Search Results (50)

The project of the flexible direct transmission of renewable energy has become an inevitable development trend for the large-scale grid connection of renewable energy. Its two-terminal weakly fed AC system is often composed of 100% power electronic equipment, which leads to an essential transformation in fault characteristics and protection requirements. At present, in research, the traditional directional elements are limited by the negative-sequence control strategy, resulting in the decline of their sensitivity and reliability. Therefore, this paper proposes a model for identifying directional elements using composite electrical quantities that is not affected by the control strategy of the two-terminal weakly fed AC system and can reliably identify the fault direction. Firstly, the adaptability of traditional directional elements under the negative-sequence current suppression strategy on both sides of the system when faults occur in the AC line was analyzed. Secondly, based on the idea of model recognition, the model relationship of fault voltage and current in the case of ground faults and non-ground faults occurring at different locations was analyzed. Finally, a fitted voltage was constructed and the Kendall correlation coefficient was introduced to achieve fault direction discrimination. Simulation results demonstrate that the proposed pilot protection scheme can operate reliably under conditions of 300 Ω transition resistance and 25 dB noise interference. Full article

This paper presents a comprehensive review of High-Voltage Direct-Current (HVDC) systems, focusing on their technological evolution, fault characteristics, and advanced signal processing techniques for fault detection. The paper traces the development of HVDC links globally, highlighting the transition from mercury-arc valves to Insulated Gate Bipolar Transistor (IGBT)-based converters and showcasing operational projects in technologically advanced countries. A detailed comparison of converter technologies including line-commutated converters (LCCs), Voltage-Source Converters (VSCs), and Modular Multilevel Converters (MMCs) and pole configurations (monopolar, bipolar, homopolar, and MMC) is provided. The paper categorizes HVDC faults into AC, converter, and DC types, focusing on their primary locations and fault characteristics. Signal processing methods, including time-domain, frequency-domain, and time–frequency-domain approaches, are systematically compared, supported by relevant case studies. The review identifies critical research gaps in enhancing the reliability of fault detection, classification, and protection under diverse fault conditions, offering insights into future advancements in HVDC system resilience. Full article

This paper explores how different control strategies—grid-forming and grid-following—impact the transient stability of modular multilevel converters (MMCs) interfacing with AC power grids. By employing electromagnetic transient simulation tools (PSCAD/EMTDC) on an adapted IEEE three-machine, nine-bus system, various scenarios are analyzed, including faults of differing types and locations. In the simulation, traditional synchronous generators (SGs) are replaced by MMCs configured under distinct control modes. Results indicate that grid-forming (GFM) control enhances the receiving-end grid’s transient stability by providing superior phase support and extended fault-clearing times compared to grid-following (GFL) control, with hybrid approaches yielding intermediate performance. These findings underline the importance of converter control selection in achieving robust dynamic operation in modern power systems with a high penetration of renewable energy. Full article

There is a paradigm shift to hybrid (AC/DC) networks that integrate both AC and DC to meet growing energy demands, mitigate global warming, and interconnect distributed energy sources (DERs). However, the unique characteristics of AC/DC faults, the mutual interaction of hybrid lines, the harmonic components of converters/inverters, multiple directions of energy flow, and varying current levels have challenged the existing protection algorithms. Therefore, this paper presents a data-driven coordination AC/DC fault protection algorithm. The algorithm utilizes faulty voltage and current signals to retrieve the precise time-domain characteristics of AC, DC, and intersystem (IS) faults to develop the algorithm. The proposed algorithm consists of four stages: stage 1 includes the detection of faults, stage 2 identifies the fault as either AC or DC, stage 3 classifies the respective AC and DC faults, and stage 4 locates the AC/DC fault precisely. The hybrid test system is developed in a MATLAB/Simulink environment, and the data-driven algorithm is trained and tested in Python. The extensive simulation results for multiple fault cases, either AC or DC, and the comparisons of various performance indicators confirm the effectiveness of the developed algorithm, which performs efficiently under a noisy and extended hybrid AC/DC network. Compared to other schemes, the proposed coordination protection approach can enhance the speed and accuracy of hybrid AC/DC networks. Full article

