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At least 829 records · Page 46

An Alternative Timing and Synchronization Approach for Situational Awareness and Predictive Analytics

Accurate and synchronized timing information is required by power system operators for controlling the grid infrastructure (relays, Phasor Measurement Units (PMUs), etc.) and determining asset positions. Satellite-based global positioning system (GPS) is the primary source of timing information. However, GPS disruptions today (both intentional and unintentional) can significantly compromise the reliability and security of our electric grids. A robust alternate source for accurate timing is critical to serve both as a deterrent against malicious attacks and as a redundant system in enhancing the resilience against extreme events that could disrupt the GPS network. To achieve this, we rely on the highly accurate, terrestrial atomic clock-based network for alternative timing and synchronization. In this paper, we discuss an experimental setup for an alternative timing approach. The data obtained from this experimental setup is continuously monitored and analyzed using various time deviation metrics. We also use these metrics to compute deviations of our clock with respect to the National Institute of Standards and Technologys (NIST) GPS data. The results obtained from these metric computations are elaborately discussed. Finally, we discuss the integration of the procedures involved, like real-time data ingestion, metric computation, and result visualization, in a novel microservices-based architecture for situational awareness.

Chinthavali, Supriya↗

Steady-State Analysis of Microgrid Distributed Control Under Denial of Service Attacks

Distributed control is an effective method to coordinate multiple components in a microgrid. It usually has mandatory requirements for communication graph topology; changing the topology unexpectedly could disrupt the operation of a distributed controller. A denial of service (DoS) attack blocks communication channels to cause variations in communication graph. Unforeseen topology changes render a controller to receive incomplete system information. Control decisions made based on incorrect information can lead to significantly reduced grid supporting capability. As a result, the vital power balance between generation and load may be challenged. Determining power balance requires steady-state power flow analysis; however, the cyber-induced steady-state analysis is not well studied in the literature. Here, in this article, we show that a cyber–physical microgrid with unknown DoS attacks has augmented uncertain power flow equations, whose special structure creates new computational issue to determining power balance. To deal with the issue, we develop a novel cyber-induced microgrid model: the cyber–physical system is transformed into a pure physical model, where the disruption effects of DoS in the cyber layer are shown to be equivalent to the variations of the physical model parameters. With the transformed system, we develop a sufficient condition to ascertain the system power balance under unknown DoS attacks. In addition, practical insights for resilient distributed control design are shown as well.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Enhancing Distribution Grid Resilience Through Model Predictive Controller Enabled Prioritized Load Restoration Strategy

Effective resilience improvement strategies enable the power grid to cope with disruptive extreme events. Most power grid outages are caused by disruptions in distribution grids. Motivated by the urgent need for power system resilience research, this paper proposes a priority-weighted optimal load restoration technique to enhance the resilience of distribution grids against extreme events. The proposed technique is based on smart distribution technology and framed as sequential multi-step decision process (MDP) and mixed integer linear program (MILP). It is formulated as optimal control problem with a model predictive control (MPC) approach. We applied the devised MILP-MPC-based load restoration technique to a simplified single-bus version of the IEEE 13-bus distribution system with integrated distributed energy resources (DERs) such as wind turbine, photovoitaic array, microturbine, and energy storage device. The technique executes a reducing and rolling horizon optimization in each control step in real-time using the forecasted information of the renewables, the fuel status of the microturbine and the state of charge of the energy storage device. We consider an extreme event which triggered outage of the upstream utility grid and caused islanded operation of the distribution grid. We demonstrated the effectiveness of the proposed MPC approach in restoring the distribution grid loads based on their priority during the main grid outage-caused islanded operation.

