A Decentralized Fault Section Location Method Using Autoencoder and Feature Fusion in Resonant Grounding Distribution Systems

In industrial applications, the existing fault location methods of resonant grounding distribution systems suffer from low accuracy due to excessive dependence on communication, lack of field data, difficulty in artificial feature extraction and threshold setting, etc. To address these problems, this study proposes a decentralized fault section location method, which is implemented by the primary and secondary fusion intelligent switch (PSFIS) with two preloaded algorithms: autoencoder (AE) and backpropagation neural network. The relation between the transient zero-sequence current and the derivative of the transient zero-sequence voltage in each section is analyzed, and its features are extracted adaptively by using AE, without acquiring network parameters or setting thresholds. The current and voltage data are processed locally at PSFISs throughout the whole procedure, making it is insusceptible to communication failure or delay. The feasibility and effectiveness of the approach are investigated in PSCAD/EMTDC and real-time digital simulation system, which is then validated by field data. Compared with other methods, the experiment results indicate that the proposed method performs well in various scenarios with strong robustness to harsh on-site environment and roughness of data

How Committed Individuals Shape Social Dynamics: A Survey on Coordination Games and Social Dilemma Games

Committed individuals, who features steadfast dedication to advocating strong beliefs, values, and preferences, have garnered much attention across statistical physics, social science, and computer science. This survey delves into the profound impact of committed individuals on social dynamics that emerge from coordination games and social dilemma games. Through separate examinations of their influence on coordination, including social conventions and color coordination games, and social dilemma games, including one-shot settings, repeated settings, and vaccination games, this survey reveals the significant role committed individuals play in shaping social dynamics. Their contributions range from accelerating or overturning social conventions to addressing cooperation dilemmas and expediting solutions for color coordination and vaccination issues. Furthermore, the survey outlines three promising directions for future research: conducting human behavior experiments for empirical validation, leveraging advanced large language models as proxies for committed individuals in complex scenarios, and addressing potential negative impacts of committed individuals

An Integrated Approach for Failure Mitigation & Localization in Power Systems

The transmission grid is often comprised of several control areas that are connected by multiple tie lines in a mesh structure for reliability. It is also well-known that line failures can propagate non-locally and redundancy can exacerbate cascading. In this paper, we propose an integrated approach to grid reliability that (i) judiciously switches off a small number of tie lines so that the control areas are connected in a tree structure; and (ii) leverages a unified frequency control paradigm to provide congestion management in real time. Even though the proposed topology reduces redundancy, the integration of tree structure at regional level and real-time congestion management can provide stronger guarantees on failure localization and mitigation. We illustrate our approach on the IEEE 39-bus network and evaluate its performance on the IEEE 118-bus, 179-bus, 200-bus and 240-bus networks with various network congestion conditions. Simulations show that, compared with the traditional approach, our approach not only prevents load shedding in more failure scenarios, but also incurs smaller amounts of load loss in scenarios where load shedding is inevitable. Moreover, generators under our approach adjust their operations more actively and efficiently in a local manner.Comment: Accepted to the 21st Power Systems Computation Conference (PSCC 2020

An integrated approach for failure mitigation & localization in power systems

The transmission grid is often comprised of several control areas that are connected by multiple tie lines in a mesh structure for reliability. It is also well-known that line failures can propagate non-locally and redundancy can exacerbate cascading. In this paper, we propose an integrated approach to grid reliability that (i) judiciously switches off a small number of tie lines so that the control areas are connected in a tree structure; and (ii) leverages a unified frequency control paradigm to provide congestion management in real time. Even though the proposed topology reduces redundancy, the integration of tree structure at regional level and real-time congestion management can provide stronger guarantees on failure localization and mitigation. We illustrate our approach on the IEEE 39-bus network and evaluate its performance on the IEEE 118-bus, 179-bus, 200-bus and 240-bus networks with various network congestion conditions. Simulations show that, compared with the traditional approach, our approach not only prevents load shedding in more failure scenarios, but also incurs smaller amounts of load loss in scenarios where load shedding is inevitable. Moreover, generators under our approach adjust their operations more actively and efficiently in a local manner

An integrated approach for failure mitigation & localization in power systems

The transmission grid is often comprised of several control areas that are connected by multiple tie lines in a mesh structure for reliability. It is also well-known that line failures can propagate non-locally and redundancy can exacerbate cascading. In this paper, we propose an integrated approach to grid reliability that (i) judiciously switches off a small number of tie lines so that the control areas are connected in a tree structure; and (ii) leverages a unified frequency control paradigm to provide congestion management in real time. Even though the proposed topology reduces redundancy, the integration of tree structure at regional level and real-time congestion management can provide stronger guarantees on failure localization and mitigation. We illustrate our approach on the IEEE 39-bus network and evaluate its performance on the IEEE 118-bus, 179-bus, 200-bus and 240-bus networks with various network congestion conditions. Simulations show that, compared with the traditional approach, our approach not only prevents load shedding in more failure scenarios, but also incurs smaller amounts of load loss in scenarios where load shedding is inevitable. Moreover, generators under our approach adjust their operations more actively and efficiently in a local manner

An incremental high impedance fault detection method under non-stationary environments in distribution networks

