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Here, we propose a sensing scheme based on an all-dielectric metamaterial with the smooth reflection and transmission spectral lines in 10-60THz, and verify the applications of the measuring the resonance characteristics of Xuan paper samples. The reflection and thermal conductivity of Xuan paper samples enhance with the concentration of alum water increasing and weaken due to the thickness increasing. These results provide a solid foundation for this metamaterials in measuring the reflective and thermal resonance properties of Xuan paper samples. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of volume traps intentionally introduced into a silicon-on-insulator (SOI) substrate by inserting a layer of polysilicon beneath buried oxide. In radio frequency applications, this type of substrate, referred to as trap-rich, is known to considerably reduce the generation of harmonics resulting from the parasitic non-linear charge dynamics introduced by the substrate handler under the buried oxide. This analysis focuses on a test vehicle in the form of an integrated coplanar waveguide on two types of substrates, namely, high-resistivity SOI substrates with and without a trap-rich layer. From a modeling point of view, a simulation methodology is implemented in order to convert the 3D simulation of the coplanar waveguide into a 2D treatment that takes into account the wave propagation effect associated with the distributed nature of the transmission line. As a first step, this modeling strategy is implemented to reproduce the effect of increasing substrate resistivity on 2nd and 3rd harmonic reductions, leading to an excellent agreement with experimental data. Building on this validation of the simulation method, we have opted to simulate the non-linear response of the transmission line on the SOI trap-rich substrate by simplifying the trap distribution model. To avoid the adoption of unverified and strongly process-dependent trap distributions across the bandgap, a midgap monovalent trap density has been introduced, either acceptor or donor density. A monovalent density of acceptor traps with a concentration of 1016 cm−3 and a carrier lifetime of 0.1 ns has been shown to reproduce the experimental data very accurately with a substantial reduction in 2nd and 3rd harmonics. A detailed analysis of the displacement current waveforms explains the beneficial role of acceptor traps compared with donor traps. [ABSTRACT FROM AUTHOR]

The combination of the dark fiber in existing Optical Fiber Composite Overhead Ground Wire (OPGW) with Distributed Optical Fiber Sensing (DOFS) technology can be used to enable online monitoring and provide early warnings of anomalies in high-voltage transmission lines. Accurate mapping of the optical cable length to the geographic coordinates of actual towers is a key factor in achieving this goal. This paper discusses the principle of using a DOFS system for transmission line tower positioning and presents four available positioning features. To overcome the limitations of single physical parameter positioning, this paper presents a self-developed hybrid DOFS that simultaneously captures Rayleigh backscattering and Brillouin scattering signals. Several physical parameters, including temperature, strain, and vibration, are acquired synchronously. Through hybrid multi-parameter analysis, the rapid and accurate positioning of OPGW line towers is achieved. Experimental results have shown that the proposed method, based on the hybrid DOFS system, can locate up to 82 towers, while the traditional method could only identify 12. The hybrid system was able to complete 80% of the tension towers in 40 h. This paper presents a novel multi-parameter localization method that has the potential to significantly improve the efficiency and reliability of grid operation and maintenance. [ABSTRACT FROM AUTHOR]

Radio stations are seriously affected by transmission line reradiation interference, but most of the existing methods for analyzing and solving reradiation interference on transmission lines focus on approximating the physical problem through mathematical models and algorithms, and it is difficult to study the correlation between transmission lines and reradiation interference in depth. This paper introduces the characteristic mode theory to study the influence factors of reradiation interference on transmission lines, which can decompose the surface induced current of transmission lines into a series of mutually orthogonal mode currents. This paper verifies the correctness of applying the MS (mode significance) value of the characteristic mode theory to analyze the reradiation interference through a simple transmission line example. Taking a line with 5 towers as an example, by analyzing the characteristic mode currents of transmission lines with different forwarding angles and linear arrangements, we not only verified that the characteristic mode currents can well characterize the reradiation interference, but also verified that the characteristic currents of different modes have a direct connection with the structure of the line, which can be applied in the process of designing or reconstructing the towers of the transmission lines, to predict the influence of different structural parameters on electromagnetic scattering, so as to optimize the tower design to reduce the reradiation interference effects and thus optimize the tower design to reduce reradiation interference. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Semantic segmentation of target objects in power transmission line corridor point cloud scenes is a crucial step in powerline tree barrier detection. The massive quantity, disordered distribution, and non-uniformity of point clouds in power transmission line corridor scenes pose significant challenges for feature extraction. Previous studies have often overlooked the core utilization of spatial information, limiting the network's ability to understand complex geometric shapes. To overcome this limitation, this paper focuses on enhancing the deep expression of spatial geometric information in segmentation networks and proposes a method called BDF-Net to improve RandLA-Net. For each input 3D point cloud data, BDF-Net first encodes the relative coordinates and relative distance information into spatial geometric feature representations through the Spatial Information Encoding block to capture the local spatial structure of the point cloud data. Subsequently, the Bilinear Pooling block effectively combines the feature information of the point cloud with the spatial geometric representation by leveraging its bilinear interaction capability thus learning more discriminative local feature descriptors. The Global Feature Extraction block captures the global structure information in the point cloud data by using the ratio between the point position and the relative position, so as to enhance the semantic understanding ability of the network. In order to verify the performance of BDF-Net, this paper constructs a dataset, PPCD, for the point cloud scenario of transmission line corridors and conducts detailed experiments on it. The experimental results show that BDF-Net achieves significant performance improvements in various evaluation metrics, specifically achieving an OA of 97.16%, a mIoU of 77.48%, and a mAcc of 87.6%, which are 3.03%, 16.23%, and 18.44% higher than RandLA-Net, respectively. Moreover, comparisons with other state-of-the-art methods also verify the superiority of BDF-Net in point cloud semantic segmentation tasks. [ABSTRACT FROM AUTHOR]

