This paper presents an extensive dataset of real-world oscillograms that capture voltage and current signals from electrical substations. The dataset aims to advance research on power system analysis, fault detection, and machine learning-driven relay protection. It includes approximately 50,000 oscillograms recorded with sampling rates up to 8 kHz. A manually annotated subset of 480 oscillograms categorizes events into four groups: noise-dominated signals without deviations; routine equipment operations such as load switching, circuit breaker actions, motor startups, or transformer energization; non-critical deviations compliant with operational standards, including single-phase ground faults or minor voltage dips; critical faults such as short-circuits or voltage collapses requiring immediate relay protection activation. The unannotated part of the data supports self-supervised and unsupervised machine learning methods, enabling tasks like feature extraction, anomaly detection, and latent pattern identification in power networks. The dataset facilitates various applications, including the validation of synthetically trained models, the refinement of adaptive relay protection algorithms, and the development of fault detection and diagnosis systems.

This study quantitatively analyzed the effects of repetitive fault currents occurring in an accelerator environment on the breaking performance of molded-case circuit breakers (MCCBs). To this purpose, four MCCB samples are subjected to one, two, and three repeated fault tests. The interrupting process is divided into the arc stretch and moving (t1–t2) section and the absorption in the splitter plate (t2–t3) section, and the energy and time are analyzed. The experimental results show that the total energy consumption increased by an average of 1.8–1.9 times in the second and third tests compared to the first test, and the interruption time is also extended by 1.6–2.0 times. In particular, the energy increase rate in the t2–t3 section is the highest, at an average of 220%, indicating that the splitter plate is thermally saturated and significantly affected by hot gas due to repeated breaking. These results imply that the thermal and electrical performances of MCCBs deteriorates in a repetitive fault environment, with the interrupting speed delayed and internal energy loss increased. This study suggests the possibility of energy-based condition diagnosis using the energy consumption ratio of each section. Furthermore, the ratios can be used as basic data for evaluating the reliability of circuit breakers under repetitive failure conditions and building predictive maintenance models.

A realistic breaker model for simulation of prestrike/restrike in circuit breakers

Coordination of Directional Overcurrent Relays in Transient Topologies Induced by Faster Operation of Remote-side Circuit Breakers

Coupled simulation of anode erosion in vacuum circuit breakers under high-frequency inrush current

Fault-tolerant control of discrete-time markov jump power systems based on mode detection information.

Investigation on the Thermal Characteristics of 33 kV DC Vacuum Circuit Breakers Using 3-D Modeling

Hypergeometric behavior of metal oxide varistors in DC circuit breakers

Suppression of Diode-Induced Reverse Voltage Stress for the Asymmetric IGCT Device in the Hybrid MVDC Circuit Breaker

Smart Electrical Outlet with Integrated Circuit Breaker Protection

Most faults in power lines are caused by short circuits resulting from phenomena such as lightning, severe weather, or power surges linked to circuit breaker operations. These short circuits, whether temporary or permanent, require accurate detection and location to enable rapid repair and restoration of power supply. To protect the system against short-circuit currents, which can cause irreversible damage to key equipment, it is essential to quickly disconnect the faulty part of the network. In order to correctly size this equipment, it is essential to estimate the magnitude of the currents likely to flow during a short circuit. This study involved calculating single-phase short-circuit currents in the event of a fault on the Cable, Soluxe, Airoport, Talladje, and Gawaye feeders at the Niamey3 electrical substation. The method used to calculate short-circuit currents in HTB and HTA networks is based on the principle of symmetrical components. This method was chosen for its accuracy and analytical nature. The results obtained show that the Soluxe feeder has the highest short-circuit current, with a value of 1.95 kA, compared to those of the Cable, Airoport, Talladje, and Gawaye feeders, which are 1.86 kA, 0.67 kA, 0.64 kA, and 0.56 kA, respectively. This is explained by the fact that the calculated impedances (direct, inverse, and zero-sequence) of this feeder are lower than those of the other four feeders.

