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At least 1,405 records · Page 78

Rethinking the Price Formation Problem–Part 2: Rewarding Flexibility and Managing Price Risk

In this study, part 1 of this two-part paper describes the impact that uncertainty has on the design and analysis of price formation policies in the non-convex auctions conducted by U.S. wholesale electricity market operators. Using first a toy model and then a large-scale test system, Part 2 demonstrates the difference in prices under the idealized benchmark of ex ante convex hull pricing defined in Part 1 versus existing methods, in particular documenting the potential for suppression of volatility and therefore under-compensation of flexibility by existing methods. The examples highlight that inefficient spot price formation can induce inefficient forward commitments of generators, necessitating out-of-market intervention to restore a reliable and efficient operating plan.Given the potential side effects of existing policies for investment and operation, we suggest two elements in a reoriented approach to the price formation problem: first ensuring that prices exhibit full-strength volatility, and second ensuring that risk-averse market participants have sufficient ability to manage this volatility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Rapid Monitoring and Defense Approach for Resilience Improvement of Grid Cyber Security

Cyber-physical systems and electric utilities significantly depend on the reliability and efficiency of information and operational technology. However, false data injection attacks based on synchrophasor measurement data pose a serious threat to the safe and reliable operation of modern power systems. Here, to mitigate this problem, a rapid monitoring and defense approach is proposed to defend against cyber attacks. Initially, the Time and Frequency based Convolutional neural Network (TFCN) is proposed to detect different types of attacks. Within the TFCN, the advances are that both time and frequency domain information can be fused without extra spectrum analysis methods, and can save detection time to speed the calculation efficiency using the developed time-frequency block. Next, a comprehensive defense strategy is developed for multiple cyber attacks to ensure the stability and resilience of the power system according to the feedback detection results. The advances of this strategy are that different control strategies can be automatically selected to recover the stability to the greatest extent according to the detected attacks. To verify the effectiveness of the proposed approach, the high-speed frequency measurements collected from the wide-area monitoring system are used. The results demonstrate that the cyber attack detection performance can reach 95.57% accuracy, outperforming both traditional and some advanced neural networks. Importantly, the defense strategy is conducted and verified in a modified IEEE 39 bus system as well, which illustrates profound performance in faster stability restoration.

Comprehensive defense strategy↗

Filtered Backprojection in Compton Imaging using a Spherical Harmonic Wiener Filter with Pixelated CdZnTe

Filtered backprojection is an image reconstruction technique for Compton imaging that provides reasonably high resolution at much lower computational costs when compared to iterative methods. Here, this work applies a Wiener filter that has been derived for spherical harmonics on Compton imaging using the OrionUM pixelated CdZnTe imaging-spectrometer. To regularize the filter, an investigation is made into the power spectral density of the signal and noise to develop an appropriate spectral signal-to-noise ratio model for the restoration process. Experimental measurements were conducted with two 228Th sources placed 30° apart. The resulting filtered image of the two sources have an average full-width-at-half-maximum (FWHM) of 9.8° or 7.5° when using a mean squared error and structural similarity optimization approach respectively; an improvement from the 29.0° FWHM image when using simple backprojection.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Stacked Low-Inertia Converter or Solid-State Transformer: Modeling and Model Predictive Priority-Shifting Control for Voltage Balance

This paper presents control challenges of stacked low-inertia converter (SLIC) or cascaded reduced dc-link solid-state transformer (SST) and proposes a novel model predictive priority-shifting (MPPS) control with implicit modulator and a discrete-time large-signal model for voltage balancing and dc-link regulation. Low-inertia converters, featuring small electrolytic capacitor-less dc links, dramatically reduce cost, size, and weight compared to conventional solutions. However, without a large dc-link buffer, the input and output are tightly coupled, leading to significant control challenges. The control becomes even more challenging with these converters stacked input-series output-parallel (ISOP) for medium-voltage (MV) grid, which causes coupling between the modules besides the coupling within each module. This paper analyzes the multi-objective, multi-degree of freedom control problem, using the modular soft-switching solid-state transformer (M-S4T) as an example of the SLIC. First, distribution of control efforts under controller saturation is critical because multiple control objectives can be conflicting, especially when the module voltages are unbalanced and are being restored. The MPPS can shift the priorities to address this issue. Second, due to the low inertia and high dc-link ripple, classic space vector pulse-width modulation (SVPWM), average model with small-ripple assumption, and control design based on small-signal model cannot accurately modulate, model, and control the nonlinear reduced dc link. Therefore, a discrete-time large-signal model of the M-S4T is established to derive the predictive control in the MPPS. The MPPS and the PI control are compared in MV simulations to show the issue of applying the PI to the SLIC and the effectiveness of the MPPS for voltage balancing and dc-link regulation in a deadbeat manner. Finally, the proposed control is tested on a 5 kV ISOP SiC SST prototype to verify priority shifting to address controller saturation issue and fast and robust voltage balancing.