South Africa is currently experiencing an energy crisis because of a mismatch between energy supply and demand. Increasing energy demand necessitates the adequate operation of generation and transmission facilities to maintain the reliability of the power system. Transmission line compensation is used to increase the ability to transfer power, thereby enhancing system stability, voltage regulation, and reactive power balance. Also, in recent years, the introduction of renewable energy sources (RES) has proven to be effective in supporting the grid by providing additional energy. As a result, the dynamics of power systems have changed, and many developing nations are adopting the integration of renewable energy into the grid to increase the aspect ratio of the energy availability factor. While both techniques contribute to the grid's ability to meet energy demand, they frequently introduce technical challenges that affect the stability and protection of the systems. This paper provides a comprehensive review of the challenges introduced by transmission line compensation and the integration of renewable energy, as well as the various techniques proposed in the literature to address these issues. Different compensation techniques, including fault detection, classification, and location, for compensated and uncompensated transmission lines, including those connected to renewable energy sources, are reviewed. This paper then analyzes the adaptive distance protection schemes available in the literature to mitigate the impact of compensation/integration of RES into the grid. Based on the literature reviewed, it is essential for protection engineers to understand the dynamics introduced by network topology incorporating a combination of RES and heavily compensated transmission lines. [ABSTRACT FROM AUTHOR]

This paper calculates and analyses electric fields generated by high-voltage overhead power transmission lines. These fields have significant implications for safety and design considerations. The study utilises a numerical technique to determine the electric field distribution in regions containing multiple charges. Based on this method, a computer program is developed to calculate the electric field profile at ground level and two meters above ground level for both 400 kV overhead power lines. The results demonstrate the method's effectiveness in accurately computing the electric field intensity for various line configurations, making it applicable to any power line design. The paper also highlights the potential health effects associated with exposure to these electric fields, including leukaemia, breast cancer, cognitive impairments, and reproductive consequences. The proposed method can also be applied to other transmission lines, providing valuable insights into health considerations. The accuracy of the computation methods is validated using the finite element analysis method. This research contributes to the understanding and assessing ground-level electric fields, offering industry professionals and researchers valuable insights into the safety and design of power transmission systems. [ABSTRACT FROM AUTHOR]

Due to the influence of many factors, distribution cables are often densely placed at the bottom of the cable trench. As a result, it is easy for distribution cables to become the thermal bottleneck of the whole transmission line. To address this dilemma, this paper establishes a finite element simulation model of a cable trench to analyze the hot spots of cables with different arrangements in the cable trench. Then, the model's accuracy is verified based on real temperature rise experiments. For an arrangement with overheating risk, the ampacity improvement method of filling the cable trench with high-thermal-conductivity material was proposed, and the ampacity improvement effect under different filling ratios was assessed. Finally, combined with the analysis of economic benefit and cost, the method of determining the optimal filling ratio was used, and the impact resistance of the cables under the impact of new energy load was analyzed. The results indicate that, for the case of the optimal filling ratio, the cables in the dense cable trench showed superior impact resistance. The investigations in this paper make significant contributions to the promotion of the maximum utilization of cables. [ABSTRACT FROM AUTHOR]

One of the key challenges in Multi-Spectral Automatic Diagnostic (MAD) robot design is the precise targeting of narrow-angle cameras on a specific part of the equipment. The paper shows that a low-cost MAD robot, whose navigation system is based on open-source ArduRover firmware and a pair of low-cost Ublox F9P GNSS receivers, can inspect the 8 × 4 degree ultraviolet camera bounding the targeting error within 0.5 degrees. To achieve this result, we propose a new targeting procedure that can be implemented without any modifications in ArduRover firmware and outperforms more expensive solutions based on LiDAR SLAM and UWB. This paper will be interesting to the developers of robotic systems for power equipment inspection because it proposes a simple and effective solution for MAD robots' camera targeting and provides the first quantitative analysis of the GNSS reception conditions during power equipment inspection. This analysis is based on the experimental results collected during the inspection of the overhead power transmission lines and equipment inspections on the open switchgear of different power plants. Moreover, it includes not only satellite, dilution of precision, and positioning/heading estimation accuracy but also the direct measurements of angular errors that could be achieved on operating power plants using GNSS-only camera targeting. [ABSTRACT FROM AUTHOR]

Ferrite-loaded gyromagnetic nonlinear transmission line (GNLTL) provides a possible option to compress an input pulse to a narrower width for its remarkable sharpening effect. However, it is difficult to accurately predict the output of the GNLTL due to the complex interaction between the magnetic moment of ferrite and the bias magnetic field. In this paper, a finite element model of the GNLTL is established based on the Landau–Lifshitz–Gilbert equation to investigate the performance of the GNLTL. To validate this model, a prototype is used for experimental comparison. The result demonstrates good agreement between experiment and simulation. This paper further explores the influence of the bias magnetic field and the length of the GNLTL on the output pulse. Moreover, a method to sharpen the falling edge is proposed based on the reflection and superposition of the GNLTL output. Simulation and experimental results show its effectiveness and feasibility. [ABSTRACT FROM AUTHOR]

With the penetration of DGs in power systems, some restrictions such as economic dispatch in non-dispatchable sources, their control technology and voltage/frequency stability may be challenging. In conventional power systems, the transient stability has been obtained by high-inertia of upstream network in all conditions; however, in modern power grids, the micro grids (MGs) which could operate in both islanded mode and grid-connected mode are taken into account to overcome this issue. AC or DC types of DGs usually connect to the loads through power electronic converters, in which for researchers, this issue has been interesting and applicable to continue. When loads have been changed, the frequency has influenced correspondingly and must not exceed the permissible range. Therefore in this paper, this intention has been studied using conventional droop controller and intelligent sliding surface approach (ISSA) to evaluate the DGs effects on load-frequency control. While two or more areas (as some individual MGs) connect to each other via a transmission line, the voltage/frequency stability and power balancing constrained may be changed, which the ISSA is hired to track the frequency changes. To examine this problem, in this paper there are three MGs operate separately to show if the load may not supply, they should connect to adjacent block. If this important concern has not considered, it may cause global black-out. The simulation results obtained by ISSA compared with droop controller method represent the superiority of proposed technique to achieve best power sharing. [ABSTRACT FROM AUTHOR]

This paper proposes a novel methodology to improve stability in a transmission system under critical conditions of operation when additional loads that take the system to the verge of stability are placed in weak bus bars according to the fast voltage stability index (FVSI). This paper employs the Newton–Raphson method to calculate power flows accurately and, based on that information, correctly calculate the FVSI for every transmission line. First, the weakest transmission line is identified by considering N − 1 contingencies for the disconnection of transmission lines, and then all weak nodes associated with this transmission line are identified. Following this, critical scenarios generated by stochastically placed loads that will take the system to the verge of instability will be placed on the identified weak nodes. Then, the methodology will optimally size and place a single static VAR compensator SVC in the system to take the transmission system to the conditions before the additional loads are connected. Finally, the methodology will be validated by testing the system for critical contingencies when any transmission line associated with the weak nodes is disconnected. As a result, this paper's methodology found a single SVC that will improve the system's stability and voltage profiles to similar values when the additional loads are not connected and even before contingencies occur. The methodology is validated on three transmission systems: IEEE 14, 30, and 118 bus bars. [ABSTRACT FROM AUTHOR]