The timely detection and accurate location of capacitor element breakdown faults (CEBFs) are crucial in optimizing the performance of alternating current (AC) filters and ensuring the safety and stable operation of high-voltage direct current transmission systems. In this paper, by analyzing the physical process of CEBFs and the transient fault characteristics, a mapping relationship is established between the initial phase angle of the fault, the direction of sudden changes in unbalanced current, and the current difference on the low-voltage side for CEBFs occurring in different bridge arms. A fault arm localization method is developed for CEBFs in H-type AC filters based on the direction of sudden current changes. This technique is shown to enhance both the location accuracy and reliability compared with previous methods. The feasibility and accuracy of the proposed method are validated through simulations and experimental data. Full article

The AC/DC transmission system is an important component of the power system, and the cross-circuitry Fault diagnosis of the AC/DC transmission system plays an important role in ensuring the normal operation of power equipment and personal safety. The traditional AC/DC transmission detection methods have the characteristics of complex detection processes and low fault line identification rates. Aiming at such problems, this paper proposes a new method of cross-circuitry Fault diagnosis based on the AC/DC transmission system based on a blind signal separation algorithm. Firstly, the method takes the typical cross-circuitry Fault scenario as an example to construct the topology diagram of the AC/DC power transmission system. Then, the electrical signals of the AC system and the DC system of the AC/DC power transmission system are collected, and the collected signals are extracted by the blind signal separation algorithm. Then, aiming at the cross-circuitry Fault problem of the DC system, the electrical quantities of the positive and negative poles on the rectifier side and the inverter side are collected, and the characteristics of the electrical quantities are analyzed by wavelet to determine the fault. At the same time, aiming at the problem of the cross-circuitry Fault of the AC system, three fault types of cross-circuitry Fault, ground fault, and intact fault are set up, and the electrical quantities of A, B, and C are collected on the same side, and the characteristics of three-phase electrical quantities are analyzed by wavelet. Finally, the cross-circuitry Fault judgment interval of the AC/DC system is set as the basis of fault judgment. After experimental verification, the relative error of the model is 1.4683%. The crossline fault identification method of the AC/DC transmission system based on the blind source separation algorithm proposed in this paper can accurately identify the crossline fault location and identify the fault type. It also provides theoretical and experimental support for power system maintenance personnel to maintain equipment. Full article

The growing demand for electricity, integration of renewable energy sources, and recent advances in power electronics have driven the development of HVDC systems. Multi-terminal HVDC (MTDC) grids, enabled by Voltage Source Converters (VSCs), provide increased operational flexibility, including the ability to reverse power flow and independently control both active and reactive power. However, fault propagation in DC grids occurs more rapidly, potentially leading to significant damage within milliseconds. Unlike AC systems, HVDC systems lack natural zero-crossing points, making fault isolation more complex. This paper presents the implementation of a wavelet-based protection algorithm to detect faults in a four-terminal VSC-HVDC grid, modelled in MATLAB and SIMULINK. The study considers several fault scenarios, including two internal DC pole-to-ground faults, an external DC fault in the load branch, and an external AC fault outside the protected area. The discrete wavelet transform, using Symlet decomposition, is applied to classify faults based on the wavelet entropy and sharp voltage and current signal variations. The algorithm processes the decomposition coefficients to differentiate between internal and external faults, triggering appropriate relay actions. Key factors influencing the algorithm’s performance include system complexity, fault location, and threshold settings. The suggested algorithm’s reliability and suitability are demonstrated by the real-time implementation. The results confirmed the precise fault detection, with fault currents aligning with the values in offline models. The internal faults exhibit more entropy than external faults. Results demonstrate the algorithm’s effectiveness in detecting faults rapidly and accurately. These outcomes confirm the algorithm’s suitability for a real-time environment. Full article