14 SOLAR ENERGY↗

Resilience-Oriented DG Siting and Sizing Considering Stochastic Scenario Reduction

In this paper, a fuel-based distributed generator (DG) allocation strategy is proposed to enhance the distribution system resilience against extreme weather. The long-term planning problem is formulated as a two-stage stochastic mixed-integer programming (SMIP). The first stage is to make decisions of DG siting and sizing under the given budget constraint. In the second stage, a post-extreme-event-restoration (PEER) is employed to minimize the operating cost in an uncertain fault scenario. In particular, this study proposes a method to select the most representative scenarios for the SMIP. First, a Monte Carlo Simulation (MCS) is introduced to generate sufficient scenarios considering random fault locations and load profiles. Then, the number of scenarios is reduced by the K-means clustering algorithm. The advantage of scenario reduction is to make a trade-off between accuracy and computational efficiency. Finally, the SMIP is solved by the progressive hedging algorithm. Here, the case studies of the IEEE 33-bus and 123-bus test systems demonstrate the effectiveness of the proposed algorithm in reducing the expected energy not served (EENS), which is a critical criterion of resilience.

42 ENGINEERING↗

Resilience Evaluation and Enhancement for Island City Integrated Energy Systems

Extreme natural hazards, such as hurricanes or earthquakes, have a high probability of threatening energy supply security and causing high-order contingencies to island city-integrated energy systems (IC-IESs). To better evaluate and enhance resilience, a novel approach is proposed in this work for IC-IESs. The resilience of an IC-IES is analyzed from both the system level and the component level. At the system level, the impacts of extreme natural disasters are quantified. At the component level, the importance of individual components is analyzed through pre-failure and post-failure indices. The pre-failure index identifies the system’s weak links before an energy interruption, and the post-failure index determines the optimal repair strategy to restore the service. The proposed indices are solved by the impact increment method (IIM), which significantly improves computational efficiency without much affecting result accuracy. Numerical simulation studies are conducted on the modified Barry Island IES and IES E123-G48-H32 test systems. Furthermore, the results validate the effectiveness of the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Adaptive Deep Reinforcement Learning Algorithm for Distribution System Cyber Attack Defense With High Penetration of DERs

With grid modernization, smart inverters are increasingly used to execute advanced controls for distribution network reliability. However, this also increases the cyber-attack space. Here this paper focuses on the defense approaches to restore the system to normal operation circumstances in the presence of cyber-attacks. A unique deep reinforcement learning (DRL) method is developed to minimize voltage violations and reduce power losses for impacted feeders. The defense problem is reformulated as a Markov decision-making process to dynamically control DERs while minimizing load shedding. This is achieved via an improved soft actor-critic (SAC)-based DRL algorithm, which can govern DER set points and load-shedding scenarios in discrete and continuous modes via the auto-tune entropy and Gaussian policy features. Numerical comparison results on the modified IEEE 123-node system with other control approaches, such as Volt-VAR (VV), Volt-Watt (VW), and model predictive control (MPC) show that the proposed method can eliminate voltage violations and provide feasible control actions that perform complete mitigation of cyber-threats.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Integrated Framework of Multisource Data Fusion for Outage Location in Looped Distribution Systems