In the non-stationary environments of distribution networks, where operating conditions continually evolve, maintaining reliable high impedance faults (HIF) detection is a significant challenge due to the frequent changes in data distribution caused by environmental variations. In this paper, we propose a novel HIF detection method based on incremental learning to handle non-stationary data stream with changing distributions. The proposed method utilizes stationary wavelet transform (SWT) to extract fault characteristics in different frequency domains from zero-sequence current data. Subsequently, a complex mapping from signal features to operational conditions is established using backpropagation neural network (BPNN) to achieve online detection of HIF. Additionally, signal features are analyzed using density-based spatial clustering of applications with noise (DBSCAN) to monitor the distribution of data. After encountering multiple distribution changes, an incremental learning process based on data replay is initiated to evolve the BPNN model for adapting to the changing data distribution. It is worth noting that the data replay mechanism ensures that the model retains previously acquired knowledge while learning from newly encountered data distributions. The proposed method was implemented in a prototype of a designed edge intelligent terminal and validated using a 10 kV testing system data. The experimental results indicate that the proposed method is capable of identifying and learning new distribution data information within non-stationary data stream. This enables the classifier model to maintain a high level of detection accuracy for the current cycle data, effectively enhancing the reliability of HIF detection

Optimizing postbiotic production through solid-state fermentation with Bacillus amyloliquefaciens J and Lactiplantibacillus plantarum SN4 enhances antibacterial, antioxidant, and anti-inflammatory activities

BackgroundPostbiotics are an emerging research interest in recent years and are fairly advanced compared to prebiotics and probiotics. The composition and function of postbiotics are closely related to fermentation conditions.MethodsIn this study, we developed a solid-state fermentation preparation method for postbiotics with antimicrobial, antioxidant, and anti-inflammatory activities. The antibacterial activity was improved 3.62 times compared to initial fermentation conditions by using optimization techniques such as single factor experiments, Plackett–Burman design (PBD), steepest ascent method (SAM), and central composite design (CCD) methods. The optimized conditions were carried out with an initial water content of 50% for 8 days at 37°C and fermentation strains of Bacillus amyloliquefaciens J and Lactiplantibacillus plantarum SN4 at a ratio of 1:1 with a total inoculum size of 8%. The optimized SSF medium content ratios of peptide powder, wheat bran, corn flour, and soybean meal were 4, 37.4, 30, and 28.6%, respectively.ResultsUnder these optimized conditions, postbiotics with a concentration of 25 mg/mL showed significant broad-spectrum antibacterial capabilities against Escherichia coli, Salmonella, and Staphylococcus aureus and strong antioxidant activity against ABTS, DPPH, and OH radicals. Moreover, the optimized postbiotics exhibited good anti-inflammatory ability for reducing nitric oxide (NO) secretion in RAW 264.7 macrophage cells in response to LPS-induced inflammation. Furthermore, the postbiotics significantly improved intestinal epithelial wound healing capabilities after mechanical injury, such as cell scratches in IPEC-J2 cells (p < 0.05).ConclusionIn brief, we developed postbiotics through optimized solid-state fermentation with potential benefits for gut health. Therefore, our findings suggested that the novel postbiotics could be used as potential functional food products for improving body health

Turbulent interactions with normal shocks and their effects on aluminum particle burn time

Interactions between turbulence and shock waves have been proposed to decrease the burn time of fuel particles due to various mechanisms such as enhanced mixing, entropy production, and transport. In order to demonstrate this e ffect, burn time measurements were obtained for laminar and turbulent conditions at similar test conditions. The amount of turbulence present was also studied using PIV methods to verify that it represents a signi cant di fference between the two conditions. The experiments were conducted in the UIUC heterogeneous shock tube facility. The test conditions were 10atm and 2500K after the refl ected shock for both the turbulent and laminar cases. Turbulence conditions were produced by placing a perforated plate directly upstream of the optical section installed at the end of the shock tube; the plate design has been previously documented in multiple papers to produce an area of isotropic and homogeneous turbulence. The test particles were 40-60nm Al, 110 nm Al, 4 um Al, and 7.5 um Al in order to allow for a representative range of Al particles typically used in energetics research. High speed cameras and a 532 nm green laser were used to obtain both the burn time data and PIV turbulence images. Burn time results showed a 10-25% reduction in burn times for the turbulent case compared to the laminar case. The amount of reduction seems to decrease by increasing particle size. Due to a lack of standard burn time evaluation procedure and thermal noise in the data, e fforts were necessary to address repeatability and error issues. Therefore, 3 tests were conducted at each condition for each particle size, and variation between the tests were accounted for in the error to show that despite the error present, we can be reasonably con fident that there exists a notable burn time reduction. Finally, PIV was employed to study the quality and quantity of the turbulence present in the test conditions. The turbulent case PIV data indicated an average turbulence intensity of approximately 3%, which may be qualifi ed as medium turbulence. Laminar PIV data was less indicative due to poor seeding capabilities and flow disruption when the seeded particles were swept o the loading plate in the shock tube. An estimated 1% turbulence intensity was still observed in the laminar case, although it is clear from the velocity profi les that the fl ow is significantly more uniform and data less precise and therefore less reliable