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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]

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]

Abstract: A wide band flexible substrate based metamaterial is presented. The metamaterial is fabricated on photo paper using conductive nanoparticle ink targeting flexibility applications. The metamaterial structure shows a wide double negative region of 1.848 GHz (8.298–10.146 GHz). The transmission coefficient of the proposed metamaterial has been measured and verified with simulated one. The perceptible novelties of the proposed work are its simplicity, cost effectiveness, and flexibility with covering wide X‐band microwave spectra. [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]

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]

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]

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]

ABSTRACT Two key components, among several, in the design of a conformal antenna are the planar conductors and the flexible substrates. In this paper, a new approach of using graphene-based conductors instead of copper conductors in the design of a conformal antenna is presented. To determine the conductivity properties of the graphene-based conductor, the copper conductors in a well-known micro-strip transmission line (TL) and micro-strip antenna were replaced with the graphene-based conductors and were analytically evaluated, simulated in a full-wave simulation software and experimentally tested. Overall, it was shown that these graphene-based conductors have a conductivity that is high enough to design a useful micro-strip TL and micro-strip antenna. In particular, a conductivity of σ = 1.94 × [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]

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]

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 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]

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]

A prerequisite to ensure the stability of the power supply system is suitable functioning of transmission line equipment. However, the increasing deployment of transmission lines in modern power systems has introduced significant challenges to line inspection. While deep learning-based image detection techniques have shown promise in improving the efficiency and accuracy of insulator detection, they often require substantial computational resources and energy. This limitation hinders the consistent guarantee of accuracy and real-time performance on resource-constrained drones. To address this issue, this paper investigates the co-optimization problem of energy consumption and analytic accuracy in insulator image detection on unmanned aerial vehicles (UAVs). We propose a latency-aware end-edge cooperative insulator detection task offloading scheme with high energy efficiency and accuracy that aims to achieve optimal performance. Initially, we conducted an experimental analysis to examine the influence of input image resolution on the accuracy and latency of the CNN-based insulation detection model. Subsequently, we develop a model that takes into account the latency, analytic accuracy and energy consumption for image detection task offloading. Finally, we formalized a nonlinear integer optimization problem and designed a particle swarm optimization (PSO)-based task offloading scheme to optimize task accuracy and energy consumption while adhering to latency constraints. Extensive experiments validated the effectiveness of the proposed end-edge cooperative insulator detection method in optimizing accuracy and energy consumption. [ABSTRACT FROM AUTHOR]

In monitoring transmission line external damage prevention, due to the limited memory computing power of the equipment, the image needs to be transmitted to the data center at regular intervals, resulting in a high false negative rate. Therefore, this paper proposes a target detection method based on lightweight YOLOv5s. First, DSConv and improved E‐ELAN are used in Backbone to reduce the model's parameters. Then, GSConv and VoV‐GSCSP are introduced in Neck to reduce the complexity of the model. Finally, the Mish activation function achieves more effective feature transfer. According to the experimental findings, the proposed model's parameters are about 37% smaller than the original model's, and the calculation amount is about 53% smaller. The detection accuracy on the self‐built data set is the same, which proves that the proposed algorithm can reduce the model while maintaining high detection performance. It has specific practical significance for the terminal real‐time detection of external mechanical damage targets. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Accurate parameters are crucial in modern energy systems to ensure the reliable operation of all components. Given the substantial volume of data in monitored systems, high-performance methods are necessary. This paper proposes a new Bayesian multi-output regressor for estimating the parameters of a three-phase transmission line. The presented approach achieves acceptable accuracy in parameter estimation using only one end of the line. The Bayesian regressor is developed using information derived from the data themselves, eliminating the need to explicitly model the system. This capability allows the method to estimate parameters while accommodating different noise models, even in the presence of systematic errors and non-Gaussian random noise. The methodology was validated on various systems, including a two-bus system, IEEE 14-bus, IEEE 39-bus, and IEEE 118-bus, under diverse conditions such as varying sample sizes, loads, and noise levels. These tests demonstrate the robustness of the proposed approach. [ABSTRACT FROM AUTHOR]