Accurate outage location is essential for expediting post-outage power restoration, minimizing outage duration, and enhancing the resilience of distribution networks. With the advent of advanced metering infrastructure, data-driven outage location methods have significantly advanced beyond traditional approaches that rely on manual inspections. However, existing methods still face critical challenges, like reliance on single-source data, limited ability to handle partially observable systems or difficulties with loop networks. To the best of our knowledge, no single approach has comprehensively addressed all of these challenges at once. To this end, this paper proposes a comprehensive multisource data fusion framework for outage locations via probabilistic graph networks. The framework consists of three key phases. First, a novel method for reconstituting distribution networks with loops is developed, transforming looped networks into multiple radial subnetworks that retain all outage causalities of the original network. Second, Bayesian network (BN) models are established for each subnetwork, integrating multiple data sources and network structures. Finally, a joint Gibbs sampling mechanism, featuring forward and backward information flow, is designed to merge data from separate BN models and maximize the utilization of limited evidence, ensuring accurate outage location identification. In conclusion, the framework was validated on two modified public test systems, and comparative studies confirmed its effectiveness.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Guest Editorial: Special Section on Sustainable Energy for Enhancing Grid Resiliency

Extreme weather threatens lives, disables communities, and devastates energy generation, transmission, and distribution systems. These extreme events are likely to become more frequent or more intense due to climate change. Energy networks have shown significant vulnerability during record hurricanes, deadly heat waves, destructive wildfires, and winter storms in the past few years. Because of the energy transition process, modern power grids will feature a high penetration level of the use of renewable resources. The adoption of renewable energy and the rise of omnidirectional power delivery mean that our energy network is more decentralized than ever. In this new environment, grid operation becomes more complex, and achieving resiliency is more difficult than in the past. Many utilities are seeking the latest technologies to improve energy security and responsiveness to severe events. On the one hand, sustainable energy resources can provide emergency power and assist grid restoration in disastrous events. On the other hand, their volatility, susceptibility, interdependency, and other unique features must be carefully considered when being used for grid resilience enhancement. This special section brings together 22 papers that range from innovative research advances tackling fundamental challenges of achieving more resilient grids to real-world demonstrations of leveraging sustainable energy resources to enhance grid resiliency. These papers can be categorized into three groups.

climate change↗

Bioenergy landscapes drive trophic shifts in generalist ants

Changes in trophic niche—the pathways through which an organism obtains energy and nutrients—are a fundamental way in which organisms respond to environmental conditions. But the capacity for species to alter their trophic niches in response to global change, and the ways they do so when able, remain largely unknown. Here we examine food webs in three long–term and large–scale experiments to test how resource availability and nutritional requirements interact to determine an organism's trophic niche in the context of one of the largest global trends in land use—the rise in bioenergy production. Here, we use carbon and nitrogen stable isotope analyses to characterize arthropod food webs across three biofuel crops representing a gradient in plant resource richness (corn monocultures, fields dominated by native switchgrass and restored prairie), and to quantify changes in the trophic niche of a widespread generalist ant species across habitats. In doing so, we measure the effects of basal resource richness on food chain length, niche breadth and trophic position. We frame our results in the context of two hypotheses that explain variation in trophic niche—the niche variation hypothesis which emphasizes the importance of resource diversity and ecological opportunity, and the optimal diet hypothesis which emphasizes dietary constraints and the availability of optimal resources. Increasing plant richness lengthened food chains by 10%–20% compared to monocultures. Niche breadths of generalist ants did not vary with resource richness, suggesting they were limited by optimal diet requirements and constraints rather than by ecological opportunity. The ants instead responded to changes in plant richness by shifting their estimated trophic position. In resource–poor monocultures, the ants were top predators, sharing a trophic position with predatory spiders. In resource–rich environments, in contrast, the ants were omnivores, relying on a mix of animal prey and plant–based resources. In addition to highlighting novel ecosystem impacts of alternate bioenergy landscapes, our results suggest that niche breadth and trophic diversification depend more on the presence of optimal resources than on ecological opportunity alone.

