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At least 343 records · Page 19

Series FACTS Devices for Increasing Resiliency in Severe Weather Conditions

Severe weather conditions are low-probability, high-impact events that affect grid operations. The majority of power outages are caused by severe weather conditions. Grid resiliency to weather events can be enhanced by decreasing the reliance on its affected sections. One way to do this is to reduce the power flow through lines vulnerable to severe weather. If a line is disconnected, its initial power flow is distributed through the neighbor lines, which may cause congestion in the grid. FACTS devices can be used to control the power flow of lines that have a higher chance of power outages. Most previous works do not consider weather events in power flow control. In this work, a linearized optimal power flow (OPF)–based algorithm is developed to minimize the real power flow of vulnerable lines considering the thermal limits of lines to prevent infeasible solutions; the simulation is fast, making it suitable for large-scale systems. The proposed optimization problem is presented as a mixed-integer linear program (MILP), making it capable of using short-term load forecasting due to its high solution speed. The proposed optimization problem considers multiple lines with different outage probabilities and the uncertainties of the weather forecast. Moreover, it estimates the power reduction in vulnerable lines due to changes in the series FACTS devices. The performance of the proposed optimization problem is tested on IEEE 14-, 30-, and 118-bus systems for several scenarios. The results are validated with the AC power flow results from MATPOWER.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Load altering attack-tolerant defense strategy for load frequency control system

Cyber attacks are emerging threats to every information-oriented energy management system. By violating the cyber systems, the hacker can disrupt the security and stability due to the strong coupling between the cyber and physical facilities. In this paper, one type of cyber attacks designated as the load altering attack is studied for the power system frequency control, and corresponding defense strategies are proposed to improve the frequency control performance. Considering the difficulty of the application of model-based controller into large-scale power systems, a novel model-free defense framework is for the first time presented. Under this framework, both active defense and passive defense strategies are designed. The former assumes that the defender has the initiative to learn different attack scenarios. Adaptive defense strategies are implemented using the online attack identification information and off-line trained strategy pool. The latter assumes that the defender passively tolerates various attack scenarios via the pre-trained off-line strategy. Both approaches prove to be effective through validation based on the IEEE benchmark systems. The proposed defense framework and defense strategies can be extended to other energy control systems to enhance their attack tolerance capability.

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GPU cache management based on locality type detection

Wavefront loading in a processor is managed and includes monitoring a selected wavefront of a set of wavefronts. Reuse of memory access requests for the selected wavefront is counted. A cache hit rate in one or more caches of the processor is determined based on the counted reuse. Based on the cache hit rate, subsequent memory requests of other wavefronts of the set of wavefronts are modified by including a type of reuse of cache lines in requests to the caches. In the caches, storage of data in the caches is based on the type of reuse indicated by the subsequent memory access requests. Reused cache lines are protected by preventing cache line contents from being replaced by another cache line for a duration of processing the set of wavefronts. Caches are bypassed when streaming access requests are made.

Zhang, Xianwei↗

Optimal D-FACTS Placement in Moving Target Defense Against False Data Injection Attacks

Moving target defense (MTD) is a defense strategy to detect stealthy false data injection (FDI) attacks against the power system state estimation using distributed flexible AC transmission system (D-FACTS) devices. However, existing studies neglect to address a fundamental yet critical issue, i.e., the D-FACTS placement, by assuming that all lines are equipped with D-FACTS devices. Here, to tackle this problem, we first derive analytical necessary conditions and requirements on the D-FACTS placement for a complete MTD. Further, we propose sufficient conditions using a graph theory-based topology analysis to ensure that the MTD under the proposed D-FACTS placement has the maximum rank of its composite matrix, which is indicative of the MTD effectiveness. Based on the analytical conditions, we design D-FACTS placement algorithms by using the minimum number of D-FACTS devices to achieve the maximum MTD effectiveness. A novel MTD-based ACOPF model, in which the reactance of D-FACTS lines is introduced as decision variables, is proposed to find a trade-off between the system loss and the MTD effectiveness. Numerical results on 6-bus, IEEE 14-bus, and IEEE 118-bus systems show the efficacy of MTDs using the proposed D-FACTS placement algorithms in maximizing the composite matrix rank and detecting FDI attacks.