The application of distributed sensors in smart transmission lines to replace traditional inspection methods is an inevitable trend. Currently, the challenge of energy supply for sensors serves as a bottleneck that hinders the intelligent development of transmission lines. This paper focuses on the application of self‐powered inspection technology based on triboelectric and electromagnetic mechanisms in transmission lines. It proposes a self‐powered temperature and vibration monitoring and warning system (STV‐MWS) for multi‐parameter monitoring of transmission line status. This work utilizes the quasi‐zero stiffness structure and center misalignment design to improve the output performance of STV‐MWS at low vibration amplitude, thereby extending its vibration amplitude response range. The STV‐MWS is capable of harvesting and monitoring vibration of 50 µm and above vibration amplitude and 2–700 Hz vibration frequencies, which fully covers the breeze vibration range of transmission lines. Through the split package design, the flexible deployment of STV‐MWS is achieved, further enhancing its engineering application value. This work can effectively ensure that the transmission line inspection can carry out accurate status monitoring and intelligent analysis in the environment characterized by steep terrain, challenging power extraction, and difficult fault judgment, thereby realizing the visualization and intelligence of the transmission line status. [ABSTRACT FROM AUTHOR]

Bird‐related outages greatly threaten the safety of overhead transmission and distribution lines, while electrocution and collisions of birds with power lines, especially endangered species, are significant environmental concerns. Automatic bird recognition can be helpful to mitigate this contradiction. This paper proposes a method for automatic classification of bird species related to power line faults combining deep convolution features with error‐correcting output codes support vector machine (ECOC‐SVM). An image dataset of about 20 high‐risk and 20 low‐risk bird species was constructed, and the feed‐forward denoising convolutional neural network was used for image preprocessing. The deep convolution features of bird images were extracted by DarkNet‐53, and taken as inputs of the ECOC‐SVM for model training and bird species classification. The gradient‐weighted class activation mapping was used for visual explanations of the model decision region. The experimental results indicate that the average accuracy of the proposed method can reach 94.39%, and its performance was better than other models using different feature extraction networks and classification algorithms. [ABSTRACT FROM AUTHOR]

Designing and fabricating a directional coupler with composite right/left-hand (CRLH) transmission lines with a coupling level of 15 dB is presented in this paper. Compared to conventional couplers, this asymmetric structure has achieved this coupling level compared to the simple transmission line. This structure is comprised of interdigital capacitors and short connection stubs. The distance between two coupled lines is equal to 0.4 mm, and the stubs are spirally designed to compress the structure. The subs' length is approximately equal to λ/4, and the impedance of the ports is equal to 50 Ω. After designing and simulating, the coupler was fabricated and measured. The directional coupler at the frequency of 1.9 GHz has an isolation level of 44 dB and a directivity of 67.1 dB. Overall, construction and simulation results are in good agreement. [ABSTRACT FROM AUTHOR]

In this paper, a ferrite-filled rectangular waveguide as a balanced composite right/left-handed (CRLH) transmission line is considered. Based on the surface current density of dominant mode, a centerline longitudinal slot on the broad wall of this ferrite-filled rectangular waveguide can be radiate to the free space as a leaky-wave antenna (LWA). This proposed LWA has the both capability of the fixed-bias frequency scanning and fixed-frequency bias scanning from negative to positive angles. However, the gain of the centerline slotted ferrite-filled rectangular waveguide antenna is not acceptable. By adding another slot and changing the position of slots on the broad wall, the gain is improved to more than 9 dB in frequency range of 6.59–6.69 GHz. [ABSTRACT FROM AUTHOR]

When cables use many wires packed in a hexagonal pattern wrapped by bands around the surface, effective stiffness plays an important role in structural integrity and safety. This paper studies cylindrical wires packed in a hexagonal lattice tightened up by wrapping bands. When a transverse load is applied, the stress transferred through the contacts between the wires can be represented by a center-center force network with the Hertz contact theory. When yielding is considered in the contact zone, an elastoplastic contact model is developed. The Singum model simulates the singular forces by the stress between continuum particles. The effective stress-strain relationship changes with the stress of the wrapping bands and exhibits isotropic behavior in the cross section. Therefore, the overall elastic behavior of the cable is transversely isotropic with a tailorable stiffness in the cross section by the wrapping force. This method is general for mechanical modeling of packed parallel wire cables, and its application to bridge cable testing and repair with development length prediction is underway. Practical Applications: This study introduces a novel approach, the Singum model, for analyzing the overall mechanical properties of packed wire cables, which are crucial for ensuring structural integrity and safety in various engineering applications. By investigating the effective transverse stiffness of packed wire cables through a combination of theoretical modeling, finite element analysis (FEM), and experimental tests, this research provides valuable insights into optimizing cable design and performance across diverse engineering applications such as cable domes, electric transmission lines, tramways, cable-stayed bridges, and suspension bridges. The findings highlight the significant impact of wrapping force on the effective stiffness of packed cylinders, offering engineers a means to tailor the stiffness of cable cross sections for specific requirements in these applications. This study provides a robust framework for advancing the understanding and optimization of packed wire cable systems in engineering practice with reasonable assumptions and simplifications, which can be tailored for specific materials or applications. [ABSTRACT FROM AUTHOR]

This paper presents the findings of the research aimed at developing computer models to determine the operating conditions in electric power systems (EPSs) feeding DC and AC railway substations. The object of the research is an EPS with a predominant traction load whose high-voltage power lines are connected to transformer and converter substations with 3 kV and 27.5 kV traction networks. The supply network includes 110 kV and 220 kV power lines. The EPS operating parameters are calculated based on the decomposition of the system into alternating and direct current segments. Calculations are performed for the fundamental frequency and high harmonic frequencies. The modeling technique is universal and can be used to determine the operating parameters and power quality indices for any configuration of an EPS and various designs of traction networks. With this technique, one can solve numerous additional problems, such as calculating the processes of ice melting in traction networks and power lines, determining electromagnetic field strengths, and assessing the heating of power line wires and catenary suspensions. The results obtained show that the voltages on the current collectors are within acceptable limits for all AC and DC electric locomotives. The levels of asymmetry on the 110 and 220 kV tires of traction substations (TP) do not exceed the normally permissible values. The values of the asymmetry coefficients for DC TP are tenths of a percent. With an increase in the size of traffic and in post-emergency conditions caused by the disconnection of communication between one of the support substations and the EPS, the asymmetry indicators on the 220 kV buses of AC substations may exceed the permissible limits. Phase-controlled reactive power sources can be used to reduce them. The analysis of the results of the determination of non-sinusoidal modes allows us to formulate the conclusion that the values of harmonic distortion go beyond the normative limits. Passive and active filters of higher harmonics can be used to normalize them. Calculations of thermal modes of traction transformers show that the temperatures of the most heated points do not exceed acceptable values. [ABSTRACT FROM AUTHOR]

