Search Results (1,481)

The widespread integration of inverter-based distributed generators (IIDGs) severely limits the adaptability of conventional three-step overcurrent protection in distribution networks (DNs). To address weak rural infrastructure and incomplete post-fault data, this paper proposes a dynamic adaptive current protection strategy for active distribution networks (ADNs) against two-phase short-circuit faults (TPSCFs), using local sequence components. First, we derive analytical expressions for positive/negative-sequence current/voltage at feeder outlet protection devices during TPSCFs, analyzing how the IIDG fault output affects these components. Based on this, an adaptive scheme is developed using only local measurements, with feeder head voltage/current sequence components as criteria. Leveraging line impedance and topology, the scheme ensures selective, accurate fault section identification under incomplete measurements, requiring only feeder head sequence data. A high-IIDG-penetration DN model is built in PSCAD/EMTDC, and TPSCFs under various conditions are simulated. Results show the scheme provides rapid, reliable full-line protection for TPSCFs in IIDG-penetrated ADNs, enhancing protection effectiveness. Full article

Accurate analysis of commutation phenomena in permanent magnet DC (PMDC) motors requires simultaneous consideration of electromagnetic field distribution and armature circuit dynamics. Classical circuit-based models are unable to properly capture transient effects occurring in short-circuited coils during commutation, while purely field-based models neglect the influence of the supply circuit. In this paper, a coupled field–circuit model of a PMDC motor with an innovative magnetic circuit based on rectangular NdFeB permanent magnets is presented. The model combines a two-dimensional finite element electromagnetic analysis with a segmented armature circuit and dynamic commutator switching, allowing the electromotive force to be computed individually for each coil based on the actual magnetic field distribution. The novelty of the proposed approach lies in the integration of a non-standard rectangular permanent magnet topology with a coil-resolved field–circuit commutation model, validated on a physical motor prototype. Simulation results are compared with experimental measurements obtained from a laboratory prototype at rotational speeds of 850 and 1000 r/min. The predicted electromagnetic torque shows good agreement with measurements, with deviations below 5%, while the armature current is estimated with an error of up to approximately 20%, primarily due to model simplifications. The developed model provides direct access to transient commutation waveforms and constitutes a practical tool for the analysis and design optimization of PMDC motors operating under dynamic conditions, particularly in cost-sensitive and reliability-oriented applications. Full article

Freshwater fish habitat simulation is a vital technology for assessing the state and dynamics of aquatic ecosystems under changing environments. Based on a comprehensive dataset spanning 1991–2024, this study constructs a domain knowledge map by integrating co-citation analysis, keyword burst detection, and social network metrics. The bibliometric results quantitatively identify leading contributors and trace the field’s exponential growth. Complementing this, a critical technical review reveals a significant paradigm shift in modeling methodologies: moving from traditional univariate suitability curves to advanced multivariate and artificial intelligence (AI)-based frameworks. Despite these advancements, our analysis highlights critical gaps in addressing habitat connectivity and broad environmental stressors. To overcome these limitations, we propose a novel framework that integrates landscape pattern indices with circuit theory to quantify habitat patch arrangement and ecological flows. Furthermore, we advocate for future research to explicitly incorporate climate change scenarios (e.g., thermal regime shifts) and geomorphological processes. This study offers both a macroscopic overview of the discipline’s evolution and a roadmap for developing robust, ecosystem-based management tools. Full article

In nanometer integrated-circuit (IC) manufacturing, advanced technology scaling has intensified the effects of process variations on circuit reliability and performance. Random fluctuations in parameters such as threshold voltage, channel length, and oxide thickness further degrade design margins and increase the likelihood of functional failures. These variations often lead to rare circuit failure events, underscoring the importance of accurate yield estimation and robust design methodologies. Conventional Monte Carlo yield estimation is computationally infeasible as millions of simulations are required to capture failure events with extremely low probability. This paper presents a novel reliability-based circuit design optimization framework that leverages deep transfer learning to improve the efficiency of repeated yield analysis in optimization iterations. Based on pre-trained neural network models from prior design knowledge, we utilize model fine-tuning to accelerate importance sampling (IS) for yield estimation. To improve estimation accuracy, adversarial perturbations are introduced to calibrate uncertainty near the model decision boundary. Moreover, we propose a cascaded batch Bayesian optimization (CBBO) framework that incorporates a smart initialization strategy and a localized penalty mechanism, guiding the search process toward high-yield regions while satisfying nominal performance constraints. Experimental validation on SRAM circuits and amplifiers reveals that CBBO achieves a computational speedup of 2.02×–4.63× over state-of-the-art (SOTA) methods, without compromising accuracy and robustness. Full article