The inspection of overhead power transmission lines is of the utmost importance to ensure the power network's uninterrupted, safe, and reliable operation. The increased demand for frequent inspections implementing efficient and cost-effective methods has emerged, since conventional manual inspections are highly inaccurate, time-consuming, and costly and have geographical and weather restrictions. Unmanned Aerial Vehicles are a promising solution for managing automatic inspections of power transmission networks. The project "ALTITUDE (Automatic Aerial Network Inspection using Drones and Machine Learning)" has been developed to automatically inspect the power transmission network of Lesvos Island in Greece. The project combines drones, 5G data transmission, and state-of-the-art machine learning algorithms to replicate the power transmission inspection process using high-resolution UAV data. This paper introduces the ALTITUDE platform, created within the frame of the ALTITUDE project. The platform is a web-based, responsive Geographic Information System (GIS) that allows registered users to upload bespoke drone imagery of medium-voltage structures fed into a deep learning algorithm for detecting defects, which can be either exported as report spreadsheets or viewed on a map. Multiple experiments have been carried out to train artificial intelligence (AI) algorithms to detect faults automatically. [ABSTRACT FROM AUTHOR]

The paper proposes an ultra-wideband frequency selective rasorber (FSR) with low infrared emissivity for the composite detection threat of both radars and infrared sensors. Firstly, the equivalent circuit (EC) method based on transmission line (TL) theory is utilized to analyze the absorption/transmission conditions. Then, based on the analysis above, sinusoidal microstrip lines with non-frequency-varying characteristics are adopted in the design, which significantly enhances the transmission bandwidth of FSR. The FSR demonstrates an absorption band ranging from 2.65 GHz to 8.80 GHz and a transmission band ranging from 9.15 GHz to 17.71 GHz. Furthermore, an infrared shielding layer (IRSL) exhibiting low emissivity in the infrared band and high transmittance in the microwave band is applied to the FSR. The simulation and experiment results verify that the IRSL-FSR demonstrates an ultra-wide transmission band ranging from 9.16 GHz to 17.94 GHz and an ultra-wide absorption band ranging from 2.66 GHz to 8.01 GHz. Additionally, it exhibits a low emissivity value (0.23) in 8–14 μm, providing a viable solution to the formidable challenge of radar-infrared bistealth for satellites and other communication-enabled flying platforms. [ABSTRACT FROM AUTHOR]

Currently, the intelligent defect detection of massive grid transmission line inspection pictures using AI image recognition technology is an efficient and popular method. Usually, there are two technical routes for the construction of defect detection algorithm models: one is to use a lightweight network, which improves the efficiency, but it can generally only target a few types of defects and may reduce the detection accuracy; the other is to use a complex network model, which improves the accuracy, and can identify multiple types of defects at the same time, but it has a large computational volume and low efficiency. To maintain the model's high detection accuracy as well as its lightweight structure, this paper proposes a lightweight and efficient multi type defect detection method for transmission lines based on DCP-YOLOv8. The method employs deformable convolution (C2f_DCNv3) to enhance the defect feature extraction capability, and designs a re-parameterized cross phase feature fusion structure (RCSP) to optimize and fuse high-level semantic features with low level spatial features, thus improving the capability of the model to recognize defects at different scales while significantly reducing the model parameters; additionally, it combines the dynamic detection head and deformable convolutional v3's detection head (DCNv3-Dyhead) to enhance the feature expression capability and the utilization of contextual information to further improve the detection accuracy. Experimental results show that on a dataset containing 20 real transmission line defects, the method increases the average accuracy (mAP@0.5) to 72.2%, an increase of 4.3%, compared with the lightest baseline YOLOv8n model; the number of model parameters is only 2.8 M, a reduction of 9.15%, and the number of processed frames per second (FPS) reaches 103, which meets the real time detection demand. In the scenario of multi type defect detection, it effectively balances detection accuracy and performance with quantitative generalizability. [ABSTRACT FROM AUTHOR]