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Regulatory Mechanisms to Enable Investments in Electric Utility Resilience

In 2019, Sandia National Laboratories contracted Synapse Energy Economics (Synapse) to research the integration of community and electric utility resilience investment planning as part of the Designing Resilient Communities: A Consequence-Based Approach for Grid Investment (DRC) project. Synapse produced a series of reports to explore the challenges and opportunities in several key areas, including benefit-cost analysis, performance metrics, microgrids, and regulatory mechanisms to promote investments in electric system resilience. This report focuses on regulatory mechanisms to improve resilience. Regulatory mechanisms that improve resilience are approaches that electric utility regulators can use to align utility, customer, and third-party investments with regulatory, ratepayer, community, and other important stakeholder interests and priorities for resilience. Cost-of-service regulation may fail to provide utilities with adequate guidance or incentives regarding community priorities for infrastructure hardening and disaster recovery. The application of other types of regulatory mechanisms to resilience investments can help. This report: characterizes regulatory objective as they apply to resilience; identifies several regulatory mechanisms that are used or can be adapted to improve the resilience of the electric system--including performance-based regulation, integrated planning, tariffs and programs to leverage private investment, alternative lines of business for utilities, enhanced cost recovery, and securitization; provides a case study of each regulatory mechanism; summarizes findings across the case studies; and suggests how these regulatory mechanisms might be improved and applied to resilience moving forward. In this report, we assess the effectiveness of a range of utility regulatory mechanisms at evaluating and prioritizing utility investments in grid resilience. First, we characterize regulatory objectives which underly all regulatory mechanisms. We then describe seven types of regulatory mechanisms that can be used to improve resilience--including performance-based regulation, integrated planning, tariffs and programs to leverage private investment, alternative lines of business for utilities, enhanced cost recovery, and securitization--and provide a case study for each one. We summarize our findings on the extent to which these regulatory mechanisms have supported resilience to date. We conclude with suggestions on how these regulatory mechanisms might be improved and applied to resilience moving forward.

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Physics-Based Feature Extraction from Bulk Time-Series PMU Datasets for Event Detection

In this work, two physics-based feature extraction techniques are developed for bulk time-series phasor measurement unit (PMU) datasets collected from the field to train the machine learning model for anomaly detection. Two approaches have been developed to extract useful features for different types of events. An admittance-based feature extraction technique is developed to detect events that involve line outages and system topology variations. The developed algorithm extracts the system equivalent admittance variation. Additionally, Fielder’s Theory is utilized to further reduce the potential computation burden by sectionalizing large-scale grids and datasets into smaller areas. Second, an oscillation-based feature extraction technique is developed to detect low-frequency oscillations in power grids. The dominant oscillation modes in the grids are extracted using energy-sorted Prony analysis. The extracted dominant oscillation modes by the developed work exhibit a high fitting resolution. Finally, the developed techniques have been validated using large-scale and real-world datasets.

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Identifying synoptic controls on boundary layer thermodynamic and cloud properties in a regional forecast model

Although most of our understanding of boundary layer cloudiness is based on idealized, subtropical, barotropic marine environments, boundary layer clouds exist across a range of conditions. In this study, we use the Naval Research Laboratory's Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) and an automated cold-front-relative analysis framework to explore the boundary layer structure associated with low clouds across a transect through the cold front of a midlatitude synoptic cyclone. The model credibly captures boundary layer structure in line with conceptual models of midlatitude cyclones and ground-based observations at Graciosa Island in the Azores. The warm sector is conditionally unstable, with clouds that are too shallow and with too little liquid water, compared to cloud property retrievals from satellite and surface-based instruments. The cold-frontal region exhibits convection associated with weak stability and ascent. Northwest of the cold front, the boundary layer is well mixed, deeper, and capped by a strong inversion maintained by large-scale subsidence. Simulated clouds in frontal and post-frontal regions are mostly too thick, with too much liquid water and too little cloud base drizzle. The post-frontal clouds are associated with grid-scale updrafts, which appear to be the model's attempt to represent mesoscale organization of cellular convection typically observed in the cold sector of midlatitude cyclones. The deep, well-mixed post-frontal boundary layers and cloudiness are maintained by strong surface fluxes, as in cold air outbreaks. Our analysis framework serves as a unique approach to model verification, and our results offer insights into differences in boundary layer cloud behavior between subtropical and synoptic cold-sector regimes.

