Search Results (106)

The growing deployment of photovoltaic (PV) power plants has made reliable fault detection and classification a critical challenge for ensuring operational efficiency, safety, and economic viability. Faults on the direct current (DC) side, especially during the commissioning phase, can significantly affect power output and maintenance costs. This paper proposes a fault classification methodology for the direct current (DC) side of PV power plants, using the MATLAB/Simulink 2023b simulation environment for system modeling and dataset generation. The method accounts for different environmental and operational conditions—including irradiance and temperature variations—to enhance fault identification robustness. The main electrical faults—such as open circuit (OC), short circuit (SC), connector faults, and partial shading—are analyzed based on features extracted from current–voltage (I–V) and power–voltage (P–V) curves. The proposed classification system achieved 100% accuracy by applying the One-Versus-One (OVO) and One-Versus-Rest (OVR) techniques, using a dataset with 704 samples for one string and 2480 samples for three strings. The lowest accuracies were observed with the OVO technique: 99.03% for 1024 samples with one string, and 97.35% for 880 samples with three strings. The study also highlights the performance of multiclass machine learning techniques across different dataset sizes. The results reinforce the relevance of using machine learning integrated into the commissioning phase of PV systems, with the potential to improve reliability, reduce losses, and optimize the operational costs of solar plants. Future work should explore the application of this method to real-world data, as well as its deployment in the field to support companies and professionals in the sector. Full article

In order to meet the needs of grid integration of various renewable energy sources and promote long-distance power transmission, a hybrid multi-infeed DC system architecture consisting of a line-commutated converter (LCC) and a modular multilevel converter (MMC) is constructed. Focusing on the issue of traditional differential protection refusing to operate under high-resistance grounding faults and failing under symmetrical faults, a dual-criteria protection mechanism is proposed in this paper. By integrating current differential and voltage criterion, the accurate identification of various types of AC line faults can be realized. A hybrid DC system simulation model was built on MATLAB, the sampled data was decoupled, and the differential quantity was calculated to test the dual-criteria protection mechanism. The simulation results show that the proposed protection mechanism can effectively identify various faults within the hybrid DC multi-feed system area and faults outside the area and has robustness to complex working conditions such as high-resistance grounding and three-phase short circuits, which improves the sensitivity, selectivity, and adaptability of the protection. This method is designed for AC line protection under the disturbance of multi-infeed DC systems. It is not directly applicable to pure DC microgrids. The concept can be extended to AC/DC hybrid microgrids by adding DC-side protection criteria and re-calibrating thresholds. Full article

To meet the demands of deep grid integration of renewable energy and long-distance power transmission, this paper presents a hybrid multi-infeed DC system architecture that includes an AC power source (AC), a voltage source converter (VSC), and a modular multilevel converter (MMC). Addressing the limitations of traditional differential protection—such as insufficient sensitivity under high-resistance grounding and susceptibility to false operations under out-of-zone disturbances—this paper introduces an enhanced current differential criterion based on dynamic phasor analysis. By effectively decoupling DC bias and load current components and optimizing the calculation of action and braking quantities, the proposed method enables the rapid and accurate identification of typical faults, including high-resistance grounding, three-phase short circuits, and out-of-zone faults. A multi-scenario simulation platform is built using MATLAB to thoroughly validate the improved criterion. Simulation results demonstrate that the proposed method offers excellent sensitivity, selectivity, and resistance to false operations in multi-infeed complex systems. It achieves fast fault detection (~2.0 ms), strong sensitivity to high-resistance internal faults, and low false tripping under a variety of test scenarios, providing robust support for next-generation DC protection systems. Full article

The large-scale integration of renewable energy and the high penetration of power electronic devices have led to a significant reduction in system inertia and short-circuit capacity. This is particularly manifested in the form of insufficient multiple renewable energy stations short-circuit ratio (MRSCR) and transient overvoltage issues following severe disturbances such as AC and DC faults, which greatly limit the power transfer capability of large renewable energy bases. To effectively mitigate these challenges, this paper proposes an optimal synchronous condenser deployment method tailored for large-scale renewable energy bases. The proposed mathematical model supports a hybrid centralized and distributed configuration of synchronous condensers with various capacities and manufacturers while considering practical engineering constraints such as short-circuit ratio, transient overvoltage, and available bays in renewable energy stations. A practical decomposition and iterative computation strategy is introduced to reduce the computational burden of transient stability simulations. Case studies based on a real-world system verify the effectiveness of the proposed method in determining the optimal configuration of synchronous condensers. The results demonstrate significant improvements in grid strength (MRSCR) and suppression of transient overvoltages, thereby enhancing the stability and transfer capability of renewable energy bases in weak-grid environments. Full article