Fast open-circuit (OC) fault diagnosis is essential to ensure that a multilevel inverter operates under stable conditions. Conventional diagnosis methods either require additional hardware sensors or complex calculations. However, these conditions are difficult to realize in some low-cost application scenarios. For this reason, a two-step process-based OC fault diagnosis method is proposed according to available data that can be acquired using the existing sensors in the application. At the same time, the proposed method does not involve complex and precise calculation. By analyzing the effects of an OC fault on the AC-side three-phase current, the faulty bridge arm can be quickly located via the average current. Furthermore, through establishing the calculation model of the neutral point potential, an accurate diagnosis of faulty switching devices can be achieved quickly and easily based on the residuals. The proposed OC fault diagnosis method is also proved to be correct and effective based on simulation and experience. Full article

With the load center’s continuous expansion and development of the AC power grid’s scale and construction, the recipient grid under the multi-feed DC environment is facing severe challenges of DC commutation failure and bipolar blocking due to the high strength of AC-DC coupling and the low level of system inertia, which brings many complexities and uncertainties to economic scheduling. In addition, the large-scale grid integration of wind power, photovoltaic, and other intermittent energy sources makes the ultra-high-voltage (UHV) DC channel operation state randomized. The deterministic scenario-based timing power simulation is no longer suitable for the current complex and changeable grid operation state. In this paper, we first start with the description and analysis of the uncertainty in renewable energy (RE) sources, such as wind and solar, and reconstruct the time-sequence power model by using the stochastic differential equation model. Then, a carbon emission trading cost (CET) model is constructed based on the CET mechanism, and the two-stage locating and capacity optimization model for the UHV DC receiving end is proposed under the constraint of dispatch safety and stability. Among them, the first stage starts with the objective of maximizing the carrying capacity of the UHV DC receiving end grid; the second stage checks its dynamic safety under the basic and fault modes according to the results of the first stage and corrects the drop point and capacity of the UHV DC line with the objective of achieving safe and stable UHV DC operation at the lowest economic investment. In addition, the two-stage model innovatively proposes UHV DC relative inertia constraints, peak adjustment margin constraints, transient voltage support constraints under commutation failure conditions, and frequency support constraints under a DC blocking state. In addition, to address the problem that the probabilistic constraints of the scheduling model are difficult to solve, the discrete step-size transformation and convolution sequence operation methods are proposed to transform the chance-constrained planning into mixed-integer linear planning for solving. Finally, the proposed model is validated with a UHV DC channel in 2023, and the results confirm the feasibility and effectiveness of the model. Full article

Over the past few decades, wind energy has expanded to become a widespread, clean, and sustainable energy source. However, integrating offshore wind energy with the onshore AC grids presents many stability and control challenges that hinder the reliability and resilience of AC grids, particularly during faults. To address this issue, current grid codes require offshore wind farms (OWFs) to remain connected during and after faults. This requirement is challenging because, depending on the fault location and power flow direction, DC link over- or under-voltage can occur, potentially leading to the shutdown of converter stations. Therefore, this necessitates the proper understanding of key technical concepts associated with the integration of OWFs. To help fill the gap, this article performs an in-depth investigation of existing alternating current fault ride through (ACFRT) techniques of modular multilevel converter-based high-voltage direct current (MMC-HVDC) for OWFs. These techniques include the use of AC/DC choppers, flywheel energy storage devices (FESDs), power reduction strategies for OWFs, and energy optimization of the MMC. This article covers both scenarios of onshore and offshore AC faults. Given the importance of wind turbines (WTs) in transforming wind energy into mechanical energy, this article also presents an overview of four WT topologies. In addition, this article explores the advanced converter topologies employed in HVDC systems to transform three-phase AC voltages to DC voltages and vice versa at each terminal of the DC link. Finally, this article explores the key stability and control concepts, such as small signal stability and large disturbance stability, followed by future research trends in the development of converter topologies for HVDC transmission such as hybrid HVDC systems, which combine current source converters (CSCs) and voltage source converters (VSCs) and diode rectifier-based HVDC (DR-HVDC) systems. Full article