The prevailing approach to the wind resistance design of transmission towers is rooted in the quasi-static method. However, this methodology faces criticism for neglecting tower-line coupling dynamics. Despite efforts to boost structural wind resilience, the research on tower failure mechanisms, especially under extreme winds considering tower-line coupling, is limited. To address this gap, the wind-induced dynamic failure modes of the transmission tower-line system are investigated in this paper. The consistent discrete random flow generation method is employed to simulate the fluctuating wind field for transmission lines. Incorporating the compressive buckling mode of angle steel, the plastic hinge model of the frame element is employed to simulate mechanical nonlinearity. A typical transmission tower-line system is concerned, with a finite element model established for a three-tower, four-line coupled configuration. The findings reveal that the wind-induced collapse of the transmission tower is directly triggered by the buckling failure of the compressed main members, with the vulnerable section located beneath the lower cross-arm. The transmission tower experiences bidirectional bending and compression instability under an unfavorable wind direction. In contrast, the traditional pushover collapse modes of the transmission tower cannot fully capture the characteristics of the collapse failure, mainly due to the ignorance of the transverse wind force action induced by the coupling effect. This research underscores the importance of incorporating lateral dynamic considerations into transmission tower designs and advocates for optimizing strategies to mitigate wind-induced collapse modes. [ABSTRACT FROM AUTHOR]

Industrial development and population growth have increased the need for higher-capacity power transmission lines. Aluminum conductor steel-supported (ACSS) conductors, a type of high-temperature low-sag (HTLS) conductor, are now widely used in new designs and reconductoring applications. ACSS conductors are preferred over traditional aluminum conductor steel-reinforced (ACSR) conductors due to their high strength, low sag, and excellent thermal stability. These attributes have garnered significant interest from researchers, engineers, and manufacturers. This paper provides a comprehensive review of the structure, properties, testing methods, and environmental behavior of ACSS conductors. [ABSTRACT FROM AUTHOR]

Current sensors based on the tunneling magnetoresistive effect (TMR) are widely used for current measurement due to their high sensitivity, small size, and low power consumption. This paper proposes an effective error correction model to rectify the eccentricity of the transmission line, which can cause a significant measurement error in the ring‐array single‐axis TMR sensor. The model employs a convolutional neural network (CNN) to identify the relationship between the conductor eccentricity and the output of three sensors. The resulting correction factor is then fed back to eliminate the error associated with wire eccentricity. Concurrently, the Sparrow search algorithm (SSA) is employed to optimize the hyperparameters of the convolutional neural network (CNN) in order to enhance the model's performance. The experimental results demonstrate that the maximum error of the ring‐array single‐axis TMR current sensor, corrected by SSA‐CNN, is less than 0.42%, which markedly enhances the precision of the measurement. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper introduces a novel method that leverages artificial neural networks to estimate magnetic flux density in the proximity of overhead transmission lines. The proposed method utilizes an artificial neural network to estimate the parameters of a mathematical model that describes the magnetic flux density distribution along the lateral profile for various configurations of overhead transmission lines. The training target data is acquired using the particle swarm optimization algorithm. A performance comparison between the proposed method and the Biot-Savart law-based method is conducted using an extensive test dataset. The resulting coefficient of determination and mean square error values demonstrate the successful application of the proposed method for a range of different spatial arrangements of phase conductors. Furthermore, the performance of the proposed method is thoroughly assessed on multiple test cases. The practical relevance of the proposed method is highlighted by contrasting its results with the field measurements obtained in the proximity of a 400 kV overhead transmission line. [ABSTRACT FROM AUTHOR]

Definition: On 1 January 2001, the IEC 61000-3-2 regulation became effective. Since then, mitigating current harmonics has been essential to ensure that electronic equipment connected to single-phase power distribution lines conforms to electromagnetic compatibility directives. Today, high-quality rectification, commonly known as power factor correction (PFC), is a well-established technique widely adopted by the industry for powering various devices from the ac line. The topic has been studied by academia and industry since the mid-1980s; thus, an enormous amount of research has been published and countless solutions have been proposed since then. However, only a few of those solutions have encountered wide industrial usage. So, it is not the authors' intention to provide a comprehensive review, but to take stock of the most used PFC techniques from an industry perspective. This paper will review the power factor theory with non-sinusoidal currents, the practical and regulatory aspects of using PFC, and the most common industry solutions for power factor correction in equipment operated from the single-phase, public, low-voltage supply system, with a special focus on boost PFC pre-regulators, their control methods, design procedures, and issues. [ABSTRACT FROM AUTHOR]

Inspecting and maintaining power lines is essential for ensuring the safety, reliability, and efficiency of electrical infrastructure. This process involves regular assessment to identify hazards such as damaged wires, corrosion, or vegetation encroachment, followed by timely maintenance to prevent accidents and power outages. By conducting routine inspections and maintenance, utilities can comply with regulations, enhance operational efficiency, and extend the lifespan of power lines and equipment. Unmanned Aerial Vehicles (UAVs) can play a relevant role in this process by increasing efficiency through rapid coverage of large areas and access to difficult-to-reach locations, enhanced safety by minimizing risks to personnel in hazardous environments, and cost-effectiveness compared to traditional methods. UAVs equipped with sensors such as visual and thermographic cameras enable the accurate collection of high-resolution data, facilitating early detection of defects and other potential issues. To ensure the safety of the autonomous inspection process, UAVs must be capable of performing onboard processing, particularly for detection of power lines and obstacles. In this paper, we address the development of a deep learning approach with YOLOv8 for power line detection based on visual and thermographic images. The developed solution was validated with a UAV during a power line inspection mission, obtaining mAP@0.5 results of over 90.5% on visible images and over 96.9% on thermographic images. [ABSTRACT FROM AUTHOR]