Abstract In response to the problems of interference and low fault diagnosis accuracy in traditional circuit breaker communication, a hybrid model of high-speed power line carrier communication and convolutional neural network-long short-term memory network is studied to construct an intelligent molded case circuit breaker system. In terms of communication, the use of orthogonal frequency division multiplexing modulation and parallel cascaded convolutional code encoding technology significantly improves anti-interference ability and transmission stability. In terms of fault diagnosis, a dual input convolutional neural network-long short-term memory network model is constructed, which integrates current and voltage waveform image features with multi-dimensional temporal state data to achieve accurate identification and early warning of multiple faults. The experimental results show that the high-speed power line carrier communication module can effectively improve communication performance, achieving a communication success rate of over 99% and a transmission delay of less than 100 ms at a rate of 1 Mbps. In addition, the proposed model achieves an average accuracy of 98.2%, which is 3.7%∼12.4% higher than advanced models such as Transformer and XGBoost. Especially in the case of contact overheating faults, the F1 Score reaches 96.0%. On the STM32H743 microcontroller, the model’s single inference time is only 45.2 ms, with an average warning advance of 280.5 ms, fully meeting the real-time requirements of ‘warning trip’. This system significantly improves the accuracy of fault diagnosis and the timeliness of early warning, providing an efficient communication computing integrated solution for the intelligent upgrade and predictive maintenance of circuit breakers in low-voltage distribution networks.

This paper presents a procedure for calculating switching overvoltage on the main circuit breaker of a medium-voltage (MV) cable feeder, to which induction and/or synchronous generators are connected, during a three-phase short circuit. When a fault occurs, the feeder is disconnected by the circuit breaker located at its beginning. After the set operating time of the relay protection, since islanded operation is not permitted, the connected distributed generators will also be disconnected. It is shown that, during the period when the network is disconnected while the generators remain connected, the overvoltage factor reaches values between 2.2 and 2.5, depending on the types of generators and the location of points of common coupling. The individual transient responses of the distribution network and the mentioned types of distributed generators differ significantly. Using the superposition theorem, the calculation of switching overvoltage is demonstrated with elementary computer assistance.

Adding tiny amounts of tungsten (W) and graphene (Gr) in traditional Cu-Cr contact efficiently enhances the mechanical strength and breakdown strength of vacuum circuit breakers (VCBs). However, anodes made of W or W-alloy are acknowledged to harm the interruption performance of VCBs through impeding the post-arc recovery of vacuum gap by stronger surface emission. To investigate into the influence of W/Gr addition with a small mass ratio in Cu-Cr contact, this study employs molecular dynamics method to simulate anode behaviours during arcing and post-arc processes. Through the simulations, surface temperature and surface atom emission of the anode, which are perceived as the key phenomena affecting the post-arc recovery of vacuum, are used to assess the influence of material modifications on the interruption performance of VCBs. As a result, the existence of additional phases and the resulted interfaces are shown inevitably affecting the thermal processes of anode. Furthermore, this influence relates to the position, thickness, and orientation of the additional phases, and could be mitigated by limiting the size of the additional phases. Simulation results are validated by experiences of W usage in VCBs, as well as theoretical analysis of thermal processes of anode. Based on the simulation, suggestions on the material preparation of material modifications are provided to mitigate their influences on the interruption performance of VCBs.

The global phase-out of sulfur hexafluoride (SF6), an insulating gas with high global warming potential (GWP), has driven the search for eco-friendly alternatives in high-voltage equipment. Perfluoroisobutyronitrile (C4F7N) emerges as a promising candidate due to its low GWP and high dielectric strength. However, its chemical stability under circuit breaker conditions, especially when interacting with vaporized contact materials such as silver, remains a key concern. This study investigates the decomposition mechanisms of C4F7N in the presence of silver vapor using quantum chemical calculations at the B3LYP/LanL2DZ level. A reaction network comprising 35 pathways and 12 transition states were identified. All structures were confirmed as valid stationary points via frequency analysis and intrinsic reaction coordinate (IRC) calculations. Three primary reaction pathways between C4F7N and Ag were delineated, leading to secondary reactions that generate low-weight molecules and Ag-containing species such as AgF and AgCN. Key energy barriers and temperature-dependent equilibrium constants (Keq) were determined to evaluate pathway feasibility. This work provides fundamental insights into the high-temperature interfacial chemistry of C4F7N with Ag, offering essential data for assessing its material compatibility and long-term reliability as a sustainable insulation medium in power systems.