Eissner, Jordan M. [Univ. of Kansas, Lawrence, KS ↗

Detecting and Characterizing Mg ii Absorption in DESI Survey Validation Quasar Spectra

Abstract We present findings of the detection of Magnesium II (Mg ii , λ = 2796, 2803 Å) absorbers from the early data release of the Dark Energy Spectroscopic Instrument (DESI). DESI is projected to obtain spectroscopy of approximately 3 million quasars (QSOs), of which over 99% are anticipated to be at redshifts greater than z > 0.3, such that DESI would be able to observe an associated or intervening Mg ii absorber illuminated by the background QSO. We have developed an autonomous supplementary spectral pipeline that detects these systems through an initial line-fitting process and then confirms the line properties using a Markov Chain Monte Carlo sampler. Based upon a visual inspection of the resulting systems, we estimate that this sample has a purity greater than 99%. We have also investigated the completeness of our sample in regard to both the signal-to-noise properties of the input spectra and the rest-frame equivalent width ( W 0 ) of the absorber systems. From a parent catalog containing 83,207 quasars, we detect a total of 23,921 Mg ii absorption systems following a series of quality cuts. Extrapolating from this occurrence rate of 28.8% implies a catalog at the completion of the five-year DESI survey that will contain over eight hundred thousand Mg ii absorbers. The cataloging of these systems will enable significant further research because they carry information regarding circumgalactic medium environments, the distribution of intervening galaxies, and the growth of metallicity across the redshift range 0.3 ≤ z < 2.5.

79 ASTRONOMY AND ASTROPHYSICS↗

Detecting Magnetic Fields in Exoplanets with Spectropolarimetry of the Helium Line at 1083 nm

The magnetic fields of the solar system’s planets provide valuable insights into their interiors and can have dramatic consequences for the evolution of their atmospheres and interaction with the solar wind. However, we have little direct knowledge of magnetic fields in exoplanets. Here we present a method for detecting magnetic fields in the atmospheres of close-in exoplanets based on spectropolarimetric transit observations at the wavelength of the helium line at 1083 nm. This methodology has been successfully applied for exploring magnetic fields in solar coronal filaments. Strong absorption signatures (transit depths on the order of a few percent) in the 1083 nm line have recently been observed for several close-in exoplanets. We show that in the conditions in these escaping atmospheres, metastable helium atoms should be optically pumped by the starlight and, for field strengths more than a few × 10 -4 G, should align with the magnetic field. This results in linearly polarized absorption at 1083 nm that traces the field direction (the Hanle effect), which we explore by both analytic computation and the HAZEL numerical code. The linear polarization $\sqrt{{Q}^{2}+{U}^{2}}/I$ ranges from ~10 -3 in optimistic cases down to a few × 10 -5 for particularly unfavorable cases, with very weak dependence on field strength. The line-of-sight component of the field results in a slight circular polarization (the Zeeman effect), also reaching $V/I\sim \mathrm{few}\times {10}^{-5}({B}_{\parallel }/10\,{\rm{G}})$. We discuss the detectability of these signals with current (SPIRou) and future (Extremely Large Telescope) high-resolution infrared spectropolarimeters, and we briefly comment on possible sources of astrophysical contamination.

79 ASTRONOMY AND ASTROPHYSICS↗

Non-contact based measurement of thin film coatings using eddy current measurements

When a time varying magnetic field attempts to penetrate a conductive surface, the surface will respond to that time varying field by the generation of circular currents around the flux lines. This effect is described by Faraday’s law of induction. An eddy current based measurement system attempts to discern the power loss incurred by these circulating currents within the conductive surface. The measurement system described here uses an Agilent E 4980A LCR meter to quantify the reaction of the film to the high frequency magnetic field lines which are forced into the film. The measurement metric is the meter’s interpretation of the power dissipation caused by the measured film. The meter is setup to use the Ls/Rs inductor model, and is run at 1 Mhz to bring the losses within the film as high as possible for sensitivity.

