Search Results (3,029)

Wireless communication above $300\mathrm{GHz}$ requires highly sophisticated analog circuit design due to severe frequency dependent ohmic losses. The complexity of such electronic hardware motivates exploring wireless quantum optical communication approaches even for the 6G “terahertz (THz) range” $\left[300\mathrm{GHz},10\mathrm{THz}\right]$. In this work, the classical radio frequency (RF)-based inner physical layer (PHY) transceiver blocks of channel coded wireless communication systems are replaced by wireless quantum optical transceiver blocks. Short range concepts employing LEDs as transmitters are particularly attractive, owing to their low implementation cost and practical simplicity. In contrast to laser based wireless quantum optical transmission over multipath channels, the quantum mechanical density operator ${\underline{\rho }}_{\mathrm{RX},[{\mathfrak{s}}_i,b_i]}$ and the transition probability $\gamma ({\mathfrak{s}}_i,{\mathfrak{s}}_{i+1})$ required by the quantum data detection must be revised accordingly. Furthermore, the novel interpretation introduced here, in which the extrinsic information is treated as a diversity branch rather than as an estimate of the a priori information, facilitates turbo equalization that still can accomodate varying a priori information. However, due to the limited uncoded transmission performance achievable with such systems, the incorporation of sophisticated channel coding schemes appears imperative. The authors therefore investigate the combination of sophisticated channel coding techniques, such as polar coding, with LED based wireless quantum optical transmission technologies. All numerical results assume a cryogenically cooled receiver front-end (approximately 10 K), yielding thermal noise levels. Operation at room temperature in the 6G THz range $\left[300\mathrm{GHz},10\mathrm{THz}\right]$ would require an average number ${\overline{N}}_{\alpha }$ of thermal noise photon values of approximately 5 to 20, which is beyond the scope of this feasibility study. The results show that the proposed paradigm enables simple, robust, and practically viable wireless quantum optical communication systems with favorable transmission performance. Additional gains are achieved through iterative turbo equalization. The results also suggest that the proposed approach can pave the way toward robust and economically viable future communication solutions. Full article

Solar insecticidal lamps are important physical control devices for green pest management, but faults in their photovoltaic power supply units can reduce trapping efficiency and shorten service life. To improve fault identification under complex agricultural environments, this study proposes a signal-image-level multimodal fusion network (SIL-MMFN) for detecting and classifying photovoltaic panel operating states in solar insecticidal lamps. The method combines time-series measurements with short-time Fourier transform (STFT)-based time–frequency images. A convolutional image branch extracts spatial features from time–frequency representations, whereas a bidirectional GRU branch with attention models temporal dependencies in the original signals. In addition, physics-informed features based on the illumination–current residual and output power are introduced to enhance discriminative fault information. Field data collected from four agricultural deployment nodes were used to classify normal, open-circuit, and mismatch states. Experimental results show that the proposed method achieved an accuracy of 97.5%, precision of 96.7%, recall of 97.8%, and macro-F1 score of 97.3%, outperforming single-modality and representative comparison models. The results indicate that multimodal fusion helps reduce confusion between open-circuit and mismatch faults and provides a potential approach for operating-state monitoring and maintenance of agricultural photovoltaic equipment. In this study, fault diagnosis refers to the detection and classification of photovoltaic panel operating states, including normal, open-circuit, and mismatch conditions. Full article

This paper proposes a novel fault-identification method for micro-coils in relays with forcibly guided contacts, a type of electromechanical elementary component (EMEC), combining a composite analytical model, a 2D thermal model, and a 1D-CNN. A low-order thermal circuit with one central node and four boundary nodes is established, while a two-dimensional anisotropic Poisson equation is used as a high-order calibration model. The two models are coupled through iterative correction of reusable thermal resistances. For thermal aging, enamel-film delamination, and inter-turn short-circuit faults, thermal-conductivity attenuation, asymmetric branch-resistance perturbation, and localized abnormal heat-source injection are introduced to generate physically constrained temperature sequences. Orthogonal centerline temperature distributions are extracted as one-dimensional feature vectors for 1D-CNN classification. Simulation results show that the hybrid model has an error of approximately 1.7% compared with finite-element results, and the trained 1D-CNN achieves 98.13% accuracy on 160 test samples. Experimental reconstruction and deep-feature visualization further verify its ability to distinguish normal, aging, delamination, and local short-circuit states. Full article

