With remarkable features of low-cost, high-reliability, low-losses and light-weight, diode rectifier unit (DRU) and modular multilevel converter (MMC) based multiterminal dc system (DRU-MMC-MTDC) is a promising solution for offshore wind power transmission. DC chopper (DCC) and hybrid dc circuit breaker (HCB) are two different and essential facilities in the DRU-MMC-MTDC system for onshore ac and offshore dc fault ride-through, respectively. Considering that the structures of DCC and HCB are quite similar, in which the solid-state switches (SSSs) are the most expensive parts, emerging DCC function and dc interruption function seems to be a promising method to improve the utilization rate of SSSs. To realize this goal, the contributions of this paper is: DCC function extension method of HCBs is proposed, enabling HCBs to ride through both onshore ac and offshore dc faults. The working principle is: with MMC bypassed under an onshore ac fault, by tripping HCBs, part of the metal oxide varistors can serve as DCC to absorb the surplus power, so that no independent DCC is needed. Simulations and experiments are conducted for verification. The comparison between the proposed method and the conventional method of installing both DCC and HCB shows that the proposed method can save equipment investment and reduce control complexity in comparison with DCC.

Three-phase adaptive auto-reclosing is crucial for rapid power restoration after high-voltage AC line faults. However, in islanded wind farms integrated via modular multilevel converter-based high-voltage direct current (MMC HVDC) systems, a three-phase trip on the single-circuit AC outgoing line deprives the wind farm of voltage support, risking immediate disconnection. Furthermore, the rapid decay of line electromagnetic energy renders passive fault identification methods ineffective. This paper analyzes the wind farm's overvoltage and frequency instability mechanisms during grid loss operation, proposing a short-term uninterrupted operation strategy. Subsequently, an active signal injection method is proposed, utilizing the open-loop control of the sending-end MMC to generate a small-amplitude probing voltage. To analyze this injection process, the positive- and negative-sequence equivalent models of the MMC within the submodule capacitor discharge loop are derived to determine the safe probing voltage boundary and construct a transient fault identification criterion based on discharge current amplitude. Additionally, a coordinated strategy integrating the auto-reclosing process with the control of power electronic sources at both ends is developed. Simulations verify that the scheme prevents injection-induced overcurrents during severe faults while maintaining high sensitivity for high impedance faults, thereby facilitating rapid power restoration and significantly enhancing system reliability.

The two-level voltage-source converter (2L VSC) is the key equipment in a microgrid. However, power electronic devices in VSC are vulnerable to surge current under DC faults. Up to now, existing methods to deal with DC faults cannot balance fault current elimination performance and investment. To solve this problem, by adding a unit with a thyristor anti-parallel with a diode in the up-or down-bridge-arm of each phase, an improved 2L VSC with DC fault ride-through capability is proposed in this paper. The topology and working principle of the improved VSC are presented. The parameter design method of the proposed 2L VSC is discussed in terms of current and voltage requirements during DC fault ride-through. The simulation and experiments are carried out for verification, and the results are consistent with the theoretical analysis, showing that the fault current inside the proposed VSC could be eliminated within 1ms, and there are no overcurrent or overvoltage issues. In the end, comparisons between the proposed method and the existing methods are presented to prove the superiority of the proposed 2L VSC.

With the continuous advancement of power electronic equipment and the widespread integration of distributed generation, distribution networks composed entirely of converter-based generators have become one of the key development approaches for low-carbon and flexible modern distribution systems. This paper investigates a short-circuit calculation method for 100% converter-based generator distribution networks with system voltage established by V/f-controlled converters and multi-point grid-following distributed generation integration. The limitations of the widely used fixed-point iteration method in short-circuit calculations for active distribution networks are analyzed. The intrinsic relationships between the capacity of V/f-controlled generators, the capacity and connection locations of grid-following distributed generators, the magnitude of fault resistance, and the convergence behavior of the fixed-point iteration sequence are revealed. To address the convergence issues of traditional iterative algorithms caused by the capacity of converter-based generators and fault conditions, a short-circuit calculation method based on outer-layer voltage approximation and inner-layer spectral gradient iteration is proposed. The global convergence of the proposed method is mathematically proven. A case study involving a 100% converter -based generator distribution network with five converter-based generator nodes is conducted. A simulation model is built in PSCAD/EMTDC to simulate fault scenarios. The effectiveness and superiority of the proposed method are validated by comparing the short-circuit calculation results with simulation results and benchmarking against fixed-point iteration methods.