43 PARTICLE ACCELERATORS↗

Astrometric gravitational-wave detection via stellar interferometry

Here, we evaluate the potential for gravitational-wave (GW) detection in the frequency band from 10 nHz to 1 μ Hz using extremely high-precision astrometry of a small number of stars. In particular, we argue that nonmagnetic, photometrically stable, hot white dwarfs (WD) located at ~kpc distances may be optimal targets for this approach. Previous studies of astrometric GW detection have focused on the potential for less precise surveys of large numbers of stars; our work provides an alternative optimization approach to this problem. Interesting GW sources in this band are expected at characteristic strains around h c ~10 -17 × (μHz/ $f$ GW ). The astrometric angular precision required to see these sources is Δθ~h c after integrating for a time T~1/$f$GW. We show that jitter in the photometric center of WD of this type due to starspots is bounded to be small enough to permit this high-precision, small-N approach. We discuss possible noise arising from stellar reflex motion induced by orbiting objects and show how it can be mitigated. The only plausible technology able to achieve the requisite astrometric precision is a space-based stellar interferometer. Such a future mission with few-meter-scale collecting dishes and baselines of $\mathscr{O}$(100 km ) is sufficient to achieve the target precision. This collector size is broadly in line with the collectors proposed for some formation-flown, space-based astrometer or optical synthetic-aperture imaging-array concepts proposed for other science reasons. The proposed baseline is however somewhat larger than the km-scale baselines discussed for those concepts, but we see no fundamental technical obstacle to utilizing such baselines. A mission of this type thus also holds the promise of being one of the few ways to access interesting GW sources in this band.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Isotope ratio-based quantification of carbon assimilation highlights the role of plastidial isoprenoid precursor availability in photosynthesis

Abstract Background We report a method to estimate carbon assimilation based on isotope ratio-mass spectrometry (IRMS) of 13 CO 2 labeled plant tissue. Photosynthetic carbon assimilation is the principal experimental observable which integrates important aspects of primary plant metabolism. It is traditionally measured through gas exchange. Despite its centrality in plant research, gas exchange performs poorly with rosette growth habits typical of Arabidopsis thaliana , mutant lines with limited biomass, and accounts poorly for leaf shading. Results IRMS-based carbon assimilation values from plants labeled at different light intensities were compared to those obtained by gas exchange, and the two methods yielded similar values. Using this method, we observed a strong correlation between 13 C content and labeling time (R 2 = 0.999) for 158 wild-type plants labeled for 6 to 42 min. Plants cultivated under different light regimes showed a linear response with respect to carbon assimilation, varying from 7.38 nmol 13 C mg −1 leaf tissue min −1 at 80 PAR to 19.27 nmol 13 C mg −1 leaf tissue min −1 at 500 PAR. We applied this method to examine the link between inhibition of the 2 C -methyl- d -erythritol-4-phosphate (MEP) pathway and suppression of photosynthesis. A significant decrease in carbon assimilation was observed when metabolic activity in the MEP pathway was compromised by mutation or herbicides targeting the MEP pathway. Mutants affected in MEP pathway genes 1-DEOXY- d -XYLULOSE 5-PHOSPHATE SYNTHASE (DXS) or 1-HYDROXY-2-METHYL-2-(E)-BUTENYL 4-DIPHOSPHATE SYNTHASE (HDS) showed assimilation rates 36% and 61% lower than wild type. Similarly, wild type plants treated with the MEP pathway inhibitors clomazone or fosmidomycin showed reductions of 52% and 43%, respectively, while inhibition of the analogous mevalonic acid pathway, which supplies the same isoprenoid intermediates in the cytosol, did not, suggesting inhibition of photosynthesis was specific to disruption of the MEP pathway. Conclusions This method provides an alternative to gas exchange that offers several advantages: resilience to differences in leaf overlap, measurements based on tissue mass rather than leaf surface area, and compatibility with mutant Arabidopsis lines which are not amenable to gas exchange measurements due to low biomass and limited leaf surface area. It is suitable for screening large numbers of replicates simultaneously as well as post-hoc analysis of previously labeled plant tissue and is complementary to downstream detection of isotopic label in targeted metabolite pools.

2C‑methyl‑d‑erythritol 4‑phosphate pathway↗

Carbonate Management to Enable Energy- and Carbon-Efficient CO 2 Electrolysis (Final Technical Report)