To address the frequent external damage incidents to transmission line corridors caused by construction machinery such as excavators and cranes, this paper constructs a dataset of external damage hazards in transmission line corridors and proposes a detection method based on YOLO-LSDW for these hazards. Firstly, by incorporating the concept of large separable kernel attention (LSKA), the spatial pyramid pooling layer is improved to enhance the information exchange between different feature levels, effectively reducing background interference on external damage hazard targets. Secondly, in the neck network, the traditional convolution is replaced with a ghost-shuffle convolution (GSConv) method, introducing a lightweight slim-neck feature fusion structure. This improves the extraction capability for small object features by fusing deep semantic information with shallow detail features, while also reducing the model's computational load and parameter count. Then, the original YOLOv8 head is replaced with a dynamic head, which combines scale, spatial, and task attention mechanisms to enhance the model's detection performance. Finally, the wise intersection over union (WIoU) loss function is adopted to optimize the model's convergence speed and detection performance. Evaluated on the self-constructed dataset of external damage hazards in transmission line corridors, the improved algorithm shows significant improvements in key metrics, with mAP@0.5 and mAP@0.5:0.95 increasing by 3.4% and 4.6%, respectively, compared to YOLOv8s. Additionally, the model's computational load and parameter count are reduced, and it maintains a high detection speed of 96.2 frames per second, meeting real-time detection requirements. [ABSTRACT FROM AUTHOR]

For microgrids in deep and remote sea areas, ocean currents are widely used as an emerging power generation resource. Implementing ES systems is crucial for smooth power output and grid stability. The stability of power output from sea current energy generation faces challenges due to speed fluctuations. Enhancing resilience requires addressing transmission line failures caused by extreme seabed conditions, and ensuring operational security. An ES configuration method considering line faults based on two-stage robust optimization is presented in this paper. First, in order to simultaneously consider planning and operation, a defender–attacker–defender (DAD) model was established. Additionally, the capacity, rated power, and charging/discharging power of ES during operation were jointly optimized through the column-and-constraint generation (C&CG) algorithm. In addition, the rationality and effectiveness of the proposed method were demonstrated through experiments on modified IEEE six-bus and fifty-seven-bus systems. The results show that a distributed ES configuration increased system resilience by 54.60% and reduced abandoned power rate by 57.06% compared with the situation without ES configuration. [ABSTRACT FROM AUTHOR]

This paper implements the stochastic filters for state and parameter estimation of nonuniform transmission lines (NTL). In general, transmission line (TL) problem is a continuous time and space problem. By taking the line loading noise into account, the TL equations become a stochastic partial differential equation (PDE) rather than a simple set of coupled finite stochastic differential equations (SDE). By transforming the spatial variables into the Fourier domain, the stochastic PDE can be transformed into an infinite sequence of SDE. After truncation to a finite set of Fourier series coefficients, it becomes a finite set of coupled linear SDE, which is the required domain in which extended Kalman filter (EKF) and unscented Kalman filter (UKF) can be applied. For state space equation of EKF and UKF, the voltage and current of periodic NTL are expanded into an infinite set of spatial harmonics. In this way, the voltage and current measurement of NTL become an eigenvalue problem. The NTL is considered as cascade of small infinite NTL and the four distributed primary parameters of the periodic NTL are expressed using Fourier series expansion. Finally, the Kalman filter (KF)-based state estimation and the EKF- and UKF-based parameter estimation have been compared with recursive least squares (RLS) method. The simulation results present the superiority of the method. [ABSTRACT FROM AUTHOR]

Fault detection, classification, and location prediction are crucial for maintaining the stability and reliability of modern power systems, reducing economic losses, and enhancing system protection sensitivity. This paper presents a novel Hierarchical Deep Learning Approach (HDLA) for accurate and efficient fault diagnosis in transmission lines. HDLA leverages two-stage transformer-based classification and regression models to perform Fault Detection (FD), Fault Type Classification (FTC), and Fault Location Prediction (FLP) directly from synchronized raw three-phase current and voltage samples. By bypassing the need for feature extraction, HDLA significantly reduces computational complexity while achieving superior performance compared to existing deep learning methods. The efficacy of HDLA is validated on a comprehensive dataset encompassing various fault scenarios with diverse types, locations, resistances, inception angles, and noise levels. The results demonstrate significant improvements in accuracy, recall, precision, and F1-score metrics for classification, and Mean Absolute Errors (MAEs) and Root Mean Square Errors (RMSEs) for prediction, showcasing the effectiveness of HDLA for real-time fault diagnosis in power systems. [ABSTRACT FROM AUTHOR]

In order to improve the measurement accuracy of mutual inductance parameters of transmission lines in the environment of double circuit power lines without power outage, this paper establishes simulation models for measuring mutual inductance parameters of transmission lines using the different frequency method in two modes: equal and unequal zero sequence self‐parameters of two circuit lines, using a parallel zero sequence coupling model of double circuit power lines. In the article, simulation analysis is conducted on the line parameters with a coupling coefficient between 0.4 and 0.6 and a line length of 20–50 km. In order to further verify the correctness of the simulation model and measurement methods, a test bench was established based on the principle of line mutual inductance parameter testing in a laboratory dual circuit line without a power outage environment for experimental testing. By comparing the test values under experimental conditions with the standard values, it has been proven that the model and method can meet the actual measurement requirements of engineering. [ABSTRACT FROM AUTHOR]

This paper presents a novel technique for matching complex loads to a real source concurrently at uncorrelated frequencies under any load conditions. In the proposed method, a branched stub adds susceptances to the load admittances such that the adjusted loads for all the frequencies can be shifted to g = 1 circle using a single series transmission line; hence matching the real part of the admittances. The left-over susceptance is cancelled through another branched stub. Its adaptability allows it to increase the number of bands by adding transmission lines to the branched stubs. The structure is not subject to any fabrication-related limitations because all the transmission lines used in the design have a characteristic impedance of 50 Ohms. The concept has been validated by designing a prototype matching network for N = 3 and extending it to N = 4, and N = 5 by adding elements to the branched stubs. All the structures are fabricated on ROGERS RO4003 substrate with a dielectric constant, er = 3.38 and height, h = 20 mils. The simulated and the measured results are in good accordance. [ABSTRACT FROM AUTHOR]