While circuit parameter optimization has matured significantly, the systematic discovery of novel circuit topologies remains a bottleneck in analog design automation. This work presents SymXplorer, an open-source Python framework designed for automated topology exploration through symbolic modeling of analog components. The framework enables a component-agnostic approach to architecture-level synthesis, integrating stability analysis and higher-order filter exploration within a streamlined API. By modeling non-idealities as lumped parameters, the framework accounts for physical constraints directly within the symbolic analysis. To facilitate circuit sizing, SymXplorer incorporates a multi-objective optimization toolbox featuring Bayesian optimization and evolutionary algorithms for simulation-in-the-loop evaluation. Using this framework, we conduct a systematic search for differential Common-Gate (CG) Bandpass Transimpedance Amplifier (TIA) topologies tailored for 5G New Radio (NR) Radio-over-Fiber applications. We propose a novel, orthogonally tunable Bandpass TIA architecture identified by the tool. Implementation in 65 nm CMOS technology demonstrates the efficacy of the framework. Post-layout results exhibit a tunable gain of 30–50 dB$\Omega$, a center frequency of 3.5 GHz, and a tuning range of 500 MHz. The design maintains a power consumption of less than 400 $\mathsf{\mu }$W and an input-referred noise density of less than 50 pA/$\sqrt{\mathrm{Hz}}$ across the passband. Finally, we discuss how this symbolic framework can be integrated into future agentic EDA workflows to further automate the analog design cycle. SymXplorer is open-sourced to encourage innovation in symbolic-driven analog design automation. Full article

As distribution networks become increasingly intelligent, primary–secondary integrated distribution switches are replacing the traditional electromagnetic type. However, the high degree of integration intensifies inherent electromagnetic compatibility (EMC) challenges. This paper presents a field-circuit hybrid full-wave model to investigate switch characteristics during lightning strikes. A 3D full-wave model of the switch and a distributed parameter circuit model of the connecting lines are coupled via a network parameter matrix. This approach comprehensively accounts for the impacts of transmission lines and structural components on electromagnetic disturbances. Simulation and experimental results reveal that lightning strikes induce high-frequency damped oscillatory waves, primarily caused by traveling wave reflections along overhead lines. The characteristic frequency of disturbance is inversely proportional to the transmission line length. Additionally, internal components significantly influence this frequency; specifically, a larger voltage dividing capacitance in the voltage transformer results in a lower frequency. Model validation was performed using a 20 m transmission line setup. A 75 kV standard lightning impulse was injected into Phase B. At a distance of 500 mm from the voltage transformer, the measured radiated electric field amplitude was 14.12 kV/m (deviation < 5%), and the characteristic frequency was 1.11 MHz (deviation < 20%). These findings offer vital guidance for the lightning protection and EMC design of primary–secondary integrated distribution switches. Full article

A dynamic filtering system that can choose in real time between two different noise filters depending on the dynamics of the measured environment is presented. Unlike other adaptive filters approaches, this system does not require prior knowledge of the environment beyond noise characteristics. We implemented this system into a Brillouin optical time-domain analysis (BOTDA) sensing scheme using a closed-circuit control system for dynamic tracking of the Brillouin Frequency Shift (BFS) along the sensing fiber using a Proportional-Integral-Derivative (PID) controller. Through experiments and numerical simulations, we compare this method to the filtering capabilities of P and PI controllers chosen as optimal in a previous work for closed-circuit BOTDA (CC-BOTDA). Results show that the adaptive noise filter provides a dynamic response comparable to the other controllers, while increasing noise suppression by a factor between 30% and beyond 100%, showing how an adaptive system can improve suppression with only knowledge of the measurement noise. Full article

