Search Results (148)

The development and utilization of large-scale offshore wind power (OWP) are critical measures for achieving global energy transition. To address the demands of future large-scale OWP centralized development and transmission, this study systematically investigates the influencing factors and construction principles for topology selection in offshore wind power high-voltage direct current (HVDC) transmission systems delivering power to load centers. First, under the context of expanding the offshore wind power transmission scale, the necessity of transmitting OWP via HVDC overhead lines directly to load centers after landing is theoretically discussed. Five key topological influencing factors are then analyzed: offshore wind power collection schemes, multi-terminal HVDC network configurations, DC fault isolation mechanisms, offshore converter station architectures, and voltage source converter HVDC (VSC-HVDC) receiving terminal landing modes. Corresponding topology construction principles for direct HVDC transmission to load centers are proposed to guide system design. Finally, the feasibility of the proposed principles is validated through a case study of a multi-terminal HVDC system integrated into an actual regional power grid, demonstrating practical applicability. Full article

High-resistance faults on the DC lines of multi-terminal VSC-HVDC grids lead to insufficient protection reliability, and the introduction of current-limiting strategies alters the system’s intrinsic fault characteristics, degrading protection performance. To address these issues, we propose a DC-line protection scheme that is immune to converter control strategies and highly tolerant to fault resistance. First, based on the grid topology, post-fault current paths are analyzed, and the fault characteristics produced solely by the fault-induced voltage source are identified. A sequential overlapping derivative transformation is then employed to magnify the discrepancy between internal and external faults, forming the core of the fault-identification criterion; the zero-mode component is used for pole selection. Finally, a four-terminal VSC-HVDC model is built in PSCAD/EMTDC version 4.6.2 for validation. Simulation results show that, after applying the current-limiting strategy, the characteristic quantity changes only marginally, and the proposed protection can reliably withstand fault resistances of up to 700 Ω. Full article

The complex topology of shipboard DC microgrids and the strong coupling between positive and negative poles during faults pose significant challenges for faulted-pole identification, especially under high-resistance conditions. To address these issues, this paper proposes a novel faulted-pole identification method based on S-Transformation and convolutional neural networks (CNNs). Single-ended voltage and current measurements from the generator side are used to generate time–frequency spectrograms via S-Transformation, which are then processed by a CNN trained to classify the faulted pole. This approach avoids reliance on complex threshold settings. Simulation results on a representative shipboard DC microgrid demonstrate that the proposed method achieves high accuracy, fast response, and strong robustness, even under high-resistance fault scenarios. The method significantly enhances the selectivity and reliability of fault protection, offering a promising solution for advanced marine DC power systems. Compared to conventional fault-diagnosis techniques, the proposed model achieves notable improvements in classification accuracy and computational efficiency for line-fault detection. Full article

Detecting power transformer winding degradations at an early stage is very important for the safe operation of nuclear power plants. Most transformer failures are caused by insulation breakdown; the winding turn-to-turn short circuit fault is frequently encountered. Experience has shown that routine testing techniques, e.g., winding resistance, leakage inductance, and sweep frequency response analysis (SFRA), are not sensitive enough to identify minor turn-to-turn short defects. The SFRA technique is effective only if the fault is in such a condition that the flux distribution in the core is prominently distorted. This paper proposes the frequency domain reflectometry (FDR) technique for detecting and locating transformer winding defects. FDR measures the wave impedance and its change along the measured windings. The wire over a plane model is selected as the transmission line model for the transformer winding. The effectiveness is verified through lab experiments on a twist pair cable simulating the transformer winding and field testing on a real transformer. The FDR technique successfully identified and located the turn-to-turn short fault that was not detected by other testing techniques. Using FDR as a complementary tool for winding condition assessment will be beneficial. Full article