Abstract—Dynamic exploration and development of the Arctic zone of the Russian Federation is inextricably linked to the need to minimize risks to the technosphere, associated, among other things, with space weather effects on power equipment systems operated within the coverage of the auroral oval. At the same time, the concomitant monitoring of space weather parameters and variations of the geomagnetic field in the Arctic is carried out only by means of a small group of satellites and several dozens of magnetic stations located mainly in the USA, Canada, northern and central Europe. It is clear that the current situation practically excludes the possibility of operational diagnostics of the level of geomagnetically induced currents (GIC) for the most part of the Arctic zone of the Russian Federation, where, in fact, the only available indicator of space weather conditions are polar auroras. The paper proposes an approach to interpreting aurora appearance to assess space weather impact on high-latitude infrastructure facilities. Based on the case study of the "Vykhodnoy" substation of the "Severnyi Tranzit" (Northern Transit) main electric transmission line it is shown that when the aurora is observed in the north, at the zenith (overhead), and in the south relative to the observation point, the most probable (30-min average) GIC is 0.08, 0.23, and 0.68 A, respectively. At the same time, the probability of half-hourly average GIC exceeding 2 A (with auroras observed in the north, overhead, and in the south relative to the impacted object) is ~6, ~10, and ~15%, respectively. Finally, the ways to improving the proposed technique and the applicability limits of the approach are discussed. [ABSTRACT FROM AUTHOR]

Fault diagnosis and detection in electrical power systems need a development of new and robust supervision structures. In the last years, different intelligent monitoring methods have been successfully proposed to deal with the problem of fault diagnosis in power transmission lines. In this work, a new hybrid strategy called FFT-FL combining Fuzzy Logic (FL) approach with Fast Fourier Transform (FFT) is proposed and applied to fault diagnosis in power line network. The elaborated fault detection structure consists of indicating whether the electrical transmission is working correctly or a fault has occurred with an effective isolation step to determine the faulty zone in the line. Whereas, an identification step consists of determining faulty phase thus fault classification in the studied line network. The novel proposed algorithm (FFT-FL) is used to improve the fault diagnosis response time and to decouple between faults and disturbances. In this paper, a comparative study is presented between the two intelligent methods for detection, isolation and identification of faults using only FL and the hybrid FFT-FL structure. The obtained simulation results verify the effectiveness and the correctness of the proposed fault method for all types of faults in the power line networks and in different zones. [ABSTRACT FROM AUTHOR]

ECG signals play a vital role in the diagnosis of cardiovascular conditions. However, they often suffer from the effects of various noise sources, including baseline wandering, respiratory artifact noise, power line interference and electrode motion artifacts. To overcome these challenges, it is imperative to implement low-frequency signal noise reduction strategies. Such strategies aim to significantly improve the quality of ECG signals, thus promoting more accurate and reliable diagnosis of cardiovascular disorders. This paper conducts a comparative analysis to assess the effectiveness of commonly used filtering and wavelet techniques in reducing Baseline Wander (BW) noise within ECG signals generated by the influence of breathing or electrode movements. It is common to observe the selection and evaluation of only one particular technique in the existing literature. In contrast, this study aims to provide a comprehensive comparative analysis, providing insight into the performance and relative merits of different techniques. Our research uses both filtering and Discrete Wavelet Transform (DWT) techniques in baseline noise removal. In this context, a reference point is established utilizing noise-free signals and a meticulous investigation of the wavelet-based approach that most effectively eliminates the resulting noise is provided. Subsequently, we assess the reference input and output signal via Signal-to-Noise Ratio (SNR) and Kolmogorov–Smirnov statistical test measurements. The most important contribution of this work to the scientific community resides in the comprehensive examination of IIR/FIR-based and wavelet method-based filtering methods capable of yielding the highest SNR levels across various ECG signals with various types of BW noise. Additionally, the effectiveness of the Chebychev-II filter in BW noise removal is highlighted. Our study was conducted using the MATLAB platform and code command lines were shared to facilitate the reproduction of our study by other researchers. It is considered that this study will be an important reference in the selection of effective techniques for removing BW noise within ECG signals. [ABSTRACT FROM AUTHOR]

In this paper, a new 180° broadband phase shifter with coupled microstrip line with enhanced coupling by etched slots is proposed, which uses the energy coupling between the parallel‐coupled microstrip lines on the upper layer of the dielectric substrate and the etched rectangular slots (RS) structure on the bottom floor to circumvent the problem for achieving wide operating broadband and low insertion loss with compact size and simple structure. First, the main line and the reference line of the proposed phase shifter are composed of two parallel coupled lines and a uniform transmission line, respectively. Then, its working mechanism is described. Afterward, the phase shifter introduced an RS structure to increase the coupling strength, achieving a broadband of 69.7% and very low insertion loss (0.09 dB) with a phase shift of 180 ± 5°. Finally, a prototype 180° phase shifter with a center frequency of 3.0 GHz was designed, fabricated, and measured, and the measured results are good in agreement with the simulated ones. [ABSTRACT FROM AUTHOR]

This paper presents various control strategies to improve operations in two interconnected areas connected by a VSC‐HVDC transmission line. The main focus is on designing a central control system (CCS) that coordinates control units in both areas. In area 1, an AC voltage control unit is connected to the CCS. In area 2, three control units including a load power control unit, a fault detection unit, and an AC voltage control unit are also connected to the CCS. The CCS receives inputs from these units and generates commands for the DC voltage and active/reactive power control units on both sides of the DC line. The first proposed strategy addresses permanent voltage drops caused by load fluctuations in area 2. It adjusts the transmitted power from area 1 based on voltage variations in area 2. The second strategy focuses on mitigating faults in area 2 by injecting active and reactive power from area 1 during such events. The third strategy resolves transient voltage oscillations in both areas by controlling the reactive power of stations on either side of the DC line. Simulations using MATLAB‐SIMULINK demonstrate that these mechanisms successfully achieve their objectives. [ABSTRACT FROM AUTHOR]

In the power grid, inspection robots enhance operational efficiency and safety by inspecting power lines for information sharing and interaction. Edge computing improves computational efficiency by positioning resources close to the data source, supporting real-time fault detection and line monitoring. However, large data volumes and high latency pose challenges. Existing offloading strategies often neglect task divisibility and priority, resulting in low efficiency and poor system performance. This paper constructs a power grid inspection offloading scenario using Python 3.11.2 to study and improve various offloading strategies. Implementing a game-theory-based distributed computation offloading strategy, simulation analysis reveals issues with high latency and low resource utilization. To address these, an improved game-theory-based strategy is proposed, optimizing task allocation and priority settings. By integrating local and edge computing resources, resource utilization is enhanced, and latency is significantly reduced. Simulations show that the improved strategy lowers communication latency, enhances system performance, and increases resource utilization in the power grid inspection context, offering valuable insights for related research. [ABSTRACT FROM AUTHOR]

