the inverter voltage and current, which is developed based on the virtual oscillator control (VOC). Furthermore, the developed framework is tested in the modified IEEE 13-node test feeder. Two scenarios of grid-connected and islanded operating modes are designed, and simulation results demonstrate the effectiveness of decentralized DSR strategies for controlling grid-edge inverters to enhance the distribution system resilience.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Outage Forecast-Based Preventative Scheduling Model for Distribution System Resilience Enhancement

Distribution system resilience enhancement is an important topic to ensure customers have access to power supply during extreme events. In fact, certain weather-related extreme events can be predicted ahead of time. Therefore, it is important to investigate how to predict grid outages using extreme weather forecasts, and how outage predictions can be incorporated into distribution system resilience enhancement. In this paper, a preventative scheduling model for distribution systems is proposed. The model targets at allocating resources, especially mobile responsive resources such as mobile backup generators and mobile energy storage systems, to prepare for an extreme event in the day-ahead context. To achieve efficient resource allocation and scheduling, a machine learning-based outage prediction module is developed to predict vulnerable or risky segments of the distribution system based on historical operating records and extreme weather event forecast. By integrating the outage prediction results into the scheduling model, optimal resource allocation can be derived to help distribution systems prepare for an upcoming event and improve resilience performance. A real distribution feeder in North Carolina, U.S. is used in the case study to validate the proposed approach.

distributed energy resources↗