Enhancing the resilience of renewable energy systems in ultra-weak grids is crucial for promoting sustainable energy adoption and ensuring a reliable power supply during disturbances. Ultra-weak grids characterized by a very low Short-Circuit Ratio, less than 2, and high grid impedance significantly impair voltage and frequency stability, imposing challenging conditions for Inverter-Based Resources. To address these challenges, this paper considers a 110 KVA, three-phase, two-level Voltage Source Converter, interfacing a 700 V DC link to a 415 V AC ultra-weak grid. X/R = 1 is controlled using Sinusoidal Pulse Width Modulation, where the Grid-Connected Converter operates in Grid-Forming Mode to maintain voltage and frequency stability under a steady state. During symmetrical and asymmetrical faults, the converter transitions to Grid-Following mode with current control to safely limit fault currents and protect the system integrity. After fault clearance, the system seamlessly reverts to Grid-Forming Mode to resume voltage regulation. This paper proposes an improved control strategy that integrates voltage feedforward reactive power support and virtual capacitor-based virtual inertia using Active Disturbance Rejection Control, a robust, model-independent controller, which rapidly rejects disturbances by regulating d and q-axes currents. To test the practicality of the proposed system, real-time implementation is carried out using the OPAL-RT OP4610 platform, and the results are experimentally validated. The results demonstrate improved fault current limitation and enhanced DC link voltage stability compared to a conventional PI controller, validating the system’s robust Fault Ride-Through performance under ultra-weak grid conditions. Full article

Current–voltage (I–V) characteristics are an important measure of photovoltaic (PV) generators, corresponding to environmental conditions regarding solar irradiance and temperature. The I–V curve tracer is a widely used instrument in power engineering to evaluate system performance and detect fault conditions in PV power systems. Several technologies have been applied to develop the device and trace I–V characteristics, improving accuracy, speed, and portability. Focusing on the outdoor environment, this paper presents an in-depth analysis and comparison of the system design and dynamics to identify the I–V tracing performance based on different power conversion topologies and data acquisition methods. This is a valuable reference for industry and academia to further the technology and promote sustainable power generation. Full article

This article presents a hybrid fault diagnosis framework for DC–DC converters in photovoltaic (PV) systems, combining digital twin (DT) modelling and detection with machine learning anomaly classification. The proposed method addresses both hardware faults such as open and short circuits in insulated-gate bipolar transistors (IGBTs) and diodes and sensor-level false data injection attacks (FDIAs). A five-dimensional DT architecture is employed, where a virtual entity implemented using FMI-compliant FMUs interacts with a real-time emulated physical plant. Fault detection is performed by comparing the real-time system behaviour with DT predictions, using dynamic thresholds based on power, voltage, and current sensors errors. Once a discrepancy is flagged, a second step classifier processes normalized time-series windows to identify the specific fault type. Synthetic training data are generated using emulation models under normal and faulty conditions, and feature vectors are constructed using a compact, interpretable set of statistical and spectral descriptors. The model was validated using OPAL-RT Hardware in the Loop emulations. The results show high classification accuracy, robustness to environmental fluctuations, and transferability across system configurations. The framework also demonstrates compatibility with low-cost deployment hardware, confirming its practical applicability for fault diagnosis in real-world PV systems. Full article