Contingency analysis has been vastly explored within the context of power systems operation and security assessment. However, the impact of power quality indices into the contingency ranking and selection has not been well investigated in the literature. In order to fulfil this gap, a novel approach is proposed in this paper considering the effects of transmission lines outages in the voltage magnitudes and harmonic proliferation in power systems. The compensation theorem is applied to obtain the approximate effect of small changes in the elements of an electric network based on sensitivity analysis with the purpose of determining estimated harmonic voltages and currents in a lower computational time when compared with the traditional application of the iterative Newton–Raphson load flow methodology. Computational simulations are carried out using the IEEE 30 bus test system modified by the inclusion of non linear loads modelled as harmonic current injections. A comparative analysis is also presented considering the contingency selection using the proposed method, load flow algorithms and different ranking factors considering the impact of single contingencies into the power system voltages and total harmonic distortion variations. [ABSTRACT FROM AUTHOR]

The transistor has the problem of inability to tolerate high voltage, which leads to power quality issues in high power applications. Therefore, to solve this problem, a thyristor controlled series compensator (TCSC) is adopted, which will reduce the power quality problem in high power applications integrated with renewable systems. However, to reduce the effect of thyristors in TCSC, the gate turn-off (GTO) thyristors are employed. Also, the cost of the system is reduced by using PV based DC supply to the compensator. However, the supply from the renewable system is not constant, which induces harmonics and oscillation in output voltage. This results in an unsynchronized supply between the grid voltage and the renewable system, which has been reduced by using a novel controller that generates switching pulses for the GTO to reduce distortion in the output voltage. Since the GTO works well with switching signals rather than gate voltage, an effective control signal generation scheme is required. Therefore, this paper introduces a novel Fractional Order Proportional Integral Retarded (FOPIR) controller optimized by the Rock Hyraxes algorithm. As a result, the proposed controller reduced the harmonics to 17.52% with respect to the PIR controller. [ABSTRACT FROM AUTHOR]

Congestion in transmission lines will not be tolerable except for a short time as it may cause power outages and losses. In this paper, through multistage congestion management (CM), a conceptual framework for transmission CM is presented. At first, by the contingency analysis, uncertainties are prioritized based on their impacts on the congestion. Those with severe impacts (in congestion) are taken into account in the day ahead, while those with minor impacts are considered in the real time. It is because of the fact that all uncertainties do not happen in reality and considering all of them in the day ahead imposes high additional costs. In other words, the minor effect uncertainties are neglected in day ahead and are postponed to real time. Hence, even if they happen, they will be overcome by remedial measures with no significant concern. Then at each time interval (for both day ahead and real time), using the sensitivity analysis a congestion control zone is formed for each congested line. Finally, through the intelligent implementation of the nonlinear demand response programs (DRPs) and an alternative load shedding model, the congestion is alleviated. Results prove the effectiveness of the proposed methodology. [ABSTRACT FROM AUTHOR]

The impulse grounding impedance of the tower grounding device affects the lightning trip-out rate of the transmission line. It is necessary to optimize the design of the grounding device for impedance reduction. In this paper, a finite element model for the impulse property of the grounding device is established. The thin-shell theory is introduced to solve the problem of mesh division singularity caused by excessive dimensional differences between the conductor sectional area and soil dispersion area. Physical quantities such as potential, electric field strength, and current density of tower grounding devices were analyzed, and the impedance reduction mechanism of the needle-shaped grounding device was obtained. A simulation study of the needle-shaped tower grounding device was carried out to obtain the effects of five factors related to the needling: position, number, distance, length, and angle on the impulse grounding impedance, as well as their optimal values. The results show that adding the needling at the end of a star grounding electrode branch can effectively reduce the impulse grounding resistance. The number of needling is not the more the better, and the unit length utilization is maximum when 2 needles are used. Changes in the length of the needling have a greater impact on the impulse grounding resistance relative to changes in spacing. When the spacing between the two needles is 2 m and the length is 5 m, it is appropriate to set the angle in the range of 30°–60°. The optimized design of the tower grounding device can effectively reduce the impulse grounding impedance. [ABSTRACT FROM AUTHOR]

In this paper, we have investigated a tunable and high transmission efficiency plasmonic power splitter and also a wavelength demultiplexer based on metal–insulator-metal surface. By using Finite Difference Time Domain method, the power splitter exhibits high transmission peaks of about 45% in each output port. Additionally, the simulation results demonstrate that the equal transmitted wavelengths of the two output ports can be easily tuned by changing the geometric parameters of the waveguide. Subsequently, the structure was amended to become a demultiplexer with selecting wavelengths of 1272 and 912 nm, and transmission efficiencies of 76.44 and 88.03%, respectively. Following that, the dependence of demultiplexing wavelengths on geometrical parameters of the structure is investigated. Besides being highly compact and efficient, having narrow-band spectra and low reflectance coefficient are the other main advantages of these devices. The compact power splitter presented in this study is one of the critical components of an integrated processor and hence can be of great interest in a wide range of applications, from highly integrated photonic circuits to on-chip optoelectronic modules and other optical devices such as erbium-doped fiber amplifiers. [ABSTRACT FROM AUTHOR]

This paper introduces a new concept in transmission expansion planning based on unconventional lines, termed "smart transmission expansion planning". Traditionally, the domains of transmission expansion planning (TEP) and transmission line design are separate entities. TEP planners typically rely on the electrical specifications of a limited set of standard conventional line designs to evaluate planning scenarios, ultimately leading to the construction of the selected candidate line. In this context, it is noted that cost-effective scenarios often diverge from meeting the technical criteria of load flow analysis. To address this discrepancy, this paper proposes an alternative approach wherein TEP is conducted based on the specific requirements of the system earmarked for expansion. The transmission expansion planner initiates the process by determining optimal line parameter values that not only meet the operational criteria but also ensure cost-effectiveness. Subsequently, a line is designed to embody these optimal parameters. A detailed comparative analysis is conducted in this study, comparing the outcomes of TEP analyses conducted with conventional lines, unconventional lines, and lines featuring optimal parameters. Through extensive load flow analysis performed under normal and all single-contingency scenarios across three distinct loading conditions (peak load, dominant load representing 60% of peak load, and light load representing 40% of peak load), the results reveal that transmission lines engineered with optimal parameters demonstrate effective operation, with fewer transmission lines required to meet identical demands compared to other approaches. [ABSTRACT FROM AUTHOR]