61 RADIATION PROTECTION AND DOSIMETRY↗

Improved microgrid resiliency through distributionally robust optimization under a policy-mode framework

Critical energy infrastructure are constantly under stress due to the ever increasing disruptions caused by wildfires, hurricanes, other weather related extreme events and cyber-attacks. Hence it becomes important to make critical infrastructure resilient to threats from such cyber-physical events. However, such events are hard to predict and numerous in nature and type and it becomes infeasible to make a system resilient to every possible such cyber-physical event. Such an approach can make the system operation overly conservative and impractical to operate. Furthermore, distributions of such events are hard to predict and historical data available on such events can be very sparse, making the problem even harder to solve. To deal with these issues, in this paper we present a policy-mode framework that enumerates and predicts the probability of various cyber-physical events and then a distributionally robust optimization (DRO) formulation that is robust to the sparsity of the available historical data. The proposed algorithm is illustrated on an islanded microgrid example: a modified IEEE 123-node feeder with distributed energy resources (DERs) and energy storage. Simulations are carried to validate the resiliency metrics under the sampled disruption events.

Nazir, Mohammad Nawaf↗

Cloud-based Testbed for Adaptive Under-Frequency Load Shedding with High DER Penetration

Increasing penetration of distributed energy resources and behind-the-meter renewables may soon disrupt the efficacy of critical protection schemes, such as under-frequency load shedding (UFLS). Improved data exchange and coordination across the transmission-distribution boundary will be required to maintain reliability of bulk electric system. Standards-based data integration platforms using agreed-upon semantic vocabularies, such as the Common Information Model, will be key to enabling adaptive protection schemes requiring synthesized data from both the bulk power system and behind-the-meter resources. This paper introduces a cloud-based open-source data integration environment and UFLS clustering algorithm being developed to enable adaptive relay coordination between transmission and distribution utilities in the state of Vermont.

Anderson, Alexander A.↗

A Sequential Model Predictive and Deep Reinforcement Learning-Based Controller for Distribution System Outage Mitigation under Hurricane Events

This paper proposes a proactive outage mitigation framework for power distribution networks to withstand hurricane-induced disruptions. It leverages Model Predictive Control (MPC) to identify safe lines for proactive switching during hurricanes, minimizing the risk of cascading failures and voltage violations. The switching strategies optimized by MPC are sequentially integrated with a Deep Reinforcement Learning agent using the Advantage Actor-Critic algorithm, enabling dynamic line switching to maximize connected buses and minimize voltage violations in real time. Using a probabilistic hurricane model, the framework predicts line failures and adapts to varying conditions to enhance grid resilience. Simulations on the IEEE 123-bus system demonstrate its effectiveness in maintaining high connectivity and minimizing disruptions. Real-time testing with an RTDS confirms the practicality and reliability of the proposed approach.

Selim, Alaa [University of Connecticut]↗

A Power Outage Data Informed Resilience Assessment Framework

Catastrophic impacts to power systems due to disruptive events have increased significantly during the last decade. These events highlight the need to develop approaches to assess the resilience of power systems against extreme events. However, the availability of data that capture power system performance during and after disruptive events is scarce. This paper proposes an assessment framework to evaluate the performance aspects of the grid system during extreme outage events using the Environment for Analysis of Geo-Located Energy Information (EAGLE-I) data. EAGLE-I includes information related to the number of impacted customers, duration, and location of power outages in the United States. Statistical analyses were conducted to extract resilient-based outage data and derive probability distribution functions of their impact and recovery characteristics. A list of extreme events is identified based on few predetermined threshold values. Metrics from other power outage assessments were used to measure the characteristics of each event, including impact rate and duration, recovery rate and duration, and impact level. A probability distribution function is obtained for each metric. The obtained results provide a representation of national grid performance during extreme events, which can be applied as a framework to evaluate various resilience enhancement techniques.

EAGLE-I↗

Efficient Interdependent Systems Recovery Modeling with DeepONets

Modeling the recovery of interdependent critical infrastructure is a key component of quantifying and optimizing societal resilience to disruptive events. However, simulating the recovery of large-scale interdependent systems under random disruptive events is computationally expensive. Therefore, we propose the application of Deep Operator Networks (DeepONets) in this paper to accelerate the recovery modeling of interdependent systems. DeepONets are ML architectures which identify mathematical operators from data. The form of governing equations DeepONets identify and the governing equation of interdependent systems recovery model are similar. Therefore, we hypothesize that DeepONets can efficiently model the interdependent systems recovery with little training data. We applied DeepONets to a simple case of four interdependent systems with sixteen states. DeepONets, overall, performed satisfactorily in predicting the recovery of these interdependent systems for out of training sample data when compared to reference results.