As key equipment in medium voltage DC (MVDC) systems, modular multilevel AC/DC and DC/DC converters (MM-AC/DC, MM-DC/DC) have drawn marvelous attractions. However, research on DC fault ride-through focuses on MM-AC/DC, and the fault current elimination for MM-DC/DC remains a research gap, which limits the wide application of the MVDC system. To fulfil this research gap, the contribution of this paper is revealing the fault current characteristics of MM-DC/DC based on half-bridge and full-bridge submodules (HBSM and FBSM) and proposing a novel MM-DC/DC based on hybrid HBSM and thyristor-diode module (TDM). By integrating TDM in the upper bridge arm of one phase and the down bridge arm of the other phase in MM-DC/DC, the MM-DC/DC achieves self-elimination of fault currents. The basic concept is using the energy at the healthy side to modulate a reverse voltage source (RVS) at the faulty side of MM-DC/DC, forcing fault current through TDM pass across zero. TDM can extinguish the resulting fault current. The parameter design and control strategy of the novel MM-DC/DC are discussed. Simulation is carried out for verification, and the results show that fault current can be eliminated within several milliseconds without causing excessive operating losses and costs.

Accurate load forecasting is essential for ensuring the economic and reliable operation of integrated energy systems （IESs）. However， the nonstationarity， dynamically time-varying coupling， and high stochasticity of multivariate loads pose significant challenges to load forecasting. To address these issues， this paper proposes a probabilistic forecasting method based on multivariate variational mode decomposition （MVMD） and a dynamic hybrid graph attention network. First， MVMD is employed to synchronously decompose the original load sequences， enabling cross-series phase synchronization and modal alignment among multivariate loads. This process smooths the data while preserving the intrinsic temporal coupling characteristics between load series. Second， a dynamic hybrid graph attention network is designed. Through a gating mechanism， physical prior static graphs and a meteorology-driven dynamic graphs are adaptively fused， and spatiotemporal graph convolution is incorporated to extract higher-order time-varying coupling features. Finally， a quantile regression-based probabilistic output layer is constructed， extending conventional point forecasting to full probabilistic distribution forecasting. Experimental results based on the dataset from Arizona State University demonstrate that the proposed method effectively quantifies load uncertainty and significantly outperforms several benchmark models in forecasting performance.

Detecting inter-turn short circuits in ultra-high voltage shunt reactors is challenging due to weak fault signatures. This paper establishes an accurate three-segment fault model and derives, for the first time, explicit analytical expressions for the short-circuit phase equivalent resistance $(\boldsymbol{R}_{\mathbf{eq}})$ as a function of both short-circuit turn ratio $(\boldsymbol{\alpha})$ and transition resistance $(\boldsymbol{R}_{\mathbf{k}})$. In particular, this model reveals specific $\boldsymbol{R}_{\mathbf{eq}}$ variation laws: monotonic decrease with $\boldsymbol{\alpha}$ for metal faults and non-monotonic behavior for transition resistance faults. Leveraging these insights, an innovative identification method is proposed. Its core innovation is a theory-driven, flexible threshold $(\boldsymbol{R}_{\mathbf{set}})$ calculation based solely on the derived $\boldsymbol{R}_{\mathbf{eq}}=\boldsymbol{f}(\boldsymbol{\alpha},\boldsymbol{R}_{\mathbf{k}})$ function and user-defined pa-rameters (minimum detectable $\boldsymbol{\alpha}_{\mathbf{min}}$ and maximum tolerable $\boldsymbol{R}_{\mathbf{k}\_\mathbf{max}}$), thereby reducing reliance on empirical values. Simulation results validate the proposed model and method, demonstrating superior sensitivity and ac-curacy, especially for small-turn inter-turn short circuits with transition resistance, compared to conventional ze-ro-sequence methods. This provides a robust theoretical foundation for practical fault detection.