Fault detection in transmission lines plays an important role in maintaining the dependability and steadiness of power networks. Traditional methods for identifying faults often struggle to handle the diverse nature of real-world fault situations. Machine learning (ML) algorithms offer a data-centered approach that can adjust and learn from datasets, potentially overcoming the limitations of traditional approaches. This paper presents a review of progress in using ML for detecting faults in transmission lines. By drawing insights from lots of studies, explores the paper how ML algorithms have evolved in fault detection, including techniques like networks, recurrent neural networks featuring long short-term memory (LSTM) and convolutional neural networks (CNN). The paper delves into the spectrum of applications where ML is used for fault detection across fault scenarios and operational settings. Additionally, it discuss the obstacles and prospects linked to putting ML-based fault detection systems into practice, such as challenges with data quality, model interpretability and integration with existing grid monitoring systems. Finally, the paper outlines future research paths focused on pushing forward the boundaries of fault detection in power transmission systems through approaches and collaborative endeavors involving academia, industry players and policymakers. In general, this review highlights how ML has the power to revolutionize fault detection methods, enhancing the resilience and dependability of power systems. [ABSTRACT FROM AUTHOR]

The coupling capacitance between the line and the transducer cannot be ignored when making non‐contact voltage measurements on low‐voltage three‐phase power lines. This leads to an increase in the number of unknown capacitances, and the number of correlatable response voltage equations is less than the number of unknown coupling capacitances. In this paper, a simplified decoupling method is proposed based on the characteristics of triangular three‐phase lines erected in distribution areas. Firstly, the equivalent circuit measured by the voltage sensing mechanism during three‐phase operation is established, and the three‐phase line response voltage equation is derived. Secondly, this paper proposes a three‐phase line response voltage decoupling algorithm after designing the decoupling matrix. Then, this paper uses the least squares method to solve the coefficients in the equations. Finally, the three‐phase voltage fluctuations of the actual low‐voltage stations are simulated by simulation. The measured sensor voltage values are substituted into the algorithm to invert and calculate the three‐phase line voltage. The three‐phase phase error is less than 2°. The amplitude error is less than 1.77%. The experiment verifies the stability and accuracy of the proposed decoupling method. [ABSTRACT FROM AUTHOR]

Power line inspection is an important means to eliminate hidden dangers of power lines. It is a difficult research problem how to solve the low accuracy of power line inspection based on deep neural network (DNN) due to the problems of multi‐view‐shape, small‐size object. In this paper, an automatic detection model based on Feature visual clustering network (FVCNet) for power line inspection is established. First, an unsupervised clustering method for power line inspection is proposed, and applied to construct a detection model which can recognize multi‐view‐shape objects and enhanced object features. Then, the bilinear interpolation method is used to Feature enhancement method, and the enhanced high‐level semantics and low‐level semantics are fused to solve the problems of small object size and single sample. In this paper, FVCNet is applied to the MS‐COCO 2017 data set and self‐made power line inspection data set, and the test accuracy is increased to 61.2% and 82.0%, respectively. Compared with other models, especially for the categories that are greatly affected by multi‐view‐shape, the test accuracy has been improved significantly. [ABSTRACT FROM AUTHOR]

UAV transmission tower inspection is the use of UAV technology for regular inspection and troubleshooting of towers on transmission lines, which helps to improve the safety and reliability of transmission lines and ensures the stability of the power supply. From the traditional manual tower boarding to the current way of manually selecting target camera shooting points from 3D point clouds to plan the inspection path of the UAV, operational efficiency has drastically improved. However, indoor planning work is still labor-consuming and expensive. In this paper, a deep learning-based point cloud transmission tower segmentation (PCTTS) model combined with the corresponding target point localization algorithm is proposed for automatic segmentation of transmission tower point cloud data and automatically localizing the key inspection component as the target point for UAV inspection. First, we utilize octree sampling with unit ball normalization to simplify the data and ensure translation invariance before putting the data into the model. In the feature extraction stage, we encode the point set information and combine Euclidean distance and cosine similarity features to ensure rotational invariance. On this basis, we adopt multi-scale feature extraction, construct a local coordinate system, and introduce the offset-attention mechanism to enhance model performance further. Then, after the feature propagation module, gradual up-sampling is used to obtain the features of each point to complete the point cloud segmentation. Finally, combining the segmentation results with the target point localization algorithm completes the automatic extraction of UAV inspection target points. The method has been applied to six kinds of transmission tower point cloud data of part segmentation results and three kinds of transmission tower point cloud data of instance segmentation results. The experimental results show that the model achieves mIOU of 94.1% on the self-built part segmentation dataset and 86.9% on the self-built instance segmentation dataset, and the segmentation accuracy outperforms that of the methods for point cloud segmentation, such as PointNet++, DGCNN, Point Transformer, and PointMLP. Meanwhile, the experimental results of UAV inspection target point localization also verify the method's effectiveness in this paper. [ABSTRACT FROM AUTHOR]

The transmission line is one of the most crucial electric power system components, demanding special attention since they are subject to failures that can cause disruptions in energy supply. In this scenario, the fault location emerges as a fundamental task, providing an approximate position where the failure occurred in the line. This paper presents a method for fault location using a novel dynamic regressor selection (DRS) framework, in which we introduce embedded normalization, incorporating the data scaling process inside the framework. The DRS aims to select the most accurate models from a pool of regressors to predict the fault distance. Moreover, since there is a lack of a public dataset, this paper presents and makes a new fault dataset available to the scientific community with several features extracted from current and voltage signals of representative failure events. In our experiments, we demonstrate the importance of this embedded normalization as well as the significance in the variation of critical hyperparameters of the DRS strategy, such as the distance metric used to define the region of competence and the criterion to select the best regressors from the pool of predictors. This work also presents the definition of the oracle concept in DRS, which represents the ideal predictor selection scheme. The results demonstrate the effectiveness of the proposed method with a mean error of 0.7086 km ± 0.0068 km, representing 0.1712% ± 0.0016% of the transmission line extension (414 km). [ABSTRACT FROM AUTHOR]