97 MATHEMATICS AND COMPUTING↗

Electromagnetic Analysis of ITER Electron Cyclotron Emission Model

The ITER electron cyclotron emission (ECE) diagnostic system is located at diagnostics shielding module 2 (DSM2), equatorial port 9 (EP9), to measure electron temperature profile and electron temperature fluctuations, and also assess nonthermal electron distributions via the oblique view. Therefore, ECE has both radial and oblique views with two hot sources for calibration and two couples of mirrors for two different optical views. It shall receive that the large electromagnetic (EM) loads up to 100-MN/m3 force density due to the eddy currents on the copper mirrors generated by the short transient plasma disruption. The simplified EM analysis model using magnetic field ( B ) data and flux variations (dB/dt) method based on the worst case of plasma disruption, MD_DW_EXP16MS_CATIII, has been developed to calculate the force and moments for each ECE component and support structure for EP9 DSM2 Bay2 and Bay3. The B and dB/dt methods use the constant B and dB/dt assumed for each local bay space, but the real B and dB/dt are basically varied along the radial direction of each bay. The complex global model with the local ECE components and support structure using Maxwell transient has been developed to do EM analysis to compare the results of the B and dB/dt models. The volumetric EM force density of the whole ECE components and support structure can be used for the subsequent structural analysis. In conclusion, combined with the thermal and nuclear loads and seismic and initial loads, the ECE integration analysis can be finalized for the operation case.

Fang, J. [Princeton Plasma Physics Laboratory (PPP↗

Visualizing Comparisons of Bill of Materials

Protecting critical infrastructure from cyber attacks, natural disasters, and other disruptions is a priority of the U.S. Government. Critical infrastructure includes providing electricity to homes and businesses, supplying natural gas for heating, and producing renewable energy sources. A loss of these services, as seen in the Solarwinds supply chain attack in 2020 , Texas snowstorm of 2021, the Colonial Pipeline cyber incident of 2021, and the Washington power substation attacks in 2022 result in high costs to consumers, disruption of everyday life, and even death. To protect the infrastructure, we first have to know what equipment we are protecting. The complexity of distributed manufacturing and development coupled with the increasing prevalence of cyber and supply chain attacks necessitates a greater understanding of the hardware and software components that comprise equipment in critical infrastructure. When a vulnerability in a single software library can have disastrous consequences, it is vital to understand critical equipment and systems at a granular level. This need has led to increased energy around the development and incorporation of bill-of-materials (BOM) into existing asset management practices to aid in mitigating, and responding to future attacks \cite{noauthor_software_nodate}. While much of the current research is devoted to creating BOMs, it is equally important to develop methodologies for leveraging BOMs to answer questions, such as: How has my software changed? Are two pieces of equipment equivalent? Does this piece of equipment that just arrived match my historical information? In this work, we demonstrate how BOMs can be represented by graph structures. We then describe how these structures can be fed into a graph comparison algorithm to produce a novel interactive visualization that allows us to not only identify differences in BOMs, but show exactly where they are in the product.

Jones, Rebecca D.↗

Novel genetic tools improve Penicillium expansum patulin synthase production in Aspergillus niger

Since the first CRISPR (clustered regularly interspaced short palindromic repeats)‐Cas (CRISPR‐associated) system was developed for creating double‐stranded DNA breaks, it has been adapted and improved for different biotechnological applications. In this issue of The FEBS Journal , Arentshorst et al . developed a novel approach to enhance transgene expression of a specific protein, patulin synthase (PatE) from Penicillium expansum , in the important industrial filamentous fungus Aspergillus niger . Their technique involved the disruption of selected genes with counter‐effects on targeted protein production and simultaneous integration of glucoamylase landing sites into the disrupted gene locus such as protease regulator ( prtT ) in an ATP‐dependent DNA helicase II subunit 1 ( kusA or ku70 ) ‐ deletion strain. Multiple copies of the PatE transgene expression cassette were introduced by CRISPR‐Cas9‐mediated insertion. The purified PatE was further used for structural and functional studies, and the technique laid the foundation for elevating the overall production of various proteins or chemicals in those industrially important fungi.