To address the challenges of prolonged current isolation times and high dependency on varistors in traditional flexible short-circuit fault isolation schemes for DC systems, this paper proposes a rapid fault isolation circuit design based on an adaptive solid-state circuit breaker (SSCB). By introducing an adaptive current-limiting branch topology, the proposed solution reduces the risk of system oscillations induced by current-limiting inductors during normal operation and minimizes steady-state losses in the breaker. Upon fault occurrence, the current-limiting inductor is automatically activated to effectively suppress the transient current rise rate. An energy dissipation circuit (EDC) featuring a resistor as the primary energy absorber and an auxiliary varistor (MOV) for voltage clamping, alongside a snubber circuit, provides an independent path for inductor energy release after faults. This design significantly alleviates the impact of MOV capacity constraints on the fault isolation process compared to traditional schemes where the MOV is the primary energy sink. The proposed topology employs a symmetrical bridge structure compatible with both pole-to-pole and pole-to-ground fault scenarios. Parameter optimization ensures the IGBT voltage withstand capability and energy dissipation efficiency. Simulation and experimental results demonstrate that this scheme achieves fault isolation within 0.1 ms, reduces the maximum fault current-to-rated current ratio to 5.8, and exhibits significantly shorter isolation times compared to conventional approaches. This provides an effective solution for segment switches and tie switches in millisecond-level self-healing systems for both low-voltage (LVDC, e.g., 750 V/1500 V DC) and medium-voltage (MVDC, e.g., 10–35 kV DC) smart DC distribution grids, particularly in applications demanding ultra-fast fault isolation such as data centers, electric vehicle (EV) fast-charging parks, and shipboard power systems. Full article

Recurrent catastrophic inverter failures significantly undermine the reliability and economic viability of utility-scale photovoltaic (PV) power plants. This paper presents a comprehensive investigation of severe inverter destruction incidents at the Kopli Solar Power Plant, Estonia, by integrating controlled laboratory simulations with extensive field monitoring. Initially, detailed laboratory experiments were conducted to replicate critical DC-side short-circuit scenarios, particularly focusing on negative DC input terminal faults. The results consistently showed these faults rapidly escalating into multi-phase short-circuits and sustained ground-fault arcs due to inadequate internal protection mechanisms, semiconductor breakdown, and delayed relay response. Subsequently, extensive field-based waveform analyses of multiple inverter failure events captured identical fault signatures, thereby conclusively validating laboratory-identified failure mechanisms. Critical vulnerabilities were explicitly identified, including insufficient isolation relay responsiveness, inadequate semiconductor transient ratings, and ineffective internal insulation leading to prolonged arc conditions. Based on the validated findings, the paper proposes targeted inverter design enhancements—particularly advanced DC-side protective schemes, rapid fault-isolation mechanisms, and improved internal insulation practices. Additionally, robust operational and monitoring guidelines are recommended for industry-wide adoption to proactively mitigate future inverter failures. The presented integrated methodological framework and actionable recommendations significantly contribute toward enhancing inverter reliability standards and operational stability within grid-connected photovoltaic installations. Full article

The rise of direct current (DC) distribution networks, driven by distributed energy storage and large-scale photovoltaic integration, has significantly altered distribution network configurations. In DC networks, short-circuit faults cause a sharp drop in voltage and a rapid increase in current, negatively impacting system stability. To solve this problem, we used an improved red fox optimization (IRFO) algorithm to calculate the distance to failure of the protection device. The algorithm shows higher convergence and accuracy compared to conventional methods. The isolated forest algorithm rejects anomalous data, while an adjustable feedback factor and genetic crossover operator further improve performance. Adaptive interpolation is employed to address low sampling frequency issues, enhancing fault localization precision. Simulations performed in Simulink show that the method is highly resistant to interference with minimal localization error. It is also resistant to changes in system parameters, highlighting its robustness and usefulness in fault localization. Full article

This paper proposes a dynamic current limit for modular multilevel converters (MMCs) that maximizes the injection of current during grid faults in order to mitigate the voltage dip, reduce voltage imbalances in case of an asymmetrical fault, and ensure the proper operation of protective relays. The reduced short-circuit capacity of MMCs, and power converters in general, is one of their main limitations. In the event of a fault, the converter’s current is significantly lower than that of the synchronous generators, which may impact both the performance of power system protective relays and the mitigation of voltage drops during faults. Usually, to protect the MMCs themselves, their output current is limited by their control. However, the current flowing through the power semiconductors is the arm current, not the output current, and this consists of an AC and a DC component. A new current saturation strategy aiming at maximizing fault current injection, in compliance with the most recent grid codes, is proposed. This strategy limits the arm currents by dynamically adjusting the output current limit while injecting reactive currents (both positive- and negative-sequence) and active current according to the grid codes, the fault type, and voltage sag level. A theoretical analysis is carried out to determine the maximum current injection that will not exceed the arm limits, and this is then validated through detailed PSCAD simulations. With the proposed strategy, the supplied current can be increased by approximately 40%. Full article