There are significant emissions of greenhouse gases into the atmosphere from the transportation industry. As a result, the idea that electric vehicles (EVs) offer a revolutionary way to reduce greenhouse gas emissions and our reliance on rapidly depleting petroleum supplies has been put forward. EVs are becoming more common in many nations worldwide, and the rapid uptake of this technology is heavily reliant on the growth of charging stations. This is leading to a significant increase in their number on the road. This rise has created an opportunity for EVs to be integrated with the power system as a Demand Response (DR) resource in the form of an EV fast charging station (EVFCS). To allocate electric vehicle fast charging stations as a dynamic load for frequency control and on specific buses, this study included the optimal location for the EVFCS and the best controller selection to obtain the best outcomes as DR for various network disruptions. The optimal location for the EVFCS is determined by applying transient voltage drop and frequency nadir parameters to the Particle Swarm Optimization (PSO) location model as the first stage of this study. The second stage is to explore the optimal regulation of the dynamic EVFCS load using the PSO approach for the PID controller. PID controller settings are acquired to efficiently support power system stability in the event of disruptions. The suggested model addresses various types of system disturbances—generation reduction, load reduction, and line faults—when it comes to the Kundur Power System and the IEEE 39 bus system. The results show that Bus 1 then Bus 4 of the Kundur System and Bus 39 then Bus 1 in the IEEE 39 bus system are the best locations for dynamic EVFCS. Full article

To solve the problem of high cost and low efficiency of measuring equipment in traditional distribution network fault location, a fault section location and line selection strategy combining dynamic binary particle swarm optimization (DBPSO) configuration and fuzzy C-means (FCM) clustering is proposed in this paper. Firstly, the DBPSO algorithm is used to optimize the configuration scheme of the distributed voltage and current sensing device, which reduces the number of measuring devices and system cost on the premise of ensuring the global observability of the distribution network. When a fault occurs in the distribution network, the sensor device based on optimal configuration collects fault feature data, combines it with the FCM clustering algorithm to classify nodes according to fault feature similarity, and divides the most significant fault-affected section as the core fault area. Further, by calculating the Euclidean distance between each node in the fault section and the cluster center, the fault line is accurately identified. Finally, a fault simulation model based on an IEEE 11-node system is constructed to verify the effectiveness of the proposed method. The results show that, compared with the traditional fault section location and route selection strategy, this method can reduce the number of measurement devices optimally configured by 19–36% and significantly reduce the number of algorithm iterations. In addition, it can realize rapid fault location and precise line screening at a low equipment cost under multiple fault types and different fault locations, which significantly improves fault location accuracy while reducing economic investment. Full article

The integration of variable distributed energy sources (DERs) can reduce overall system inertia, potentially impacting the transient response of both conventional and renewable generators within electrical grids. Although transient stability indicators—for instance, the Critical Clearing Time (CCT), fault-induced short-circuit current ratios, and machine parameters, including subtransient–transient reactances and associated time constants—are influenced by total system inertia, their detailed evaluation remains insufficiently explored. These parameters provide standardized benchmarks for systematically assessing the transient stability performance of conventional and photovoltaic (PV) generators as the penetration level of distributed PV systems (PVD1) increases. This study explores the relationship between conventional stability parameters and system inertia across different levels of PV penetration. CCT, a key metric for transient stability assessment, incorporates multiple influencing factors and typically increases with higher system inertia, making it a reliable comparative indicator for evaluating the effects of PV integration on system stability. To investigate this, the IEEE New England 39-bus system is adapted by replacing selected synchronous machines with PVD1 PV units and adjusting the PV penetration levels. The resulting system behavior is then compared to that of the original configuration to evaluate changes in transient stability. The findings confirm that transient and subtransient reactances, along with their respective time constants under fault conditions, are shaped not only by the characteristics of the generator on the faulted line but also by the surrounding network structure and overall system inertia. The newly introduced sensitivity parameters offer insights by capturing trends specific to conventional versus PV-based generators under different inertia scenarios. Notably, transient parameters show similar responsiveness to inertia variations to subtransient ones. This paper demonstrates that in certain scenarios, the integration of low-inertia PV generators may generate insufficient energy, which is not above critical energy during major disturbances, resulting surviving fault and subsequently an infinite CCT. While the integration of PV generators can be beneficial for their own operational performance, it may adversely impact the dynamic behavior and fault response of conventional synchronous generators within the system. This highlights the need for effective planning and control of DER integration to ensure reliable power system operation through accurate selection and application of both conventional and proposed transient stability parameters. Full article