This paper presents a PSCAD-based analysis of short-circuit faults and protection characteristics in a real distribution-level microgrid that integrates a 1 MWh battery energy storage system (BESS) with a 500 kW power conversion system (PCS) and a 500 kW photovoltaic (PV) plant connected to a 22.9 kV feeder. While previous studies often rely on simplified inverter models, this paper addresses the critical gap by integrating actual manufacturer-defined control parameters and cable impedances. This allows for a precise analysis of sub-millisecond transient behaviors, which is essential for developing robust protection schemes in inverter-dominated microgrids. The PSCAD model is first verified under grid-connected steady-state operation by examining PV output, BESS power, and grid voltage at the point of common coupling. Based on the validated model, DC pole-to-pole faults at the PV and ESS DC links and a three-phase short-circuit fault at the low-voltage bus are simulated to characterize the fault current behavior of the grid, BESS and PV converters. The DC fault studies confirm that current peaks are dominated by DC-link capacitor discharge and are strongly limited by converter controls, while the AC three-phase fault is mainly supplied by the upstream grid. As an initial application of the model, an instantaneous current change rate (ICCR) algorithm is implemented as a dedicated DC-side protection function. For a pole-to-pole fault, the ICCR index exceeds the 100 A/ms threshold and issues a trip command within 0.342 ms, demonstrating the feasibility of sub-millisecond DC fault detection in converter-dominated systems. Beyond this example, the validated PSCAD model and associated data set provide a practical platform for future research on advanced DC/AC protection techniques and protection coordination schemes in real BESS–PV microgrids. Full article

Grid-forming converters have gained significant attention for their ability to form grid voltage and provide essential grid-supportive services. However, managing harmonics generated by nonlinear loads remains a critical challenge in weak grids. A single grid-forming converter active power filter offers limited compensation capacity, and under heavy nonlinear loading its performance is restricted by converter ratings, leading to reduced stability margins, higher harmonic distortion, and weakened voltage/frequency regulation. To overcome these limitations, this paper presents a novel distributed control approach for multiple-parallel grid-forming converters active power filters that integrates voltage and frequency regulation with scalable harmonic attenuation. The proposed method extracts harmonic components at the point of common coupling and generates harmonic voltage commands to each unit so the parallel units collectively create a near short-circuit impedance for harmonics, preventing harmonic currents from propagating into the grid. Beyond improved harmonic performance, the multi-unit system enhances effective inertia, damping, and short-circuit capacity while avoiding complex parameter tuning, enabling a simple and scalable deployment. Simulation results demonstrate effective harmonic attenuation at the point of common coupling and accurate active/reactive power sharing. Full article

With the increasing integration of renewable energy into power grids, voltage source converter-based high-voltage direct current (VSC-HVDC) stations often adopt hybrid grid-following (GFL) and grid-forming (GFM) control strategies to improve adaptability to varying grid strengths. In many existing schemes, the hybrid coefficient changes abruptly, which may produce large transient current overshoots and compromise the safe and stable operation of converters. An adaptive hybrid GFL-GFM control framework equipped with a hybrid coefficient transition regulation is proposed. Small-signal state–space models are established and eigenvalue analysis confirms stability over the considered short-circuit ratio (SCR) range. The regulating method is activated only during coefficient transitions and is inactive in steady-state, thereby preserving the operating-point eigenvalue properties. Dynamic equations of the converter current change rate are derived to reveal the key role of the hybrid-coefficient change rate in driving transient current overshoots, based on which a real-time hybrid coefficient regulating method is developed to shape coefficient transitions. Simulations on a 500 kV/2100 MW VSC-HVDC project demonstrate reduced transient current overshoot and power oscillations during SCR variations, with robustness under moderate parameter deviations as well as representative SCR assessment error and update delay. Full article

Hybrid supercapacitors possess high power and energy density, while the cascaded H-bridge converter features rapid response capability. Integrating these two components leads to an energy storage system capable of swiftly responding to power demands, effectively mitigating voltage and frequency instability in weak-grid renewable energy stations. Based on this system, in this paper, a novel automatic frequency–voltage regulation strategy is proposed. First, a fast fault severity detection method is proposed. It evaluates the system’s fault condition by monitoring the voltage response and generates auxiliary signals to enable subsequent rapid compensation of voltage and frequency. Subsequently, fast automatic voltage and frequency regulation strategies are developed. These strategies leverage real-time fault assessment to deliver immediate power support to weak-grid renewable stations following a disturbance, thereby effectively stabilizing the terminal voltage magnitude and system frequency. The effectiveness of the proposed method is validated through simulations. A grid-connected model of a weak-grid renewable energy station is established in MATLAB (2023b)/Simulink. Tests under various fault scenarios with different short-circuit ratios and voltage sag depths demonstrate that the proposed strategy can rapidly stabilize both voltage and frequency after large disturbances. Full article