The rapid growth and plummeting cost of solar energy have spurred growing interest in using CO 2 electrolysis to produce chemicals and fuels as an alternative to conventional petrochemical processes. High-temperature (>800 °C) solid oxide electrolyzers that convert CO 2 into CO and O 2 have recently become commercially available. Low-temperature electrolysis cells offer the prospect of more convenient and flexible operation, which is critical for utilizing intermittent solar energy, and provide access to more valuable C 2+ products such as ethylene, ethanol, and propanol. Over the past 10 years, research in this area has yielded substantial progress in both fundamental understanding of the requisite electrocatalytic reactions and design of prototype devices. Leveraging insights from fuel cells and membrane water electrolyzers, researchers have developed electrolysis cells with gas diffusion electrodes (GDE) that have demonstrated high CO 2 electrolysis current densities (>100 mA cm –2 ) as well as promising selectivity and stability. Despite these advances, the energy efficiency (electrical energy-to-product) and carbon efficiency (CO 2 -to-product) of low-temperature CO 2 electrolysis remain far too low for large-scale deployment. A preponderance of evidence indicates that the principal source of efficiency losses is the rapid and thermodynamically favorable reaction of CO 2 with hydroxide (OH – ) to form carbonate (CO 3 2– ). Carbonate formation imposes steady-state electrolysis conditions that result in large voltage and CO 2 losses for all known (photo)electrochemical CO 2 cells. While much current research remains focused on CO 2 reduction catalyst design, this largely overlooked CO 3 2– problem presents a fundamental scientific barrier to creating a viable electrochemical option for converting solar energy into chemicals and fuels. The project pursues an integrated, multi-PI research effort that establishes a fundamental science of CO 3 2– management. PI Kanan and Co-PI Mani’s contribution to the project is to evaluate strategies to mitigate the CO 3 2– problem by changing the properties of the electrolyte and the environment in which CO 2 reduction catalysis takes place. Experimental studies showed that electrolytes composed of a high concentration of both CO 3 2– and HCO 3 – , which serve as moderately alkaline buffers, improved the cell voltage by compared to all-HCO 3 – electrolytes, but these buffered systems still show substantial CO 2 uptake that reduces pH over time. Computational studies developed a homogenized model of a CO 2 reduction catalyst layer that permits a low-cost exploration of the high-dimensional parameter space associated with catalyst layers on gas diffusion electrodes. The model was validated by accurately reproducing experimental data for the related but simpler reaction of CO reduction and then used to probe the effects of catalyst layer architecture on CO 2 reduction. Minimizing the size of catalyst and hydrophobic domains in the catalyst layer is predicted to mitigate CO 3 2– formation and thereby enable prolonged operation at elevated pH. In support of the CO 2 electrolysis studies, a new method for rapidly prototyping electrochemical cells was developed and validated. The method uses a combination of 3D printing and electroless plating to generate conductive cell components for evaluating new cell designs. The carbonate problem encompasses mass transport processes and acid-base reactions that are relevant to many other electrochemical systems. Investigation of strategies to address the carbonate problem led to an additional line of inquiry into the physicochemical phenomena that determine the efficiency of electrochemical acid-base production, which has numerous applications in the broader field of carbon management. New strategies for using the supporting electrolyte to inhibit H + /OH – recombination in electrochemical acid-base production were evaluated, leading to the development of a novel acid-base producing system that eliminates the need for ion exchange membranes and exhibits promising efficiency and current densities for scalable applications.

25 ENERGY STORAGE↗

Development of Scalable Coastal and Offshore Macroalgal Farming

The US DOE/ARPA-E MARINER program funded a four-year project to determine an optimal way to grow kelps in large, nearshore and offshore arrays for the eventual purpose of biofuel production with the goal of keeping the cost below $\$$80 USD per dry metric ton of kelp. This project specifically looked at how Saccharina latissima can be grown in the Gulf of Alaska to reach that goal. There were three major aspects of the research: 1) optimizing nursery production and seeding lines for outplanting, 2) designing an economical, modular outplanting structure and 3) developing methods to efficiently harvest the product. Farm designs were based on catenary structures and the use of spreader bars with variable spacing of grow lines and line types. The spacing of the grow lines makes a difference in the yield. Grow line spacing of ≥1.5m showed about a 50% increase in kg/m. There was no statistical difference in the growth of Saccharina latissima whether in the middle or the outside of the array, but the line type and perhaps line thickness can make a difference in yield. Sagging caused by the weight of the mature fronds resulted in lower growth at depth. Various harvesting approaches for mature kelps were tested by collaborating farmers. One promising innovation is the use of large bags for holding the freshly harvested fronds. Although the weight of the fronds on the growlines causes the lines to sink, the bags packed with the harvested fronds float, allowing for easy loading to the transfer vessel. Another advance in harvesting is a specially built harvest vessel, the Harvest Buddy, allowing a more mechanized and faster way to harvest. A significant aspect of this project was the TTO/T2M. Several different outreach activities were performed by the Alaska Fisheries Development Foundation and GreenWave. A techno-economic assessment (TEA) using our data has pointed to solutions to reach the $\$$80 goal. A second phase of this project involved the co-culture of two different species of kelps. Interest in farming kelps has grown beyond using kelp for food, feed or biofuels. There is considerable interest in generating biomass from seaweed for use in bioplastics and other products that would substitute for petroleum-derived products. For these uses to be viable, large amounts of biomass are needed. Very large kelp farms can be expensive to build and maintain, leading to the need to optimize the biomass per unit area. Although close spacing of growlines can lead to poor growth, a viable approach may be to grow two species of kelps together: one that hangs down and one that is buoyant, growing up. This system would increase the spacing in three dimensions. In Alaska, Saccharina latissima is commonly grown hanging down from longlines. One of the buoyant Alaskan kelps is Nereocystis luetkeana. Because there are commercial uses for wild-harvested Nereocystis in Alaska, we undertook a preliminary trial in Kodiak, Alaska that grew both Saccharina and Nereocystis in the same longline array. Closely spaced lines were seeded the first week of February 2023 and set at 3m below the surface. The arrays were harvested in late June 2023. Despite having 45% fewer grow-lines, the total yield of the Nereocystis on the combined arrays was statistically similar to the Nereocystis only arrays. Total yields were greatest on the combined arrays, followed by the Nereocystis only and Saccharina only arrays. These results may have significance for large scale macroalgal production.