Computational Fluid Dynamics (CFD) was applied to an intermittent anoxic/aerobic Moving Bed Biofilm Reactor (MBBR) operated under six different aeration intermittency cycles and dissolved oxygen concentration levels. Experimental results showed that most aeration cycles did not provide a sufficiently long anoxic phase to sustain effective denitrification, thereby limiting NOx removal efficiency. This behavior was not adequately captured by simulations performed using conventional biological models (BioWin), which rely on the assumption of complete mixing. In contrast, the CFD model implemented in ANSYS Fluent 2024 R2 enabled a detailed characterization of reactor hydrodynamics and the identification of several inefficiencies, including short-circuiting, back-mixing, and the presence of dead zones. Notably, the simulations revealed a pronounced asymmetric distribution of carriers within the reactor, with the majority accumulating along one side, leaving a significant fraction of the reactor volume largely unoccupied. Further analysis indicated that this phenomenon was caused by a design flaw—specifically, the asymmetric placement of the aerators—combined with an excessively high air injection flow rate. Full article

Renewable energy is being increasingly integrated into power grids. As a result, the three-phase grid-connected inverter (GCI) faces power transfer limitations caused by small-signal stability issues. To improve energy utilization and enhance stability, this paper employs an impedance-based method to analyze the small-signal stability power boundary of the GCI. This boundary is then quantified using the generalized Nyquist criterion (GNC). Our analysis reveals that the power boundary decreases as the grid short-circuit ratio (SCR) decreases or the phase-locked loop (PLL) bandwidth increases. To address this problem, we propose an impedance reshaping method that cancels the negative resistance effect introduced by PLL feedforward. This approach raises the small-signal stability power limit to the rated power and ensures stable operation under grid impedance variations and high PLL bandwidth. Finally, impedance analysis and experimental verification confirm both the theoretical correctness and the practical effectiveness of the proposed method in extending the stability power boundary. Full article

To address the potential oscillation instability issues of grid-forming (GFM) inverter systems integrated into grids with reactive power compensation devices, an impedance-based model of the grid-connected system is established. The impedance analysis reveals that the compensation capacitors alter the grid impedance characteristics, leading to impedance crossover points with insufficient phase margin in the mid-to-high frequency range, thereby inducing oscillations. To address this, a negative capacitive and virtual resistive loop-based composite control strategy is proposed. The grid-side capacitive effects can be neutralized through the virtual negative capacitance, and the system damping is enhanced by a virtual resistive loop to maintain stable operation under varying short-circuit ratios. Hardware-in-the-loop experiments validate that the proposed scheme maintains stable operation under various capacitance switching and grid strengths, thereby enhancing the robustness of the GFM inverter in complex distribution network environments. Full article

Due to the low inertia and small internal resistance of the DC line, the short-circuit fault is more harmful to the DC microgrid than the AC microgrid. Therefore, rapid and accurate detection of faults in DC microgrids plays an important role in ensuring the stable operation of DC microgrids. In this paper, the residual generator is designed based on the state observer, and the fault diagnosis of the DC microgrid is achieved by analyzing and processing the residual signal. Firstly, a mathematical model is established for a single line, and the corresponding residual generator is designed by using the unknown input observer to achieve the fault detection of a single key protection line. Secondly, considering the high cost of fault detection for each line alone, a residual generator is established for the entire DC microgrid to achieve fault detection of the entire DC microgrid, which effectively reduces the cost of fault detection. Finally, the radial DC microgrid and the ring DC microgrid are simulated and verified respectively to ensure that the designed fault diagnosis method is applicable to both topologies. Full article