This paper describes and validates an advanced synthesis design process of Frequency-Selective Surfaces (FSSs) with elliptic band-stop responses. A systematic procedure based on the Generalized Chebyshev Function and the extracted pole technique enables control of the position of the transmission zeros and the attenuation level to obtain an equiripple rejection response. A systematic process is followed to obtain the lumped LC values of the resonator circuits extracted as poles and the impedance inverters. Then, equivalent dipoles and transmission lines are obtained to carry out the electromagnetic design at normal incidence for a linearly polarized field. The impact of the higher-order modes of the periodic structure on the electrical response of the FSS, which can be relevant due to the stringent selected specifications, has been also analyzed. A fourth-order band-stop filter with a 3 GHz bandwidth centered at 30 GHz and its attenuation at 50 dB has been designed considering three different implementations: two filters using a vacuum as a transmission line with different connection lengths and a third one using a dielectric substrate to enable its manufacturing. In order to verify the design procedure using experimental results, the third filter with printed dipoles in the dielectric substrate has been manufactured and measured, thus validating the developed process. [ABSTRACT FROM AUTHOR]

This paper proposes a new methodology for sensitivity analysis evaluation, fast and with high precision of the electric potential distribution near the transmission lines (TL's). The TL is modeled by the finite element method and the sensitivity of the cable positions is obtained using the adjoint method. The sensitivity of the objective function during the optimization process by using methods based on gradient information is obtained by using the adjoint method. The exact sensitivity obtained by the adjoint method concerning the numeric model of the TL's results in new geometries of the bundles conductors with high surge impedance loading. These geometries are not possible to get using analytic models. The sensitivities of a large number of conductors by phase are obtained with high precision and very low computational cost using adjoint sensitivities, which are independent of the number of design variables. The central finite difference method is used to calculate the sensitivities and to validate the adjoint method. With this methodology, the FEM model of the TL can be used during the optimization process without compromising the required computational processing time. [ABSTRACT FROM AUTHOR]

This paper introduces a highly efficient and low-power inverse class-F voltage doubler (VD) designed for radio frequency (RF) energy harvesting systems. Specifically tailored for mid-band 5G technology, the VD is designed for operation within the 1240–1300 MHz satellite band. The innovative design employs an inverse class-F architecture, incorporating a λ / 8 short-ended transmission line (TL) connected to the diode anode and a ( λ / 12 ) open-ended transmission line linked to the input of the voltage doubler. This configuration aims to reshape voltage and current waveforms, effectively reducing losses and series resistance in the diode. Dual-coupled transmission lines (CTLs) are utilized to provide passive voltage boosting at low-input power levels. The suggested voltage doubler is implemented using RO4003C substrate material with a dielectric relative permittivity ( ε r ) of 3.38 and a thickness of 0.81 mm. Measured results demonstrate a minimum input return loss of − 29.3 dB at 1.25 GHz, operating seamlessly within a frequency band from 1.18 to 1.32 GHz. The measured conversion efficiency is 45.2% at an input power (Pin) of − 4dBm. Furthermore, the peak RF–DC efficiency reaches 50% at an input power of 0dBm. Simulated results predict a remarkable conversion efficiency of 60% and 68.7% at − 4dBm and 0 dBm, respectively. In addition to its exceptional performance, the suggested voltage doubler exhibits an experimental DC output voltage of 0.53 V at P in = - 10 dBm and a saturated DC voltage of 3.4 V at an input power of 10dBm under a load terminal resistance of 8 KΩ. Finally, the dimensions of the proposed voltage doubler are 25.3 × 10.5 mm 2 . [ABSTRACT FROM AUTHOR]

This paper was conceived to investigate some central issues related to the upheaval of current energy scenarios in Sicily. New power connection lines that are about to be built in the Mediterranean area, planned with a view to a constantly increasing renewable generation, encourage the carrying out of analyses on how the Sicilian electric power system will be able to make itself ready to support large power injections, especially due to new renewables plants that will be established in the region soon. This study, carried out in close collaboration with the Italian TSO Terna S.p.A and the University of Palermo, defines what the impacts of new renewable power plants will be on the Sicilian power transmission grid under intact and non-intact grid conditions. This study consists of steady-state simulations carried out using WinCreso® software version 7.62.1-3 in two energy scenarios estimated for the years 2024 and 2027, based on real connection requests by producers to Terna, and allows one to go beyond the studies conducted so far on a 2030 basis through the precise identification of network nodes or lines in difficulty. Finally, as well as presenting an interesting case study due to Sicily's strategic position in the Mediterranean Sea, this article proposes a methodological approach that can easily be adopted in other contexts and by other TSOs to analyze similar situations. [ABSTRACT FROM AUTHOR]