Aiming at the challenge that conventional protection devices struggle to rapidly and accurately detect sub-synchronous components within a short data window during sub-synchronous oscillations (SSO), this paper proposes a detection method based on half-cycle superposition reconstruction and multi-scale inverse identification. Leveraging the half-wave symmetry of power-frequency signals, the power-frequency components are rapidly eliminated in the time domain via half-cycle delay superposition, reconstructing a signal that exclusively retains sub-synchronous information. A parameter mapping relationship between the reconstructed and original signals is established to inversely identify the true frequency and amplitude of the sub-synchronous components. To overcome "small-angle" numerical ill-conditioning and zero-crossing singularities at high sampling rates, an optimal calculation point selection and multi-scale parallel step calculation mechanism are developed. Combined with a dual statistical fusion strategy of "median + extreme-value-removed average," the interference of stochastic noise on the identification process is effectively suppressed. Simulation results on the MATLAB platform demonstrate that the proposed method achieves high detection accuracy and robust noise immunity across the entire sub-synchronous frequency band, meeting the requirements for rapid relay protection.

Aiming at the uncertainty of power flow in low-voltage distribution networks under high-penetration distributed photovoltaic integration scenarios, this paper proposes an improved probabilistic power flow calculation method for low-voltage distribution networks using Latin Hypercube Sampling and optimized by an Error Bound Method (EBM). The unique ABC three-phase + N-line structure and asymmetric source-load characteristics of low-voltage distribution networks are analyzed. The Latin Hypercube Sampling-based probabilistic power flow algorithm is employed to achieve probabilistic characterization of system power flow distribution, with the sampling scale optimized via the EBM. A 25-node low-voltage distribution network model is built in MATLAB to verify the effectiveness of the proposed method.

DC fault in diode-rectifier (DR) based MMC-HVDC system causes significant offshore AC voltage drops, threatening the stability of grid-forming (GFM) wind turbines (WTs). This paper first analyzes the mechanism of offshore AC voltage drop induced by DC faults, and reveals the reasons for overcurrent and loss of active power control. Secondly, a DC fault ride-through (FRT) strategy is proposed to improve the FRT capability, which comprises power reference modification and additional feedforward control. The proposed strategy effectively limits voltage and frequency deviations within 6%, restores active power controllability within 50 ms, and limits overcurrent to below 1.2 p.u. during DC faults. Thirdly, an additional pitch angle control is proposed to eliminate the excessive power and enhance the response speed of both pitch angle and rotor speed. Finally, leveraging the passivity-based control method, an improved inner current control loop is proposed to enhance the dynamic and static performance of the GFM WTs during DC faults. Various case studies performed on PSCAD/EMTDC and RTDS validate that the proposed strategy significantly improves the stability and FRT capability of GFM WTs compared to existing strategies.

The paper focuses on single-neutral-point low-resistance grounding (SNP-LRG) active distribution networks (ADNs) where the distribution system adopts the low-resistance grounding mode, and distributed generation (DG) grid-connected transformers adopt the ungrounded mode. The study analyzes the characteristic relationship between zero-sequence voltage and current at switches on the main line and branch lines during positive and negative direction single-phase ground faults. Based on this analysis, a directional discrimination principle for single-phase grounding faults using direction-indicating voltage (DIV) and a corresponding fault section identification method is proposed. The impact of transition resistance (TR) and DG capacity on the proposed method is analyzed, and a calculation method for the maximum allowable measurement error boundaries (MAMEBs) under different TRs is proposed. Simulation results demonstrate that the proposed method can achieve accurate and reliable section-level ground fault identification even with a TR of 3000 S2, unaffected by arc discharge phenomena during ground faults or the integration of DG. Compared to the widely proposed phasebased detection methods for SPGFs, the proposed method maintains accurate judgment at a TR of 3000 S2 while significantly enhancing adaptability to grid topology changes and DG integration. Furthermore, this study quantifies the MAMEBs for measurement equipment, providing clear guidance for the selection and evaluation of measurement devices in engineering applications. Simulations confirm that the proposed method ensures accurate fault section identification at a TR of 3000 S2 when considering a measurement absolute error of 0.0244 kV.