59 BASIC BIOLOGICAL SCIENCES↗

Warming decreases desert ecosystem functioning by altering biocrusts in drylands

Warming and precipitation fluctuations are changing desert ecosystems in global drylands. However, the effects of climate change on keystone species such as cryptogamic biocrust in drylands remain relatively under-investigated, even though biocrusts play a vital role in desert ecosystems. Here we conducted a long-term experiment (14 years) to simulate the responses of two main types of biocrusts to warming coupled with reduction in precipitation that was achieved by open-top chambers (OTCs) to simulate the predicted warming and precipitation decreasing under climate change scenario. We also conduct a structural analysis to evaluate the resulting changes in desert ecosystem functioning (carbon and nitrogen cycling). Neither warming and corresponding rainfall reduction treatments had a negative effect on lichen species richness, but both treatments reduced lichen cover and biomass. The negative effects of warming on moss-dominated crusts were much greater than those on lichen-dominated crusts. Although mosses and lichens had varying degree responses to warming, the loss of mosses and decreased lichen cover and biomass, as well as the shortening of the wet time, resulted in a reduction in carbon and nitrogen fixation, soil enzyme activity and water-holding capacity of biocrusts and topsoil. These impacts collectively change the water balance of drylands and weaken the hydrological and biogeochemical function of biocrusts. Synthesis and applications: Results from this long-term experiment suggest that the ecosystem C and N cycling and water balance of global drylands may be highly impacted by climate change, in part because of the response of biocrusts, which contribute an important implication for both dryland restoration and earth system dynamics.

54 ENVIRONMENTAL SCIENCES↗

SIRT1 targeted by miR ‐211‐5p regulated proliferation and apoptosis of Dex‐treated growth plate chondrocytes via mediating SOX2

Abstract Dexamethasone (Dex) is reported to cause bone growth retardation in children, which is associated with the increased apoptosis and decreased proliferation of growth plate chondrocytes. Sirtuin 1 (SIRT1) plays an important role in chondrocyte function and homeostasis. Thus, we further explored the regulatory mechanism of SIRT1 in Dex‐induced growth plate chondrocyte dysfunction. SIRT1 expression was detected in Dex‐treated growth plate chondrocytes using RT‐qPCR and western blot assay. The modulation of SIRT1 on SOX2 expression was evaluated. Besides, we identified that SIRT1 was targeted by miR‐211‐5p using TargetScan and RNA pull‐down assay. A loss‐of‐function assay was performed to evaluate the effects of miR‐211‐5p on Dex‐induced growth plate chondrocyte dysfunction in vitro and in vivo. We found that SIRT1 was downregulated in Dex‐treated growth plate chondrocytes. The expression of SOX2 was upregulated by overexpression SIRT1. Meanwhile, downregulation of SOX2 weakened the positive function of SIRT1 overexpression on Dex‐induced growth plate chondrocytes dysfunction. Subsequently, we confirmed that SIRT1 was targeted by miR‐211‐5p. MiR‐211‐5p inhibitor increased the expression levels of SIRT1 and SOX2, and restored the Dex‐treated growth plate chondrocyte function. Animal assays further demonstrated that the effects of miR‐211‐5p on the growth plate chondrogenesis. In conclusion, our data suggest that SIRT1 exerts a protective effect on growth plate chondrocyte under Dex stimulation. MiR‐211‐5p/SIRT1/SOX2 axis regulates the process of Dex‐inhibited growth plate chondrogenesis.

Cheng, Deliang↗

Stochastic and deterministic processes shape bioenergy crop microbiomes along a vertical soil niche

Abstract Sustainable biofuel cropping systems aim to address climate change while meeting energy needs. Understanding how soil and plant‐associated microbes respond to these different cropping systems is key to promoting agriculture sustainability and evaluating changes in ecosystem functions. Here, we leverage a long‐term biofuel cropping system field experiment to dissect soil and root microbiome changes across a soil‐depth gradient in poplar, restored prairie and switchgrass to understand their effects on the microbial communities. High throughput amplicon sequencing of the fungal internal transcribed spacer (ITS) and prokaryotic 16S DNA regions showed a common trend of root and soil microbial community richness decreasing and evenness increasing with depth. Ecological niche (root vs. soil) had the strongest effect on community structure, followed by depth, then crop. Stochastic processes dominated the structuring of fungal communities in deeper soil layers while operational taxonomic units (OTUs) in surface soil layers were more likely to co‐occur and to be enriched by plant hosts. Prokaryotic communities were dispersal limited at deeper depths. Microbial networks showed a higher density, connectedness, average degree and module size in deeper soils. We observed a decrease in fungal‐fungal links and an increase of bacteria–bacteria links with increasing depth in all crops, particularly in the root microbiome.