59 BASIC BIOLOGICAL SCIENCES↗

Night shift schedule causes circadian dysregulation of DNA repair genes and elevated DNA damage in humans

Circadian disruption has been identified as a risk factor for health disorders such as obesity, cardiovascular disease, and cancer. Although epidemiological studies suggest an increased risk of various cancers associated with circadian misalignment due to night shift work, the underlying mechanisms have yet to be elucidated. Here, we sought to investigate the potential mechanistic role that circadian disruption of cancer hallmark pathway genes may play in the increased cancer risk in shift workers. In a controlled laboratory study, we investigated the circadian transcriptome of cancer hallmark pathway genes and associated biological pathways in circulating leukocytes obtained from healthy young adults during a 24‐hour constant routine protocol following 3 days of simulated day shift or night shift. The simulated night shift schedule significantly altered the normal circadian rhythmicity of genes involved in cancer hallmark pathways. A DNA repair pathway showed significant enrichment of rhythmic genes following the simulated day shift schedule, but not following the simulated night shift schedule. In functional assessments, we demonstrated that there was an increased sensitivity to both endogenous and exogenous sources of DNA damage after exposure to simulated night shift. Our results suggest that circadian dysregulation of DNA repair may increase DNA damage and potentiate elevated cancer risk in night shift workers.

circadian misalignment↗

Metabolomic Profiling of Wild-type and Mutant Soybean Root Nodules Using Laser-ablation Electrospray Ionization Mass Spectrometry Reveals Altered Metabolism

The establishment of the nitrogen-fixing symbiosis between soybean and Bradyrhizobium japonicum is complex. In order to document the changes in plant metabolism due to the symbiosis, we utilized laser ablation electrospray ionization mass spectrometry (LAESI-MS) for in situ metabolic profiling of wild-type nodules, nodules infected with a B. japonicum nifH mutant unable to fix nitrogen, nodules doubly infected by both strains, and nodules formed on plants mutated in the stearoyl-acyl carrier protein desaturase (sacpd-c) gene, which were previously shown to have altered nodule ultrastructure. Results showed that the relative abundance of fatty acids, purines, and lipids was significantly changed in response to the symbiosis. The nifH mutant nodules had elevated levels of jasmonic acid (JA), correlating with signs of nitrogen deprivation. Nodules resulting from the mixed inoculant displayed similar, overlapping metabolic distributions within the sectors of effective (fix+) and ineffective (nifH mutant, fix-) endosymbionts. These data are inconsistent with the notion that plant sanctioning is cell autonomous. Nodules lacking sacpd-c displayed an elevation of soyasaponins and organic acids in the central necrotic regions. This study demonstrates the utility of LAESI-MS for high-throughput screening of plant phenotypes. Overall, nodules disrupted in the symbiosis were elevated in metabolites related to plant defense.

Agtuca, Beverly J.↗

Tonoplast Sucrose Transporter SUT4-Dependent Sugar Partitioning Modulates Phenological Transitions and Reproductive Success in Poplar