Diagnosing faults is crucial for ensuring the safety and reliability of medium-voltage direct current (MVDC) systems. In this study, we propose a bidirectional long short-term memory (Bi-LSTM)-based fault diagnosis scheme for the accurate classification of faults occurring in MVDC systems. First, to ensure stability in case a fault occurs, we modeled an MVDC system that included a resistor-based fault current limiter (R-FCL) and a direct current circuit breaker (DCCB). A discrete wavelet transform (DWT) extracted the transient voltages and currents measured using DC lines and AC grids in the frequency–time domain. Based on the digital signal normalized by the DWT, using the measurement data, the Bi-LSTM algorithm was used to classify and learn the types and locations of faults, such as DC line (PTP, P-PTG, and N-PTG) and internal inverter faults. The effectiveness of the proposed fault diagnosis scheme was validated through comparative analysis within the four-terminal MVDC system, demonstrating superior accuracy and a faster diagnosis time compared to those of the existing schemes that utilize other AI algorithms, such as the CNN and LSTM. According to the test results, the proposed fault diagnosis scheme detects MVDC faults and shows a high recognition accuracy of 97.7%. Additionally, when applying the Bi-LSTM-based fault diagnosis scheme, it was confirmed that not only the training diagnosis time (TraDT) but also the average diagnosis time (AvgDT) were 0.03 ms and 0.05 ms faster than LSTM and CNN, respectively. The results validate the superior fault clarification and fast diagnosis performance of the proposed scheme over those of the other methods. Full article

Flexible DC power grids are widely recognized as an important component of building smart grids. Compared with traditional AC power grids, flexible DC power grids have strong technical advantages in islanding power supplies, distributed power supplies, regional power supplies, and AC system interconnection. In multi-terminal flexible DC power grids containing renewable energy sources such as solar and wind power, due to the instability and intermittency of renewable energy, it is usually necessary to add energy storage units to pre-regulate the power of the multi-terminal flexible DC power grid in islanded operation. Aiming at the important problem of large current impact and serious consequences when the flexible DC distribution network fails, a combined location method combining an improved impedance method (series current-limiting reactors at both ends of the line to obtain a more accurate current differential value) and a particle swarm optimization algorithm is proposed. Initially, by establishing the enhanced impedance model, the differential variables under the conditions of inter-electrode short-circuit and single-pole grounding fault can be obtained. Then tailor-made fitness functions are designed for these two models to optimize parameter identification. Subsequently, the iterative parameters of the particle swarm optimization algorithm are fine-tuned, giving it dynamic sociality and self-learning ability in the iterative process, which significantly improves the convergence speed and successfully avoids local optimization. Finally, various fault types in a six-terminal DC distribution network are simulated and analyzed by MATLAB, and the results show that this method has good accuracy and robustness. This research provides strong theoretical and methodological support for improving the safety and reliability of DC distribution systems. Full article

When using transformer insulation oil as a liquid dielectric, the oil is easily polluted by the solid particles generated in the operation of the transformer, and these metallic impurity particles have a significant impact on the insulation performance inside the power transformer. The force of the metal particles suspended in the flow insulation oil is multidimensional, which will lead to a change in the movement characteristics of the metal particles. Based on this, this study explored the motion rules of suspended metallic impurity particles in mobile insulating oil in different electric field environments and the influencing factors. A multiphysical field model of the solid–liquid two-phase flow of single-particle metallic impurity particles in mobile insulating oil was constructed using the dynamic analysis method, and the particles’ motion characteristics in the oil in different electric field environments were simulated. The motion characteristics of metallic impurity particles under conditions of different particle sizes, oil flow velocities, and insulation oil qualities and influencing factors were analyzed to provide theoretical support for the detection of impurity particles in transformer insulation oil and enable accurate estimations of the location of equipment faults. Our results show that there are obvious differences in the trajectory of metallic impurity particles under different electric field distributions. The particles will move towards the region of high field intensity under an electric field, and the metallic impurity particles will not collide with the electrode under an AC field. When the electric field intensity and particle size increase, the trajectory of the metallic impurity particles between electrodes becomes denser, and the number of collisions between particles and electrodes and the motion speed both increase. Under the condition of a higher oil flow velocity, the number of collisions between metal particles and electrodes is reduced, which reduces the possibility of particle agglomeration. When the temperature of the insulation oil changes and the quality deteriorates, its dynamic viscosity changes. With a decrease in the dynamic viscosity of the insulation oil, the movement of the metallic impurity particles between the electrodes becomes denser, the collision times between the particles and electrodes increase, and the maximum motion speed of the particles increases. Full article

