Due to tree growth and wind-induced disturbances, tree-contact arc grounding faults (TAGFs) occur frequently in distribution networks. In the initial stage of the fault, the fault signal is weak and can frequently be undetected by protective devices. Therefore, a multiphysics simulation model coupling arc plasma behavior with distribution system response is developed based on magnetohydrodynamic (MHD) theory. The influences of tree species, moisture content, and branch swing velocity on arc temperature, morphology, and fault current amplitude are analyzed. A time-domain energy balance analysis is conducted to reveal the mechanisms underlying current zero-crossing behavior. Experimental results validate the model's ability to accurately reproduce key TAGF features, including high fault impedance, arc temperature fluctuations, and neutral-point voltage oscillations. The findings provide a physically interpretable foundation for early detection and suppression of TAGFs in ungrounded distribution systems.

The interaction amomg multi-parallel grid-connected converters (MPGCC) in weak grid often leads to stability challenges. This paper presents a converter admittance-reshaping control method designed to improve the stability of the MPGCC system. Firstly, a generalized mathematical model of a three-phase MPGCC system, which incorporates the interaction between converters, is established and the small-signal model is emplogyed for analysis. It reveals that kdq1(s) and kdq2(s) must satisfy the Nyquist criterion in a MPGCC system, where kdq1(s) represents the series interaction between the main grid and the MPGCC system, and kdq2(s) represents the interaction amomg the converters. Considering the uniqueness of stability analysis for MPGCC systems, this study integrates admittance reshaping-matrices into the control structure of the converters using the positive real method. This approach ensures that both the output admittance matrix of the converter and its inverse matrix are strictly positive real, thereby achieving passivity in the two-dimensional admittance model of the three-phase MPGCC output. This theoretically guarantees the asymptotic stability of the MPGCC system, thereby improving system stability. Finally, simulations and experimental tests are conducted on a device omprising three parallel-connected grid-connected converters to validate the effectiveness of the proposed control method. This paper is accompanied by a video that demonstrates the validation results.

Virtual resistance (VR) has been shown to have a positive effect on the small-signal stability of grid-connected systems controlled by virtual synchronous generator (VSG). However, VR exacerbates the coupling effects between the active and reactive power loops, leading to larger oscillation amplitudes and longer settling times. In severe cases, voltage and current limits may be violated, potentially resulting in system shutdown. To address this issue, the dynamic power coupling matrix model and the steady-state equilibrium equations of the grid-connected VSG system are established to analyze both the dynamic and steady-state coupling characteristics between active and reactive power, and the different coupling effects between VR and line resistance are revealed. Voltage and power-angle feedforward decoupling factors incorporating VR are then developed to suppress the dynamic coupling induced by VR and line resistance. Furthermore, a voltage compensation block is developed to mitigate the steady-state coupling effect of active power on reactive power. Finally, experimental results verify that the proposed decoupling method achieves effective decoupling, significantly improving both the dynamic and steady-state regulation performance of the system, while preserving the positive effect of VR on grid-connected stability.

Line-commutated-converter based high voltage direct current (LCCHVDC) systems are susceptible to commutation failure (CF) under AC faults, posing a severe threat to power grid stability. Under asymmetric faults, different commutation processes (CP) exhibit varying CF risks due to significant differences in commutation voltages. This paper analyzes the impact of advanced firing on commutation processes and the CF risk for individual CPs under asymmetric faults, pointing out that for low-risk CPs, the benefit of reduced reactive power consumption without advanced firing outweighs the benefit of implementing advanced firing to ensure successful commutation. Thus, a novel method is proposed to enhance CF resistance capability by optimizing advanced firing application. To verify the effectiveness of the proposed method, it is applied to both direct and indirect advanced firing control approaches. Simulations are conducted in PSCAD/EMTDC using the CIGRE benchmark model and a dual-infeed HVDC model. The results of waveforms and Commutation Failure Immunity Index (CFII) comprehensively demonstrate that the proposed method effectively mitigates CF while maintaining good applicability across diverse operational scenarios.

In modern smart grids, accurate and synchronized time signals are essential for effective monitoring, protection, and control. Various time synchronization methods exist, each tailored to specific application needs. Widely adopted solutions, such as GPS, however, are vulnerable to challenges such as signal loss and cyber-attacks, underscoring the need for reliable backup or supplementary solutions. This paper examines the timing requirements across different power grid applications and provides a comprehensive review of available time synchronization mechanisms. Through a comparative analysis of timing methods based on accuracy, flexibility, reliability, and security, this study offers insights to guide the selection of optimal solutions for seamless grid integration.