The main causes of damage include poor site selection, such as building on fault lines or on fill soil, as well as deficiencies in design, materials, and workmanship. Damage levels are also linked to the economic conditions of the region. In the 1939 earthquake, there were high casualties due to the magnitude of the earthquake, lack of engineering design in traditional structures and unsuitable soil conditions. Similarly, in the 1992 earthquake, unexpected damage occurred due to faulty designs created by inexperienced engineers who lacked sufficient knowledge of the seismic behavior of structures, errors in craftsmanship and workmanship, and unsuitable residential area selection for construction. These problems continue today and put most of the building stock at risk in case of a major earthquake. Seismic steel isolators are used in two new buildings in the city; if they are effective, they should be made mandatory in new construction. Otherwise, consideration should be given to relocating the city to the more stable southern rocky areas, which were unaffected in both 1939 and 1992. Full article

Challenges are brought to high impedance fault (HIF) line selection in traditional distribution networks by the fault signals with short windows and weak characteristics provided by new energy power sources. A new method driven by the symmetry of current traveling wave spectrum is proposed in this paper. Frequency-domain features are extracted by using Pisarenko spectral decomposition, and the differences in amplitude, frequency, and polarity between faulted and healthy feeders are analyzed. A similarity matrix is constructed with the help of Manhattan distance, and an improved density-based spatial clustering of application with noise (DBSCAN) clustering is adopted to achieve intelligent fault line selection. Experimental results show that compared with the steady state component method and the transient component method, the accuracy of this method is increased to 97.5%, with an improvement of more than 12.5%. Quantitative thresholds are replaced by qualitative spectrum differences, and this method is not affected by weak signals, thus solving the problem of threshold setting caused by the access of new energy. The accuracy of this method under different fault types, phases, and resistances is verified by simulation, ensuring easy engineering implementation. Full article

Fault diagnosis based on the partial discharge (PD) recognition has been widely applied on a gas-insulated line breaker (GILB) and gas-insulated switchgear (GIS) as a reliable online condition monitoring method. This paper dealt with insulation defect diagnosis based on a Random Forest (RF) algorithm with an optimized feature selection method. Four different types of insulation defect models, such as the free-moving particle (FMP) defect, the protrusion-on-conductor (POC) defect, the protrusion-on-enclosure (POE) defect, and the delamination defect, were prepared to simulate representative PD single pulses and PRPD patterns generated from the GILB. The PD signals generated from defect models were detected using the PRPD sensor which can detect phase-synchronized PD signals with the applied high-voltage (HV) signals without the need for additional equipment. Various statistical PD features were extracted from PD single pulses and PRPD patterns according to four kinds of PD defect models, and optimized features were selected with respect to variance importance analysis. Two kinds of PD datasets were established using all statistical features and top-ranked features. From the experimental results, the RF algorithm achieved accuracy rates exceeding 92%, and the PD datasets using only half of the statistical PD features could reduce the computational times while maintaining the accuracy rates. Full article

The behavior of the soils under dynamic loads is of great importance for the structures to be built in earthquake zones. As a result of the determination of the site-specific dynamic parameters of the soils and the analyzes to be made with these parameters, the ground response that will occur on the surface during the earthquake will be determined. Turkey is located in one of the important earthquake belts of Europe. Studies are carried out on the North Anatolian Fault Zone (NAFZ), which is one of the important and active fault lines here. In this study, as a result of 4 drilling studies on NAFZ, firstly, dynamic triaxial (TRX) and resonant column (RC) test systems were used to obtain site-specific shear modulus and damping curves depending on depth. 11 earthquake acceleration records reflecting the seismic characteristics of the region were selected and scaled in both time-history and frequency-time domains. Two different scaling methods were compared with the nonlinear soil amplification analysis. In addition, surface response spectra were examined according to the Turkish Building Earthquake Code (TEC 2018). Although there is not a big difference in amplification values in two different scaling methods, it has been determined that the design spectrum values are very different. Full article

Fault location technology is crucial for enhancing the efficiency of fault maintenance and ensuring the safety of the power supply in small current grounding systems. To address the challenge that traditional single-end positioning methods experience when identifying the reflected wave head and that the adaptability of wave head calibration methods is typically limited, a single-end location method of modulus wave velocity differences based on marine predator algorithm optimized multivariate variational mode decomposition (MVMD) and morphological gradient is proposed. Firstly, the minimum comprehensive entropy kurtosis ratio is used as the fitness function, and the marine predator algorithm is used to realize the automatic optimization of the mode number and penalty factor of the multivariate variational mode decomposition. Therefore, with the goal of decomposing the traveling wave characteristic signals with the most significant traveling wave characteristic information and the lowest noise component, the line-mode traveling wave and the zero-mode traveling wave are accurately decomposed. Secondly, the intrinsic mode function component with the smallest entropy kurtosis ratio is selected as the line-mode traveling wave characteristic signal and the zero-mode traveling wave characteristic signal, respectively, and the arrival time of the wave head is accurately calibrated by combining the morphological gradient value. Finally, the fault distance is calculated by the modulus wave velocity difference location formula and compared with the variational mode decomposition-Teager energy operator (VMD-TEO) method and the empirical mode decomposition _first-order difference method. The results show that the proposed method has the highest accuracy of positioning results, and the algorithm time is significantly reduced compared with the VMD-TEO method, and it has strong adaptability to different line types of faults, different fault initial conditions, and noise interference. Full article