In recent years, with the continuous growth in China’s economy, the continuous advancement of urbanization and industrialization, the contradiction between rapid economic development and the continuous reduction in traditional fossil energy reserves such as coal, oil, and natural gas, the continuous aggravation of environmental pollution has become increasingly prominent. In this era, clean energy power generation technologies such as hydropower, wind power, and solar power generation, which have the advantages of renewability, environmental protection, and economy, have developed rapidly. However, wind and photovoltaic power plants are often located in remote areas, which means significant losses in the transmission process. High-voltage direct current (HVDC) transmission technology becomes the best choice to solve this problem. The HVDC transmission system based on a grid commutator is widely used in China’s AC-DC hybrid power grid. When an AC fault occurs on the inverter side, the line-commutated converter high-voltage direct current (LCC-HVDC) system is more prone to continuous commutation failure, which brings serious harm to system operation. To better suppress the problem of continuous commutation failure on the contravariant side, this paper analyzes the mechanism of continuous commutation failure from multiple angles. The DC current command sensitivity of a voltage-dependent current order limiter (VDCOL) in the LCC-HVDC system is low, which will lead to different degrees of continuous commutation failure. In addition, the rapid rise in DC current and the drop in commutation voltage during the fault will cause the turn-off angle to drop, and the probability of continuous commutation failure of the system will increase significantly. Based on the above theoretical analysis, a new control strategy combining the dynamic compensation of the turn-off angle of a virtual inductor and the suppression of continuous commutation failure by dynamic nonlinear VDCOL is proposed. A dynamic nonlinear VDCOL control strategy is proposed for the low sensitivity of current command adjustment under conventional VDCOL control. Secondly, two concepts of virtual inductance and DC current change rate are introduced, and a control strategy based on virtual inductance is proposed to comprehensively ensure that the switching angle has sufficient commutation margin during fault recovery. Finally, based on the CIGRE standard test model in PSCAD/EMTDC, the accuracy of the correlation mechanism analysis and the effectiveness of the suppression method are verified. Full article

The coupling of AC and DC power will impact the protective actions on the AC side and pose a threat to the stable operation of the interconnection system. Therefore, a new longitudinal protection method is proposed based on the comprehensive distance similarity of voltage waveforms. Initially, the measured voltage and current data are extracted to calculate the reference voltage, and the voltage waveform fitting is optimized. Subsequently, the Euclidean dynamic time warp (DTW) distance and entropy weight method are utilized to process the voltage waveform, enabling the calculation of its comprehensive distance similarity. This similarity is adopted to determine fault location. A hybrid DC multi-feed AC/DC interconnection system, incorporating a line commutated converter-voltage source converter (LCC-VSC) and a line commutated converter-modular multilevel converter (LCC-MMC), was established in PSCAD, and fault data were simulated and output. The effectiveness of the protection scheme was validated using MATLAB. Simulation results demonstrate that the proposed method can accurately distinguish between faults inside and outside a region. When compared to existing protection methods, it demonstrates superior performance in resisting transition resistance and noise interference, while also mitigating the impact of data asynchronicity. The speed and reliability of the method are further enhanced. Full article