Climate uncertainty is intensifying the need for greater plasticity in carbohydrate reserve utilization to support winter survival and spring growth in woody perennials. In poplar, the single-copy SUT4, which encodes a tonoplast-localized sucrose transporter, and the SUT5/SUT6 genome duplicates, which encode plasma membrane-localized transporters, are expressed year-round, with SUT4 showing the highest expression during cool seasons. Given its role in vacuolar sucrose efflux and winter-predominant expression, SUT4 may play a key role in modulating seasonal carbohydrate dynamics. While SUT4-knockdown and knockout effects have been studied under greenhouse conditions, their impact under field conditions remains unexplored. Here, we report a field-based study comparing CRISPR knockout mutants of winter-expressed SUT4 and SUT5/SUT6 in Populus tremula x alba. We show that sut4, but not sut5/6, mutants exhibited earlier autumn leaf senescence, delayed spring bud flush, reduced stem growth, and altered sugar partitioning in winter xylem and bark relative to controls. After 2 years in the field, all genotypes flowered before leaf flush in early spring; however, sut4 mutants produced sterile ovules despite developing normal-looking catkins. Metabolic profiling revealed disrupted sucrose and raffinose dynamics in elongating sut4 catkins. This was accompanied by transcriptomic signatures of elevated stress and downregulation of proanthocyanidin biosynthesis and circadian clock genes. These findings highlight the critical role of SUT4 in coordinating sugar allocation, stress responses, and seasonal development in poplar.

09 BIOMASS FUELS↗

Collagen Fibril Orientation in Tissue Specimens From Atherosclerotic Plaque Explored Using Small Angle X-Ray Scattering

Atherosclerotic plaques can gradually develop in certain arteries. Disruption of fibrous tissue in plaques can result in plaque rupture and thromboembolism, leading to heart attacks and strokes. Collagen fibrils are important tissue building blocks and tissue strength depends on how fibrils are oriented. Fibril orientation in plaque tissue may potentially influence vulnerability to disruption. While X-ray scattering has previously been used to characterize fibril orientations in soft tissues and bones, it has never been used for characterization of human atherosclerotic plaque tissue. This study served to explore fibril orientation in specimens from human plaques using small angle X-ray scattering (SAXS). Additionally, plaque tissue was extracted from human femoral and carotid arteries, and each tissue specimen contained a region of calcified material. Three-dimensional (3D) collagen fibril orientation was determined along scan lines that started away from and then extended toward a given calcification. Fibrils were found to be oriented mainly in the circumferential direction of the plaque tissue at the majority of locations away from calcifications. However, in a number of cases, the dominant fibril direction differed near a calcification, changing from circumferential to longitudinal or thickness (radial) directions. Further study is needed to elucidate how these fibril orientations may influence plaque tissue stress–strain behavior and vulnerability to rupture.

60 APPLIED LIFE SCIENCES↗

Evaluating the mineral commodity supply risk of the U.S. manufacturing sector

Trade tensions, resource nationalism, and various other factors are increasing concerns regarding the supply reliability of nonfuel mineral commodities. This is especially the case for commodities required for new and emerging technologies ranging from electric vehicles to wind turbines. In this analysis, we use a conventional risk-modeling framework to develop and apply a new methodology for assessing the supply risk to the U.S. manufacturing sector. Specifically, supply risk is defined as the confluence of three factors: the likelihood of a foreign supply disruption, the dependency of U.S. manufacturers on foreign supplies, and the ability of U.S. manufacturers to withstand a supply disruption. The methodology is applied to 52 commodities for the decade spanning 2007–2016. The results indicate that a subset of 23 commodities, including cobalt, niobium, rare earth elements, and tungsten, pose the greatest supply risk. This supply risk is dynamic, shifting with changes in global market conditions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Respiration is essential for aerobic growth of Zymomonas mobilis ZM4