Sinkholes, naturally occurring formations in karst regions, represent a significant environmental hazard, threatening infrastructure, agricultural lands, and human safety. In recent years, machine learning (ML) techniques have been extensively employed for sinkhole susceptibility mapping (SSM). However, the lack of explainability inherent in these methods remains a critical issue for decision-makers. In this study, sinkhole susceptibility in the Konya Closed Basin was mapped using an interpretable machine learning model based on SHapley Additive exPlanations (SHAP). The Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM) algorithms were employed, and the interpretability of the model results was enhanced through SHAP analysis. Among the compared models, the RF model demonstrated the highest performance, achieving an accuracy of 95.5% and an AUC score of 98.8%, and was consequently selected for the development of the final susceptibility map. SHAP analyses revealed that factors such as proximity to fault lines, mean annual precipitation, and bicarbonate concentration difference are the most significant variables influencing sinkhole formation. Additionally, specific threshold values were quantified, and the critical effects of these contributing factors were analyzed in detail. This study underscores the importance of employing eXplainable Artificial Intelligence (XAI) techniques in natural hazard modeling, using SSM as an example, thereby providing decision-makers with a more reliable and comparable risk assessment. Full article

Nowadays, renewable energy facilities are coming to the forefront in order to protect nature and prevent climate change. In this context, location-based analyses are carried out for the most optimal use of renewable energy resources. This study aims to identify suitable locations for photovoltaic (PV) farms in Gaziantep using the Analytical Hierarchy Process (AHP) and Geographic Information System (GIS) technologies. The research incorporates various criteria, including solar radiation, land use, slope, aspect, distance to road, fault line proximity, distance to powerlines, and wind speed to evaluate potential sites for solar energy production. The AHP method is applied to prioritize these criteria through a pairwise comparison matrix and to calculate the weight values for each factor. The analysis reveals that approximately 80% of Gaziantep’s land is suitable for PV farm installation, with the southern region being the most favorable. Furthermore, the comparison between existing PV installations and the identified suitable areas highlights a high degree of alignment, with most of the current PV farms located in areas classified as suitable or highly suitable. Additionally, it was determined that 92% of the existing PV farms have been established within suitable areas. This indicates a high alignment between the identified suitable zones and the locations of the current PV installations, reflecting an effective site selection process based on the applied criteria. The study concludes that GIS-based AHP is an effective tool for rapid and reliable decision-making in renewable energy site selection, offering a valuable approach for future solar energy projects in Gaziantep and similar regions. Full article

This article presents research on the possibilities of using information and communication technologies in monitoring systems for electrical networks with isolated neutral, aimed at improving and automating production functions in the energy sector. This aligns with the digitalization policy of Kazakhstan’s economy and is part of similar programs in the field of the electric power industry. This article explores an approach to organizing a digital monitoring system for emergency conditions, specifically single-phase ground faults in medium-voltage lines within the range of 6–35 kV, including the new voltage class of 20 kV. A version of such a system is proposed, based on a combination of a server, a wireless information network, and remote digital voltage measurement nodes. This wireless information and communication network is designed to detect the locations of single-phase ground faults (SPGF) using specialized zero-sequence voltage sensors installed at various points along the power transmission lines, along with wireless signal transmission channels to the dispatcher’s server. To ensure protection against industrial interference, based on the results of practical environment modeling, a transmission technology most resistant to external noise is selected. This article proposes the selection of equipment necessary for implementing wireless transmission technology and develops two versions of a digital voltmeter design based on low-power programmable microcontrollers. The proposed technical solutions require further experimental validation, and therefore, the authors plan to conduct additional research and practical experiments in the future. Full article