59 BASIC BIOLOGICAL SCIENCES↗

Experimental nitrogen and phosphorus enrichment stimulates multiple trophic levels of algal and detrital-based food webs: a global meta-analysis from streams and rivers

Anthropogenic increases in nitrogen (N) and phosphorus (P) concentrations can strongly influence the structure and function of ecosystems. Even though lotic ecosystems receive cumulative inputs of nutrients applied to and deposited on land, no comprehensive assessment has quantified nutrient-enrichment effects within streams and rivers. We conducted a meta-analysis of published studies that experimentally increased concentrations of N and/or P in streams and rivers to examine how enrichment alters ecosystem structure (state: primary producer and consumer biomass and abundance) and function (rate: primary production, leaf breakdown rates, metabolism) at multiple trophic levels (primary producer, microbial heterotroph, primary and secondary consumers, and integrated ecosystem). Our synthesis included 184 studies, 885 experiments, and 3497 biotic responses to nutrient enrichment. We documented widespread increases in organismal biomass and abundance (mean response = +48%) and rates of ecosystem processes (+54%) to enrichment across multiple trophic levels, with no large differences in responses among trophic levels or between autotrophic or heterotrophic food-web pathways. Responses to nutrient enrichment varied with the nutrient added (N, P, or both) depending on rate versus state variable and experiment type, and were greater in flume and whole-stream experiments than in experiments using nutrient-diffusing substrata. Generally, nutrient-enrichment effects also increased with water temperature and light, and decreased under elevated ambient concentrations of inorganic N and/or P. Overall, increased concentrations of N and/or P altered multiple food-web pathways and trophic levels in lotic ecosystems. Finally, our results indicate that preservation or restoration of biodiversity and ecosystem functions of streams and rivers requires management of nutrient inputs and consideration of multiple trophic pathways.

59 BASIC BIOLOGICAL SCIENCES↗

Otolith 87 Sr / 86 Sr identifies natal origin, movement and life history of Burbot Lota lota in the Kootenai River following 45 years of impoundment

Abstract Hydropower has long been an effective form of renewable energy, but the development of the resource has negatively impacted fishes throughout the world. Formulating recovery plans to mitigate these effects requires a firm understanding of species‐specific provenance, life history and life stage habitat requirements. However, the importance of this information is often only recognised after a substantial population decline, when obtaining it becomes demographically challenging. We provide a case study for this scenario and present a post hoc approach to gain insight into these critical data gaps for Burbot Lota lota in the upper Kootenai River in Montana and British Columbia. The population once supported a robust tribal and recreational harvest but declined following impoundment and these fisheries have remained closed or curtailed for nearly 20 years. The reasons for the decline are unknown and actions to assist recovery have been constrained by limited information regarding natal origin, life history and habitat use. We addressed this issue using strontium isotope ratios ( 87 Sr/ 86 Sr) in otoliths collected over four decades in Lake Koocanusa, the reservoir on the Kootenai River above Libby Dam. Due to the geologic heterogeneity of the basin and resulting variation in water 87 Sr/ 86 Sr, the assignment probability for Burbot to their region of natal origin approached unity. Otolith 87 Sr/ 86 Sr also indicated the population was comprised of mainstem‐ and tributary‐origin forms and their relative abundance changed over time. Mainstem Burbot was most abundant during the 1970s and 2000s, whereas tributary forms dominated between these periods. We suggest ecosystem changes following impoundment contributed to this shift in life history forms and the overall decline of the population. Our findings underscore the need for additional investigations of these impacts to guide restoration efforts.