This paper presents a fast diagnosis and localization method for switch short-circuit faults (shoot-through faults) in three-phase current-source inverters (CSIs) based on the polarity and variation trends of normalized phase currents. Under short-circuit fault conditions, the variation trends of the two same-polarity phase currents change from opposite (normal) to identical. To capture this feature, an adaptive magnitude-normalization method is proposed, which adaptively distinguishes normal load variations from fault conditions and selects the corresponding normalization strategy, yielding constant-amplitude three-phase currents while retaining polarities and trends. The theoretical operating sector is determined from the current polarities, and the faulty switch is localized using the signs of the variation trends of the two same-polarity currents. The method applies to both single- and multiple-switch faults. Experiments on a 3 A, 50 Hz CSI prototype show an average localization time of 15 ms (0.75$T_{\mathrm{base}}$), accurate diagnosis under load (10–30 $\Omega$) and frequency (25–50 Hz) variations, and no need for additional hardware, confirming its effectiveness. Full article

This paper focuses on 220 kV cable sheath overvoltage caused by three typical operating conditions: harmonics, short-circuits, and lightning strikes. A sheath voltage simulation model on the 220 kV side is developed in PSCAD. Through multi-parameter scanning and sensitivity analysis, the overvoltage characteristics and key influencing factors are systematically studied, and engineering optimization strategies for sheath protector configuration are proposed for different types of overvoltage. Under harmonic conditions, a suppression circuit composed of discharge capacitance and discharge resistors is proposed to attenuate high-frequency disturbances. Under high-amplitude overvoltage conditions such as short-circuits and lightning strikes, the sheath protector configuration is optimized by adjusting cable length and grounding configuration. Under large current conditions, a parallel configuration scheme for sheath protectors is proposed from the perspective of energy absorption. Multi-condition simulations are conducted, and a simulation-based case study is carried out based on the actual layout and parameters of a traction substation cable line. The results show that the proposed strategies can effectively reduce the peak value of sheath overvoltage, providing simulation-based quantitative engineering guidance for the configuration of 220 kV cable sheath protectors based on sensitivity analysis results. Full article

Accurate prediction of external short-circuit (ESC) current is important for battery safety analysis and protection design, but conventional equivalent circuit models have difficulty reproducing the strongly nonlinear current evolution under ESC conditions. This study proposes a reaction-process-corrected second-order RC model for ESC current prediction, based on ESC experiments on a 37 Ah commercial NCM pouch cell at different initial SOCs. The ESC process is described by three successive stages: bottleneck control, concentration-difference control, and separator pore closure. To represent the transport-related resistance deviation during this process, an additional correction resistance R_x and a queued-charge descriptor Q are introduced into the equivalent circuit framework. A segmented closed-loop simulation strategy is then developed to update R_x and predict the ESC current. Using the 50% SOC case as an unseen validation case, the proposed model captures the main nonlinear characteristics of ESC current, including rapid initial decay, secondary rebound, and subsequent attenuation. The proposed framework improves the physical interpretability of equivalent-circuit-based ESC simulation while retaining engineering simplicity, providing a practical approach for safety-boundary assessment and protection-oriented battery system design. Full article

Under weak-grid conditions, grid-following (GFL) control of doubly fed induction generators (DFIGs) suffers from reduced stability margins, deteriorated dynamic performance, and intensified oscillations near the stability boundary. To address these issues, a pre-synchronized switching strategy between GFL and grid-forming (GFM) modes, triggered by locally measured operating variables, is proposed. Based on the GFL control model, the evolution of system dynamics with decreasing short-circuit ratio is analyzed, thereby elucidating how reduced grid strength progressively weakens robustness and disturbance rejection and eventually leads to instability. To characterize this deterioration, a set of normalized indices is constructed to quantify the oscillation levels of active power, phase-locked loop frequency, and point of common coupling voltage, enabling reliable identification of control-performance deterioration. A pre-synchronization scheme based on a virtual power closed loop is then developed, allowing the target mode to converge to the current operating point prior to takeover and enabling smooth bidirectional switching between GFL and GFM modes. Hardware-in-the-loop results demonstrate that the proposed strategy accurately detects GFL performance deterioration and effectively suppresses boundary oscillations while mitigating switching transients, thereby enhancing the adaptability of DFIGs to variations in grid strength. Full article