Modular multilevel matrix converters(M3C) are widely used in medium and high-voltage large-capacity power conversion due to their easy-to-design structure, great output waveform quality, and no need for transformers. However, when the input and output frequencies are equal, the direct AC-AC conversion leads to unstable energy in the bridge arm branchs. In this paper, a multi-frequency combination capacitor voltage stabilization control strategy is proposed, which adopts the combination of symmetrical circulating current and common mode voltage multifrequency components, and establishes the relationship model between transient power of the bridge arm and the control variables. Finally, through the hardware-in-the-loop experimental platform, when a single-phase grounding fault occurs in the distribution network, the M3C device is put into operation, which can realize reliable arc suppression and the capacitive voltage fluctuation of each bridge arm is relatively balanced, which verifies the correctness and effectiveness of the proposed method.

The operation and maintenance data of distribution cables includes multiple dimensions such as operation data, operation environment, test conditions, and manufacturing processes. Moreover, different factors have distinct characteristics, making it difficult to achieve a high prediction accuracy rate relying on a single model. To this end, this paper proposes a high-risk distribution cable identification method that integrates Bayesian and BP neural networks. It combines the advantage of the Bayesian model in special processing of the weights of influencing factors and the advantage of the BP neural network in high processing accuracy of nonlinear factors, achieving accurate identification of high-risk cables, improving the early detection rate of cable faults, and ensuring the reliability of power supply.

As an eco-friendly, sustainable, and safe energy supplier, an electric renewable energy system that includes solar, wind, hydro, and fuel cells can stave off catastrophic climate change. However, evolving components, such as renewable generation, ultrahigh-voltage transmission, distributed energy storage, and electric vehicle charging loads, continuously incorporated in such systems will significantly expand power segments/categories along with relevant event types and then raise the complexity of system topologies, flows, and operations. Escalating power intermittencies or even outages need to be handled in the face of proliferating unforeseen accidents, extreme weather, and equipment deficiencies, which requires more intelligent, automatic, and adaptable inspection and maintenance. With this motivation, a framework that combines a space–air–ground integrated network and a communication–navigation–sensing fusion module for a wider coverage risk observation is proposed. The architecture presented in this framework amalgamates space-, air-, and ground-based monitoring resources to ameliorate the coordination among communication, navigation, and remote-sensing detection functions, ensuring complementary advantages in observation coverage, depth, and speed. Next, a fusion procedure for the space–air–ground collected multisource heterogeneous data is built, and key risk factors can be distinguished from complex information scenarios in a correlation pattern exploration ensemble. Furthermore, dissimilar risk levels from diverse types of faults in each power segment or category will be quantified in a merged and unified manner through a twofold component importance evaluation ensemble. An empirical case study is also conducted to validate the framework’s performance and feasibility within real applications.

The increasing penetration of renewable energy sources reduces system inertia, leading to potential frequency instability during disturbances. Virtual inertia is essential to maintain system stability, with Battery Energy Storage Systems being a key technology due to their rapid response capabilities. However, the impact of varying power injection profiles on the equivalent inertia of BESS remains underexplored. This paper uses the Texas 2000 Synthetic Electric Power Grid as a benchmark to analyze the relationship between nadir frequency and system inertia, forming the basis for equivalent inertia calculations. By adjusting operational parameters such as time delay, injection duration, and ramping rate, the study quantifies their influence on BESS equivalent inertia. Results demonstrate that optimized control strategies enable BESS to effectively replicate physical inertia, ensuring stable operation of power systems with high renewable energy penetration.

Asymmetric ground parameters (AGPs) of the distribution system impact fault handling, not only causing false triggers potentially, but also leading to arc extinction failures of traditional arc suppression methods. Therefore, this article analyzes the characteristics of the AGPs distribution network integrated with power router (PR) in depth. And an effective resistance-capacitance impedance midpoint grounding is innovatively designed on dc side of PR, without changing the grid grounding mode by control. Thus, novel methods of PR-based active parameters asymmetry identification (APAI), and single line-to-ground (SLG) faults flexible voltage arc suppression (FVAS) considering AGPs, are proposed under the VdcQ-0, which ensures the zero-sequence decoupling regulation. First, AGPs characteristics are actively detected by interfrequency signal injection (IFSI) via PR, and APAI is initiated to identify the primary cause of the asymmetry by interfrequency damping ratio. Then, if judged as an SLG fault, PR-based FVAS is employed to actively reduce the fault voltage below re-arcing threshold, the compensation mechanism considers AGPs. Finally, simulation and experiment results demonstrate the validity of the proposed 0-axis control under VdcQ-0, verify the feasibility and effectiveness of PR-based APAI and FVAS.