Dunnigan, James L.↗

Detection efficiency of adult Pacific lamprey passage counts at Leaburg Dam and upstream distribution in the McKenzie River (Oregon, USA)

Abstract Adult Pacific lamprey ( Entosphenus tridentatus ) were counted using consistent methodology since 2005 with a video monitoring system as they passed Leaburg Dam (McKenzie River, Oregon, USA) en route to upstream spawning areas. In this study we evaluated the detection efficiency of the video system and upstream distribution of Pacific lamprey using the video counts of lamprey passage (herein, “dam counts”), passive integrated transponder (PIT) tags, and radio telemetry. In 2019–2020 we collected, tagged and tracked 32 adult lamprey (4 from the McKenzie River and 28 that were translocated from Willamette Falls). All fish were tagged and released into the tailrace of Leaburg Dam in June 2019. Oregon Department of Fish and Wildlife employees and volunteers from the local community conducted mobile radiotracking above and below the dam in drift boats (114 mainstem river kilometers) and on foot (several tributaries). The estimated detection efficiency for dam counts was 92% (95% confidence interval: 67%–99%). Fifty percent (16 of 32) of the tagged lamprey passed the dam, including 13 of 28 that were translocated. Thirty‐seven percent (6 of 16) of lamprey that passed Leaburg Dam were detected in a restored reach of the South Fork McKenzie, 32.6 river kilometers upstream of the dam.

Romer, Jeremy D.↗

Hsa_circ_0000515 is a novel circular RNA implicated in the development of breast cancer through its regulation of the microRNA‐296‐5p/CXCL10 axis

Cancer metastasis is a major cause of death among women afflicted with breast cancer (BC) and understanding the molecular processes involved is a major focus in BC research. Circular RNAs (circRNAs) have emerged as genomic regulatory molecules in carcinogenesis and metastasis; however, their role in BC is unclear. We characterized a novel circRNA, hsa_circ_0000515, in context of BC. We collected 340 cancerous tissues surgically resected from BC patients and found hsa_circ_0000515 was upregulated in BC tissues and associated with poor prognosis of BC. Silencing of hsa_circ_0000515 impaired cell cycle progression, cell proliferation, and invasion, attenuated inflammatory response, and reduced the proangiogenetic potential of BC cells. RNA pull‐down and dual‐luciferase reporter gene assays showed that hsa_circ_0000515 binds miR‐296‐5p, preventing it from repressing CXCL10 expression. We also observed that miR‐296‐5p inhibition or CXCL10 overexpression promoted cell cycle progression, restored proliferative, invasive and proangiogenetic abilities, and increased inflammatory response in MCF‐7 cells in the absence of hsa_circ_0000515. In vivo analyses showed that partial loss of hsa_circ_0000515 reduced the tumor growth of MCF‐7 cells in nude mice. The key findings from this study revealed that targeting hsa_circ_0000515 might be an effective strategy to combat BC.

Cai, Fenglin↗

Where old meets new: An ecosystem study of methanogenesis in a reflooded agricultural peatland

Reflooding formerly drained peatlands has been proposed as a means to reduce losses of organic matter and sequester soil carbon for climate change mitigation, but a renewal of high methane emissions has been reported for these ecosystems, offsetting mitigation potential. Our ability to interpret observed methane fluxes in reflooded peatlands and make predictions about future flux trends is limited due to a lack of detailed studies of methanogenic processes. In this study we investigate methanogenesis in a reflooded agricultural peatland in the Sacramento Delta, California. Furthermore, we use the stable-and radio-carbon isotopic signatures of wetland sediment methane, ecosystem-scale eddy covariance flux observations, and laboratory incubation experiments, to identify which carbon sources and methanogenic production pathways fuel methanogenesis and how these processes are affected by vegetation and seasonality. We found that the old peat contribution to annual methane emissions was large (~30%) compared to intact wetlands, indicating a biogeochemical legacy of drainage. However, fresh carbon and the acetoclastic pathway still accounted for the majority of methanogenesis throughout the year. Although temperature sensitivities for bulk peat methanogenesis were similar between open-water (Q 10 = 2.1) and vegetated (Q 10 = 2.3) soils, methane production from both fresh and old carbon sources showed pronounced seasonality in vegetated zones. We conclude that high methane emissions in restored wetlands constitute a biogeochemical trade-off with contemporary carbon uptake, given that methane efflux is fueled primarily by fresh carbon inputs.

54 ENVIRONMENTAL SCIENCES↗