High impedance faults (HIF) in the resonant grounding system of distribution networks pose significant challenges for traditional protection devices, which often fail to detect and eliminate these faults promptly. The difficulty in setting an appropriate threshold and ensuring reliable detection at low signal-to-noise ratios further complicates the issue. To overcome these limitations, this paper presents a novel approach that analyzes the kurtosis and skewness characteristics of the single-phase high-impedance grounding zero-sequence current waveform, using the Emanuel model as a basis. The proposed method detects HIF based on a kurtosis threshold and pinpoints the faulted line using the skewness coefficient, introducing a more reliable and precise detection technique. Simulation and field tests validate the robustness of this approach, demonstrating strong resistance to noise interference and enhanced fault detection capabilities.

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.

Given the inherent three-phase four-wire structure and the prevalent three-phase unbalance in low-voltage distribution networks (LVDNs), existing power flow algorithms face challenges such as decoupling difficulties, inadequate consideration of neutral wire effects, and cumbersome iterative formulas. To address these issues, this paper proposes a decoupled power flow calculation method based on matrix order reduction for LVDNs with distributed generation (DG). First, a comprehensive LVDN model incorporating the neutral wire is constructed, encompassing models for lines, transformers, ZIP loads, and distributed PV. Subsequently, a mathematical transformation is applied to the nodal admittance matrix to achieve order reduction, where the neutral wire parameters are reduced to the phase conductors to eliminate the corresponding rows and columns. Furthermore, a phase-sequence transformation is utilized to achieve sequence-component decoupling of the third-order matrix, thereby establishing the decoupled nodal voltage equations. Concurrently, a sequence-component-based forward–backward sweep (FBS) method is designed for power flow solving. Finally, a 22-node LVDN model with distributed PV is built in MATLAB/Simulink for case verification. The results demonstrate that the proposed method can accurately reflect the asymmetric operational characteristics of LVDNs. Compared with the traditional phase-component method, it effectively simplifies the calculation process and significantly enhances computational efficiency while maintaining high accuracy, providing efficient algorithmic support for the precise regulation and optimal operation of LVDNs with DG.

In line with the latest protection configuration requirements for 35 or 10 kV distribution grids, current differential protection is recommended for distribution lines connected to photovoltaic power sources. However, unlike traditional synchronous generators, photovoltaic power sources provide fault currents with amplitudes typically less than 1.2 to 2 times the rated current, and their phase angles are controlled and capacitive. This often results in the differential current being insufficient to trigger the current differential protection even during internal faults. This paper analyzes the issues with applying traditional current differential protection to photovoltaic power sources connected lines and deduces the threshold for the ratio restraint coefficient. An adaptive protection strategy is proposed, where the restraint coefficient is adjusted based on the amplitude ratios and phase angle differences of the fault currents. This ensures correct operation, particularly in cases of high photovoltaic power sources penetration. The strategy is tested through simulations conducted in Power Systems Computer Aided Design (PSCAD), showing improved sensitivity compared to traditional methods.

With the large-scale integration of renewable energy, the accuracy and dependability of the dynamic state estimation for modern distribution networks might be compromised by the uncertainty and fluctuation of renewable sources. To address these challenges, the paper proposed a new dynamic state estimation method based on Long Short-Term Memory instead of traditional Kalman Filter method. The proposed method exhibits promising accuracy with less time-cost by mitigating the negative influences of uncertainty and fluctuation brought by PV, all the while requiring limited measurements. In the paper, an improved photovoltaic power forecasting method was firstly introduced. The distribution network model considering PV forecasting effect was established by through the application of LSTM. Then, a dynamic state estimation method was developed based on established distribution network model. To prove the effectiveness of the method, the real time simulations based on RTDS platform and comparisons with traditional method were conducted.