Electricity theft users with zero electricity usage (UZEU) should be specifically concerned in electricity theft detection (ETD) research. The challenges are: they provide no effective information on electricity usage behaviors, and they are easily confused with vacant house users. This has caused the majority of the existing detection methods relying on single electricity usage to fail to identify UZEU accurately. Hence, this article first analyzes the underlying correlation between water and electricity (W&E) usage collected by the smart meter. This analysis then lends the theoretical basis to propose a new ETD method by comprehensively using the multisource information. More precisely, the proposed method utilizes the mutual information coefficient (MIC) to construct a correlation model between W&E usage and in turn the wavelet clustering algorithm to cluster the MIC of the power distribution users. Thereafter, the resulting weak correlations indicate the suspected users as the electricity theft UZEU in case of zero electricity usage. Finally, the proposed method is validated by numerical experiments in the real world and illustrated to be more accurate than existing methods in detecting UZEU.

In the field of new energy electric vehicles, ultracapacitor modules are often used as energy storage batteries. Precise estimation of state of charge (SOC) of ultracapacitor modules is critical to the secure operation of vehicle power supply. In this paper, equivalent circuit models and SOC estimation algorithms are compared and analyzed. The forgetting factor recursive least squares (FFRLS) is employed to supply precise equal circuit model parameters for SOC estimation algorithm. On this basis, an improved Sage-Husa adaptive unscented Kalman filter (IAUKF) online SOC estimation algorithm is proposed. The improved unscented Kalman filter algorithm solves the problems of poor robustness and large computational effort of the conventional Sage-Husa adaptive unscented Kalman filter algorithm (AUKF). The experiment verification is carried out in UDDS test and FUDS test respectively. The experiment verified that the SOC estimation error of IAUKF algorithm is less than 1.076%, and the average relative error is reduced by more than 50.574% compared with the conventional algorithms. The FFRLS-IAUKF joint SOC estimation algorithm has high estimation accuracy and good robustness.

The weak spots in an integrated energy system that may jeopardize the overall reliability call for timely and efficient Inspection and Maintenance (I&M). One core step is the reasonable allocation and deployment of limited I&M personnel or apparatus to the regions or periods with higher event risks, which requires a pinpoint spatiotemporal distribution forecast of future vulnerabilities. This paper presents a hybrid forecast methodology, the Saliency-Rough Fuzzy Utility Pattern recognition ensemble, in light of space-air-ground multi-source-heterogeneous input data. A parallel learning architecture is established and identifies the critical components with higher yields to enhance efficiency. Accordingly, more reasonable quantitative and qualitative evaluations can be carried out concurrently. Potential imprecise and uncertain data scenes are handled in quantitative assessments, both the failure hazard path sets and survival function likelihood boxes are incorporated in the designed relative path-Fussell Vesely Saliency (rp-FVS) model; and in qualitative analyses, the underlying perilous components can be distinguished via a combination of the variable precision-rough model. The rp-FVS-based fuzzy inference logic configures all membership functions identically according to components’ impacts. These two parts are integrated into the rough-fuzzy Utility Measure to discover concealed component-vulnerability interconnection patterns. Finally, an empirical case study is conducted for validation.

To solve the problem of single line-to-ground fault in distribution network (DN), this paper proposes an active voltage arc suppression method based on modular multilevel converter (MMC). However, how to maintain branch energy balance is a difficult problem in the application of MMC. Aiming at this problem, a branch energy balance control method based on circulating current and common mode voltage injection is proposed. Under the proposed method, there is no coupling between adjustment quantities in the system control, which reduces the design difficulty of controllers. On the output side of the system, the MMC can output high-quality alternating current, and the effect of arc suppression is obvious.

When the number of sub-modules (SMs) in modular multilevel converter (MMC) is large, the simulation speed usually slows down significantly. In this paper, we propose a fast electromagnetic transient (EMT) modeling to solve this problem. In this paper, the equivalent MMC model is derived based on Thevein theorem, on the basis of which, control strategy is designed. Nearest Level Modulation (NLM) is selected as modulation strategy of MMC. Output current and circulating current are selected as the controlled variables of MMC closed-loop control. In this paper, after constructing the EMT model, simulation tests are conducted under three operation conditions in MATLAB/Simulink software to verify the feasibility of proposed model. It can be drawn that compared with original circuit, the proposed model accelerates the simulation speed of MMC and performs excellently in output current tracking and SM capacitor voltage balance.