This comprehensive review examines the current state of cloud microservices architecture, synthesizing research findings, industry practices, and emerging innovations that define modern distributed systems. The analysis covers five critical domains: architectural patterns, container orchestration, service mesh communication, data consistency management, and security monitoring approaches. Through examination of quantifiable achievements including 58% error reduction via circuit breaker patterns, 30% energy savings with advanced orchestration, and successful zero-trust implementations, this review demonstrates the transformative potential of microservices architectures. Industry case studies from Netflix, Amazon, and Uber illustrate practical applications and lessons learned. The research identifies emerging trends in AI-driven automation, serverless integration, and hybrid architectural approaches that will shape future developments in cloud-native computing.

The structural integrity of circuit breakers in electrical systems is directly related to their resistance to high electromechanical forces generated during short circuits. In this study, the performance of alternative body materials for a molded case circuit breaker (MCCB) with a nominal current of 100A and a breaking capacity of 10 kA was evaluated using finite element analysis. Among the materials compared based on total deformation and von-Mises stress criteria, PPF GF (glass fiber- reinforced polypropylene) demonstrated the closest performance to BMC (9.40 mm, 604.82 MPa), with deformation values of 10.92 mm and stress values of 582.87 MPa. Among the other candidates, PA66 30GF (35% higher deformation) and PEEK/PEK (126% and 77% higher deformation, respectively) were found to be insufficient compared to BMC. Given that deformation is inevitable under short-circuit conditions, PPF GF is recommended as the most suitable alternative to BMC, thanks to its balance of mechanical strength and deformation resistance.

Analysis of Insulation Material Components in Low-Voltage Circuit Breakers According to Degradation Status

This paper presents a data-driven probabilistic framework for analysing power system faults using Monte Carlo simulations. The study evaluates the operational reliability of multiple high-voltage switchgear topologies—including single-busbar systems, double-busbar systems, and ring-type configurations—by modelling the stochastic behaviour of disconnectors, circuit breakers, busbars, and withdrawable switching elements with bypass arrangements. Realistic unavailability parameters derived from statistical reliability data are used to generate fault intervals for each device, enabling the simulation of millions of operational scenarios and capturing both full and partial outage events. The proposed methodology quantifies outage probabilities, identifies critical components, and reveals how devices count, switching logic, and system redundancy influence overall resilience. Results show significant reliability differences between topologies and highlight the importance of optimized substation design for fault tolerance. The developed probabilistic framework provides a transparent and computationally efficient tool to support planning, modernization, and predictive maintenance strategies in transmission and distribution networks. Findings contribute to improved fault diagnosis, enhanced grid stability, and increased reliability in both conventional and renewable-integrated power systems.

Abstract The phenomena of post-arc gap breakdown and the dielectric recovery process are crucial to the performance and reliability of vacuum interrupters and related equipment. In this paper, a two-dimensional particle-in-cell/Monte Carlo collision (PIC/MCC) simulation model is comprehensively used to study the diffusion process of the residual plasma in the post-arc stage of a vacuum circuit breaker . The research results show that under the action of the transient recovery voltage (TRV), the number of gap particles decreases, electrons dissipate faster than ions, an ion sheath layer is formed near the cathode, and the post-arc current first rises, then stabilizes, and then decreases. As the rise rate of the TRV increases, the speed of decrease in the number of electrons and ions accelerates, the current peak value increases, and the residual plasma dissipates faster. The introduction of the initial drift velocity accelerates the diffusion velocity of the post-arc plasma. Due to the opposite directions of the initial drift velocities of electrons and ions, the diffusion direction of ions is changed. After metal droplet is introduced, the diffusion speed of the post-arc plasma also slows down, the dissipation time of electrons and ions is delayed, the metal droplet hinders the plasma diffusion, and the gap electric field is distorted.