This paper proposes a dynamic voltage restorer (DVR) based on a new three-phase multilevel inverter (MLI). An integral component of DVRs is the power electronic converter. At medium-to-high voltage levels, MLIs are the ideal converters for DVR applications because lower voltage-rated switches are used to generate high voltages, thus minimizing power losses. The proposed three-phase MLI generates 15 levels of load voltage per phase, using a reduced component count: eight lower-rated semiconductor power switches, four primary DC voltage sources, two auxiliary DC sources, and eight driver circuits per phase. Additionally, each phase features a low-frequency transformer with voltage-boosting and galvanic isolation capabilities. The switching sequence of the proposed MLI is simpler to execute using fundamental frequency control; this methodology provides reduced switching stress and reduced switching losses as merits. Structurally, the proposed MLI is less complex and thus scalable. The proposed DVR, based on three-phase MLI, efficiently offsets power quality problems such as voltage swell, voltage sags, and harmonics for balanced and unbalanced loads. The operational performance of the proposed DVR-MLI is verified by a simulation, using PSCAD software and an experimental prototype. Full article

Industrial aluminum-block heating processes exhibit nonlinear dynamics, substantial time delays, and stringent requirements for fault detection and diagnosis, especially in semiconductor manufacturing and other high-precision electronic processes, where slight temperature deviations can accelerate device degradation or even cause catastrophic failures. To address these challenges, this study presents a digital twin-based intelligent heating platform for aluminum blocks with a dual-artificial-intelligence framework (dual-AI) for control and diagnosis, which is applicable to multi-port aluminum-block heating systems. The system enables real-time observation and simulation of high-temperature operational conditions via virtual-real interaction. The platform precisely regulates a nonlinear temperature control system with a prolonged time delay by integrating a conventional proportional–integral–derivative (PID) controller with a Levenberg–Marquardt-optimized backpropagation (LM-optimized BP) neural network. Simultaneously, a relay is employed to sever the connection to the heater, thereby simulating an open-circuit fault. Throughout this procedure, sensor data are gathered simultaneously, facilitating the creation of a spatiotemporal time-series dataset under both normal and fault conditions. A one-dimensional convolutional neural network (1D-CNN) is trained to attain high-accuracy fault detection and localization. PID+LM-BP achieves a response time of about 200 s in simulation. In the 100 °C to 105 °C step experiment, it reaches a settling time of 6 min with a 3 °C overshoot. Fault detection uses a 0.38 °C threshold defined based on the absolute minute-to-minute change of the 1-min mean temperature. Full article

To solve slot temperature accumulation in high thrust density permanent magnet linear synchronous motors (PMLSMs), this paper proposes an additive manufacturing (AM)-based variable cross-section winding design for coating-cooled tapered PMLSMs. Integrating the magnetic circuit features of tapered PMLSMs and AM windings’ technical merits, the motor’s operating mechanism and electromagnetic distribution are analyzed. With the coating cooling structure as the thermal management foundation, simulation reveals the motor’s temperature distribution under water cooling, defining core slot thermal management requirements. A novel cross-section winding design is then presented: first, a lumped-parameter thermal network model quantifies the coupling between the winding cross-sectional area and slot heat source distribution; second, a greedy algorithm optimizes the winding cross-section globally to reduce the slot hot-spot temperature and suppress temperature rise. Validated by a fabricated tapered PMLSM stator prototype and static temperature-rise experiments, the results confirm that winding cross-section reconstruction optimizes heat distribution effectively, offering a new approach for temperature rise suppression in high thrust density PMLSMs. Full article

This study introduces a novel hybrid model for an electromembrane stack, unifying an equivalent electrical circuit model incorporating specific resistance ($R_M,R_s$) and capacitance ($C_{gs},C_{dl}$) parameters with an empirical fouling model in a single framework. The model simplifies the traditional approach by serially connecting N ($N=10$) ion exchange membranes (anionic PC-SA and cationic PC-SK) and is validated using $NaCl$ and $N{a}_{2}S{O}_4$ solutions in comparison with laboratory tests using various voltage signals, including direct current and electrically pulsed reversal operations at frequencies of 2000 and 4000 Hz. The model specifically accounts for the chemical stratification of the cell unit into bulk solution, diffusion, and Stern layers. We also included a calibration method using correction factors (${\alpha }_i$) to fine-tune the electrical current signals induced by voltage stimulation. The empirical component of the model uses experimental data to simulate membrane fouling, ensuring consistency with laboratory-scale desalination processes performed under pulsed reversal operations and achieving a prediction error of less than 10%. In addition, a comparative analysis was used to assess the increase in electrical resistance due to fouling. By integrating electronic and empirical electrochemical data, this hybrid model opens the way to the construction of simple, practical, and reliable models that complement theoretical approaches, signifying an advance for a variety of electromembrane-based technologies. Full article