09 BIOMASS FUELS↗

Effect of Accurate Modeling of Converter Interfaced Generation (CIG) on a Practical Bulk Power System

With increased penetration of converter interfaced generation (CIG) in power systems, it becomes imperative to adequately model them in both steady-state and dynamic simulations. There are several modeling approaches and simulation platforms for CIG. In addition, it is noted that suitability of modeling approaches and models is also dependent on the system conditions. However, their suitability has yet to be systematically analyzed, and this becomes a challenge in the industry without a systemic method. To tackle these challenges, in this paper, we first develop a methodology for identifying the maximum penetration of aggregated rooftop sources that can be represented as negative loads in both the steady state and dynamic analysis. Then we verify the suitability of positive-sequence performance-based model and detailed electromagnetic transient (EMT) model for utility-scale PV plants under different fault conditions. Based on the results, we perform dynamic simulations on a large practical system with both positive-sequence transient stability(TS) and EMT-TS hybrid simulation. Our study shows that positive-sequence performance based PV plant model is more suitable for study cases with faults relatively far away from the point of connection, and that positive-sequence models and TS simulation approach can produce comparable results with reference to EMT-TS hybrid simulation for normally-cleared single-line-to-ground faults, but the inadequacy of positive-sequence based model and simulation approach becomes obvious for prolonged-tripping of unbalanced faults in proximity of the PV plants.

Huang, Qiuhua↗

An extrapolation method to remove spurious stress concentration in micromechanical analyses of composites using pixel-based meshes

It is easier to generate a finite element mesh of complicated geometries with voxel-based meshes compared to conformal meshes. However, the local stresses in voxel-based meshes are higher owing to artificial stress concentration caused due to jagged lines that approximate a curve. Here, we propose a method that accounts for this anomaly which would lead to accurate prediction of maximum von Mises stress in voxel-based meshes. The method is based on the variation of reciprocal of stresses and associated numerical gradient. The prediction of the proposed method is compared against the results of a conformal mesh by considering four two-dimensional example problems. The accuracy of the proposed method is verified using different mesh densities, material properties, and integration schemes. The proposed method was also implemented on a conformal mesh to verify that it filters out just the spurious stress concentration and not the realistic stress concentration.

36 MATERIALS SCIENCE↗

Game Theory Approaches for System-level Incentive Design

This report presents a generalized Stackelberg game framework for designing and evaluating financial incentives that enhance power system resilience through strategic deployment of distributed energy resources(DERs) under various contingencies. The proposed approach addresses the challenge of coordinating individual community investment decisions to meet system-wide resilience objectives. The framework is demonstrated in a three-community test system subjected to two transmission contingency scenarios: inter-community line failure (Case 1) and complete main grid disconnection (Case 2). In both cases, three incentive levels are compared: a Base case with no financial incentives, and low and high incentive cases. In Case 1, the Base case (no incentives) results in a total installed DER capacity of 217.2 MW, with no load shedding due to alternative routing, but community costs remain high. Increasing incentives raises DER deployment to 286.9 MW, lowers aggregate community costs by $22M annually, and completely avoids the need for costly new transmission line construction. In Case 2, the Base case results in 24.3 MWh of unserved load; introducing incentives eliminates all load shedding and ensures up to 89 MWh of battery storage is available for emergency reserve. These results demonstrate that targeted incentives can dramatically improve grid resilience and cost-effectiveness. The framework thus offers policymakers and system planners a robust tool to quantify and compare the effectiveness of incentive programs for multi-community transmission networks behavior, system resilience, and economic efficiency.

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