With the increasing penetration of distributed generators (DGs), the fault current of the connected distribution network (DN) becomes complex and variable. The overcurrent signals at the same location may be decided by the connected grid or solely by the DGs. As a result, the fault location methods based on intelligent optimization algorithms have low accuracy and poor fault tolerance, especially when the overcurrent signals are determined only by the DGs under simultaneous multi-area faults. Aimed at the aforementioned problems, a novel fault location method based on an improved seagull optimization algorithm is proposed for the distribution grid integrated with the DGs. The expression of the switch status function for DNs is firstly improved considering the impact of DGs on the overcurrent signals. An elite reverse learning strategy is introduced for the seagull optimization algorithm to the diversity of the initial seagull population. Both the Levy flight control and random walk strategies are used to increase the randomness of the optimization algorithm. It is good for avoiding the emergence of locally optimal results due to the variable overcurrent status of the feeder terminal units (FTUs). Finally, the proposed fault location method was validated using a simulation model of an active DN with photovoltaic DGs based on the IEEE 33 nodes. Based on the simulation results, it is verified that the proposed fault location method can identify single-point or multi-point faults in the case of distorted overcurrent signals. The proposed method is superior to the existing one in both high accuracy and high fault tolerance.

In DC transmission systems, the performance of circuit breakers is crucial for the reliability and safety of the system. Among the available technologies, resonant DC circuit breaker (RDCCB) has become a research hotspot with advantages of low-cost and compact-design. However, traditional reclosing strategies expose it to severe secondary-current surges and result in the excessive capacity configuration of surge arresters. This paper proposes a graded reclosing strategy for RDCCB based on fault type identification. By combines the internal current oscillation characteristics and the modular series structure of RDCCB, the proposed strategy dynamically adjusts reclosing commands based on fault identification results, thereby effectively mitigating transient impacts. First, the structure and working principles are introduced. Second, the system characteristics of graded reclosing under different fault conditions are analyzed. Finally, simulation validation is conducted. The results indicate that the proposed strategy significantly reduces current surges during the reclosing process, leading to a 38% reduction in the capacity configuration requirements for surge arresters.

Control and protection cooperation represents a significant solution to the challenges of fault current breaking and the harsh requirements of protection rapidity faced by the flexible DC grid. Fault current-limiting control utilizing Modular Multi-level Converter (MMC) and DC circuit breaker (DCCB) has become a research hotspot, but most of the existing current-limiting strategies are relatively isolated and only applicable to two-terminal DC systems. This paper integrates the MMC with the DCCB to propose a source-network cooperative current limiting control (SNCLC) that enhances the current-limiting capability and extends the action time of protection in the multi-terminal flexible DC (MTDC) grid. The selectivity and adaptability of the SNCLC are improved through timing and parameter coordination. Then this paper utilizes the refraction and reflection coefficients to analyze the effect of SNCLC on the propagation of fault traveling waves and proposes a cooperation of control and protection based on the integration of line-mode current magnitude. The proposed cooperation is adapted to various application scenarios and is not affected by the line parameters and fault locations. Finally, PSCAD-/ EMTDC-based simulations are employed to verify that the proposed scheme can identify the fault before blocking the MMC, and can withstand 300 Omega transition resistance and 30 dB noise simultaneously.

In this paper, the calculation method and transient characteristics of asymmetric faults in the DC side of a true bipolar system are studied. First, two typical MMC fault equivalent methods are analyzed, and comparison shows that active RLC equivalent branches are more suitable for fault analyses of a true bipolar system. Second, considering the influence of mutual impedance between the poles in DC side, a DC fault current calculation method for a true bipolar systems is proposed. Finally, the characteristics of transient electrical quantities including fault current and DC voltage in the process of DC faults in true bipolar systems are analyzed and summarized to provide references for the design of DC line insulation and relay protection schemes.