ABSTRACT Zymomonas mobilis is an alpha-proteobacterium that is a promising platform for industrial scale production of biofuels due to its efficient ethanol fermentation and low biomass generation. Z. mobilis is aerotolerant and encodes a complete respiratory electron transport chain, but the benefit of respiration for growth in oxic conditions has never been confirmed, despite decades of research. Growth and ethanol production of wild-type Z. mobilis is poor in oxic conditions indicating that it does not benefit from oxidative phosphorylation. Additionally, in previous studies, aerobic growth improved significantly when respiratory genes were disrupted ( ndh ) or acquired point mutations ( cydA and cydB ), even if respiration was significantly reduced by these changes. Here, we obtained clean deletions of respiratory genes ndh and cydAB , individually and in combination, and showed, for the first time, that deletion of cydAB completely inhibited O 2 respiration and dramatically reduced growth in oxic conditions. Both respiration and aerobic growth were restored by expressing a heterologous, water-forming NADH oxidase, noxE . Oxygen can have many negative effects, including formation of reactive oxygen species (ROS) or directly inactivating oxygen sensitive enzymes. Our results suggest that the effect of molecular oxygen on enzymes had a greater negative impact on Z. mobilis than formation of ROS. This result shows that the main role of the electron transport chain in Z. mobilis is reducing the intracellular concentration of molecular oxygen, helping to explain why it is beneficial for Z. mobilis to use electron transport chain complexes that have little capacity to contribute to oxidative phosphorylation. IMPORTANCE A key to producing next-generation biofuels is to engineer microbes that efficiently convert non-food materials into drop-in fuels, and to engineer microbes effectively, we must understand their metabolism thoroughly. Zymomonas mobilis is a bacterium that is a promising candidate biofuel producer, but its metabolism remains poorly understood, especially its metabolism when exposed to oxygen. Although Z. mobilis respires with oxygen, its aerobic growth is poor, and disruption of genes related to respiration counterintuitively improves aerobic growth. This unusual result has sparked decades of research and debate regarding the function of respiration in Z. mobilis . Here, we used a new set of mutants to determine that respiration is essential for aerobic growth and likely protects the cells from damage caused by oxygen. We conclude that the respiratory pathway of Z. mobilis should not be deleted from chassis strains for industrial production because this would yield a strain that is intolerant of oxygen, which is more difficult to manage in industrial settings.

09 BIOMASS FUELS↗

Signal sequences target enzymes and structural proteins to bacterial microcompartments and are critical for microcompartment formation

ABSTRACT Spatial organization of pathway enzymes has emerged as a promising tool to address several challenges in metabolic engineering, such as flux imbalances and off-target product formation. Bacterial microcompartments (MCPs) are a spatial organization strategy used natively by many bacteria to encapsulate metabolic pathways that produce toxic, volatile intermediates. Several recent studies have focused on engineering MCPs to encapsulate heterologous pathways of interest, but how this engineering affects MCP assembly and function is poorly understood. In this study, we investigated the role of signal sequences, short domains that target proteins to the MCP core, in the assembly of 1,2-propanediol utilization (Pdu) MCPs. We characterized two novel Pdu signal sequences on the structural proteins PduM and PduB, which constitute the first report of metabolosome signal sequences on structural proteins rather than enzymes. We then explored the role of enzymatic and structural Pdu signal sequences on MCP assembly by deleting their encoding sequences from the genome alone and in combination. Deleting enzymatic signal sequences decreased the MCP formation, but this defect could be recovered in some cases by overexpressing genes encoding the knocked-out signal sequence fused to a heterologous protein. By contrast, deleting structural signal sequences caused similar defects to knocking out the genes encoding the full-length PduM and PduB proteins. Our results contribute to a growing understanding of how MCPs form and function in bacteria and provide strategies to mitigate assembly disruption when encapsulating heterologous pathways in MCPs. IMPORTANCE Spatially organizing biosynthetic pathway enzymes is a promising strategy to increase pathway throughput and yield. Bacterial microcompartments (MCPs) are proteinaceous organelles that many bacteria natively use as a spatial organization strategy to encapsulate niche metabolic pathways, providing significant metabolic benefits. Encapsulating heterologous pathways of interest in MCPs could confer these benefits to industrially relevant pathways. Here, we investigate the role of signal sequences, short domains that target proteins for encapsulation in MCPs, in the assembly of 1,2-propanediol utilization (Pdu) MCPs. We characterize two novel signal sequences on structural proteins, constituting the first Pdu signal sequences found on structural proteins rather than enzymes, and perform knockout studies to compare the impacts of enzymatic and structural signal sequences on MCP assembly. Our results demonstrate that enzymatic and structural signal sequences play critical but distinct roles in Pdu MCP assembly and provide design rules for engineering MCPs while minimizing disruption to MCP assembly.

Johnson, Elizabeth R. (ORCID:0000000179236881)↗