Current transient stability analysis of power systems with doubly fed induction generators (DFIGs) draws upon the assumption that nodal electromagnetic power equals to zero during the fault period. The omission of electromagnetic power degrades the fidelity of transient stability analysis and renders the analytical impact of fault location on stability indiscernible. To address this limitation, a DFIG-integrated power system-oriented transient stability mechanism analysis method is proposed involving fault location factors. Firstly, a foundational analysis model is established by integrating a simplified DFIG representation with the improved DC power flow corrected by the fault’s instantaneous short-circuit voltage. Secondly, the non-metallic symmetrical short-circuit fault is equivalently treated as a power injection source, and the faulted electromagnetic power of generators is derived. The proposed equivalence is roughly correct, as its faulted energy integral is validated to approximate ground-truth. Lastly, combining the above analytical formulas and extended equal area criterion (EEAC), a time-domain simulation-free explicit transient stability criterion incorporating fault location factor is settled. Simulation results in a double-generator system with DFIG integration confirm that, compared to existing transient stability criterion, the proposed criterion can expand the stability assessable area by approximately 10% while maintaining accuracy. Full article

In this paper, the concept of a fault-tolerant multiport converter is proposed for a shipboard zonal DC system. The traditional zonal shipboard system offers a resilient power supply capability at the expense of increased cost and size. To solve this problem, the fault-tolerant multiport active bridge converter is proposed for shared energy storage between DC buses. When a short-circuit fault occurs on one bus, the energy storage can maintain uninterrupted power supply to the remaining healthy bus. With consideration of both normal operation and a fault-tolerant mode, the power transfer capability and ZVS region are analyzed. The proposed converter is compared with a traditional two-converter zonal system and multiport converter in terms of cost, volume, and efficiency. The performance of the proposed FT-MAB converter is tested through experimental verifications with the aim of validating the resilience of the power supply. The proposed FT-MAB converter achieves fault tolerance through topological reconfiguration, isolating the faulty port after the occurrence of a short-circuit fault and providing uninterrupted power supply to the healthy bus. Full article

To diagnose open-circuit faults (OCFs) in sub-module switching devices within input-independent output-series (IIOS) photovoltaic DC collection systems, this paper presents a hybrid diagnostic method combining convolutional neural networks (CNNs) and long short-term memory networks (LSTMs). The method utilizes a sliding window technique to segment sub-module capacitor voltage signals into time-series samples. Initially, CNN automatically extracts local features from the samples, followed by LSTM for capturing temporal dependencies and extracting global time series features, enabling effective fault detection under complex conditions. This approach eliminates the need for manual feature extraction and complex system modeling. By leveraging the model’s learning capabilities, it mitigates the impact of solar irradiance fluctuations on diagnostic accuracy. After training, the model performs real-time fault diagnosis with high precision using voltage data, offering fast, efficient, and reliable performance. The effectiveness of the method was validated through both simulation and experimental results. Full article

Faults of a Modular Multilevel Converter (MMC)-type converter valve significantly impact the reliability of flexible DC transmission systems. This paper analyzed the impact of ongoing short circuit faults in submodules on the power transmission of the MMC-type converter valve of which redundant submodules had been depleted. First, MMC’s working principle and its submodules’ possible operational states were investigated. Then, fault mechanisms for intra-submodule Insulated-Gate Bipolar transistor (IGBT) short circuits and inter-submodule short circuits were modeled to infer changes in power transmission during submodule faults. To quantify the impact of submodule faults on the energy transfer efficiency of the converter valve, an energy transfer efficiency index was proposed to obtain analytical expressions for energy transfer efficiency in the case of intra-submodule and inter-submodule short-circuit faults. Finally, the effectiveness of the proposed analytical model was verified through Simulink simulations. Simulation results indicate that ongoing intra-submodule and inter-submodule short circuits increase the input power of the converter valve, reducing energy transfer efficiency. Moreover, the energy transfer efficiency continues to decline with an increase in faulty submodules. Full article