The increasing penetration of distributed generation (DG) in distribution systems poses significant operational challenges, including increased power losses, voltage profile deviations, and variations in short-circuit currents. These issues may compromise network safety, reliability, and the selectivity of protection schemes under different operating scenarios. This paper proposes a hybrid optimization methodology for the optimal placement and sizing of DG, aiming to minimize active power losses while ensuring voltage regulation and keeping short-circuit currents within permissible limits. An integrated approach is proposed that combines a mesh-to-radial network reconfiguration strategy with a modified Ant Lion Optimization algorithm, known as ALO-DG, enabling the simultaneous optimization of network topology and the allocation of distributed generators at candidate buses. The problem is formulated taking into account power balance constraints, voltage limits, distribution network capacity limits, and short-circuit current limits. The proposed methodology achieved substantial reductions in active power losses in the IEEE 33-bus and 69-bus test systems, reaching 84.42% and 91.56%, respectively. These improvements were accompanied by enhanced voltage profiles while preserving the radial operating structure of the distribution networks. Furthermore, the proposed hybrid methodology serves as a tool for the planning and operation of distribution systems with high DG penetration, particularly in scenarios where grid security and protection coordination are critical considerations. Full article

Large-scale integration of renewable energy sources and power-electronic equipment introduces substantial background harmonics into the grid and, at the same time, gives rise to weak-grid operating conditions with a low short-circuit ratio, thereby degrading the power quality and stability of grid-connected converters. This paper investigates a three-phase LCL-type grid-connected converter and establishes a dq-domain admittance model that incorporates the DC-voltage outer loop, the phase-locked loop (PLL), and grid-voltage feedforward. On the basis of admittance-reshaping theory, a method is proposed to suppress the influence of background harmonics and enhance system stability. First, the frequency coupling caused by the structural asymmetry of the PLL and the voltage outer loop is decoupled to reduce the harmonic components in the grid current. Then, based on the decoupled model, the grid-voltage feedforward path is compensated to eliminate the negative-damping region in the converter output admittance and thus improve system stability under weak-grid conditions. Finally, simulation and experimental results verify the effectiveness of the proposed method. Full article

As the global automotive industry is transitioning toward sustainable development, new energy vehicles (NEVs) have experienced rapid global growth due to their environmental friendliness and high efficiency. Global sales of NEVs are projected to reach 50 million units by 2030. Nevertheless, safety incidents caused by impacts on traction batteries remain a major factor restricting the development of NEVs. Prismatic batteries, which account for over 90% of the traction battery market owing to their high energy density and structural robustness, nevertheless continue to face significant safety challenges under mechanical loading conditions. Typical failure modes involve structural damage induced by external compressive forces during severe vehicular collisions, which can subsequently result in the tearing of internal electrode layers and rupture of the separator, thereby initiating internal short circuits and leading to severe incidents. Accordingly, this research focuses on the mechanism of structural damage transmission for prismatic lithium-ion batteries under compression conditions. By integrating a refined mechanical model, it further elucidates the structural failure mechanisms and conducts a microscopic analysis of the damaged battery structure to investigate the effects of varying damage levels on battery safety performance, providing significant guidance for the safety and reliability of new energy vehicles. Full article

Fault detection and diagnosis of three-phase inverter-fed motor drives is essential for ensuring system reliability, safety, and continuous operation in applications such as electric vehicles and industrial automation. This paper proposes a data-driven fault detection framework based on normalized current features and a lightweight bidirectional long short-term memory (BiLSTM) network which can be generalized to different motor power rating in the same controller system. A compact set of six time-domain features, consisting of the mean and root-mean-square (RMS) values of the phase currents, is extracted and normalized with respect to the average RMS value. This normalization effectively removes dependency on operating conditions, enabling the model to generalize across different load levels and motor power ratings without retraining. A lightweight BiLSTM architecture is employed, reducing computational complexity while maintaining high diagnostic performance. The proposed method is validated under various operating conditions, including different speeds, load variations, motor power ratings, and noisy conditions. The results demonstrate an overall classification accuracy of 99.65%, with reliable fault detection achieved within less than half of a fundamental cycle. The proposed approach provides an efficient, robust, and scalable solution for inverter fault detection and diagnosis, offering strong potential for practical deployment in modern motor drive systems. Full article