To ensure the reliability of distribution network under single-line-to-ground (SLG) fault, the active voltage arc suppression (AVAS) method is usually adopted to suppress the arcs. However, its performance is unfavorable as the line impedance is practically not neglectable, especially when the low-resistance SLG fault occurs. For improvement, the active current arc suppression (ACAS) method is used as a supplement to effectively eliminate this shortcoming. Therefore, this paper proposes a composite arc suppression method, which combines the AVAS and ACAS method to suppress arc. Firstly, the limitation of AVAS method is analyzed. It is found that the residual current after AVAS can be presented by post-fault zero-sequence voltage. Then, a zero-sequence voltage threshold is set to distinguish which type of method should be adopted. When the zero-sequence voltage less than the voltage threshold, the AVAS method is adopted. When the zero-sequence voltage is larger than the voltage threshold, the ACAS method is used. The simulation results show that the proposed method has good arc suppression performance under different fault locations.

Different line resistances between battery energy storage systems (BESSs) and the bus cause the problem of state-of-charge (SOC) unbalance between the batteries. SOC unbalance brings about battery over-charge or over-discharge, which reduces the battery life. This paper proposes an SOC feedback control strategy to achieve both output power sharing and SOC equalization between the BESSs. The average SOC of the batteries is set as the reference of each SOC control loop, and the control objectives are achieved by regulating the output voltage of the energy storage converters. The state space model of the proposed control method is established for stability analysis and control parameter design. The parameters are then designed in detail according to the dynamic and steady-state performance. Simulation and experiment verified that the proposed control strategy can achieve accurate SOC equalization and output power sharing when the line resistances and the battery capacities are different.

在单相接地故障和接地故障消弧的分析中,通常假设配电网是三相平衡的.已有的消弧方法在对地参数和负载不平衡的配电网单相接地故障时消弧效果不佳.针对上述问题,提出一种计及线路阻抗和配电网参数不平衡的电压消弧方法.分析考虑配电网参数不平衡和线路阻抗的配电网等效模型,推导出精确电压消弧指令值,通过故障前后各注入一次电流计算电压指令值,有源消弧装置调控零序电压至该指令值从而抑制故障点电压、电流为0.为了避免任意注入电流引起故障电流增大,将传统电流消弧作为电压消弧的过渡能有效补偿故障电流.通过和已有考虑线路阻抗电压消弧方法、忽略线路阻抗电压消弧方法对比,仿真结果表明,在不同的不平衡度、故障位置和接地电阻下,所提方法消弧性能最佳.

Conventional cascaded H-bridge power amplifier (CHB-PA) with N H-bridge power modules (HBPMs) could create 2N+1 level for output voltage at most and the output voltage level directly affects the sinusoidal characteristic and fidelity performance of power amplifier. With the same number of cascaded HBPMs, this paper proposes an asymmetrical cascaded multilevel power amplifier (ACM-PA) in which the voltage of one HBPM is one-third of the voltage of the other HBPMs, reducing the withstand voltage level of the HBPM. A virtual carrier phase shift pulse width modulation (VCPS-PWM) strategy is also proposed for ACM-PA to increase the output voltage level up to 6N-3 with the HBPM number as the same as conventional CHB-PA. Comparative simulation and experimental results are included to validate that the proposed ACM-PA and VCPS-PWM could obviously increase the output voltage level and decrease the total harmonic distortion (THD) of load current, improving the fidelity performance of power amplifier.

Existing voltage-type arc suppression method compensates fault current without considering line impedance. When metallic single line-to-ground (SLG) fault occurs, residual current of fault location rises instead of falling with conventional method, resulting in the failure of arc suppression. To solve this problem, combined current-type and voltage-type arc suppression method, a hybrid method is proposed in this paper. The distribution network is analyzed when considering line impedance and load. According to this, the current and voltage references for active arc suppression device (ASD) are derived for accurate arc suppression. The grounding resistance is estimated by zero-sequence current and voltage of the system. When it is larger than a setting threshold, voltage-type arc suppression method is adopted. Otherwise, current-type method is adopted. The proposed method can reduce fault current to almost zero. The correctness of the proposed method is validated and comparison is presented by simulation in the MATLAB/Simulink environment.