The effective exploitation of renewable energy sources is one of the most effective solutions to counter the energy, environmental and economic problems associated with the use of fossil fuels. Small-scale wind turbines (converting wind energy into electric energy with a power output lower than 50 kW) have received tremendous attention over the past few decades thanks to their reduced environmental impact, high efficiency, low maintenance cost, high reliability, wide wind operation range, self-starting capability at low wind speed, limited installation space, reduced dependence on grid-connected power and long transmission lines, low capital costs, as well as the possibility to be installed in some urban settings. However, there are significant challenges and drawbacks associated with this technology from many different perspectives, including the significant discrepancy between theoretical performance data provided by the manufacturers and real field operation, that need to be investigated in greater depth in order to enable a more widespread deployment of small-scale wind turbines. In this review, a complete and updated list of more than 200 commercially available small-scale horizontal and vertical wind turbine models is provided and analysed, detailing the corresponding characteristics in terms of the number and material of blades, start-up wind speed, cut-in wind speed, cut-out wind speed, survival wind speed, maximum power, noise level, rotor diameter, turbine length, tower height, and specific capital cost. In addition, several scientific papers focusing on the experimental assessment of field performance of commercially available small-scale horizontal and vertical wind turbines have been reviewed and the corresponding measured data have been compared with the rated performance derived from the manufacturers' datasheets in order to underline the discrepancies. This review represents an opportunity for the scientific community to have a clear and up-to-date picture of small-scale horizontal as well as vertical wind turbines on the market today, with a precise summary of their geometric, performance, and economic characteristics, which can enable a more accurate and informed choice of the wind turbine to be used depending on the application. It also describes the differences between theoretical and in-situ performance, emphasizing the need for further experimental research and highlighting the direction in which future studies should be directed for more efficient design and use of building-integrated small-scale wind turbines. [ABSTRACT FROM AUTHOR]

Ice-covered transmission lines seriously affect the normal operation of the power transmission system. Resonance deicing based on different ice thicknesses is an effective method to solve the issue of ice-covered transmission lines. In order to obtain accurate ice thickness of transmission lines, this paper designs an ice thickness of transmission line recognition model based on Global Micro Strip Awareness Net (GMSA-Net) and proposes a Mixed Strip Convolution Module (MSCM) and a global micro awareness module (GMAM). The MSCM adapts to the shape of ice-covered transmission lines by using strip convolutions with different receptive fields, improving the encoder's ability to extract ice-covered features; the GMAM perceives through both global and micro parts, mining the connections between semantic information. Finally, the ice thickness of the generated segmented image is calculated using the method of regional pixel statistics. Experiments are conducted on the dataset of ice-covered transmission lines. The mean Intersection over Union (mIoU) of image segmentation reaches 96.4%, the balanced F-Score (F1-Score) is 98.1%, and the identification error of ice thickness is within 3.8%. Experimental results prove that this method can accurately identify the ice thickness of transmission lines, providing a control basis for the application of resonant deicing engineering. [ABSTRACT FROM AUTHOR]

Electromagnetic fields unintentionally radiated from power-line communications used in factories interfere with wireless communications. It is important to distinguish the mechanism of this undesired and unintentional radiation from that of wired communication as it affects wireless communications. In particular, unintentional radiated emissions should be reduced in order to construct a stable wired/wireless communication network. This paper focuses on power-line communication as it is used in a factory. The power distribution network in the factory consists of multiple cables bundled together. The effects of cables other than the power cable that applies the communication signal to the radiated electromagnetic field are investigated. Some of the signal power reaching the reciever is converted into common-mode current by an imbalance mismatch. The common-mode current is one of the main causes of unwanted electromagnetic radiation. To predict this conversion, an imbalance difference model is created to account for multi-conductor transmission lines such as those in the power distribution network of the factory. The proposed model can calculate the amount of common-mode excitation associated with changes in the load condition of the power lines. To verify the proposed method, the authors measured the change in common-mode current due to the difference in pairs of power lines to which the signal is applied. The calculation using the proposed model could estimate the amount of reduction in common-mode current to within an error of 1 dB. [ABSTRACT FROM AUTHOR]

Insulators are vital components used in electrical transmission lines. It's crucial to keep their production cost low since they are widely used in electricity transmission. Instead of expensive alumina-based insulators, we can make cheaper ones using clay and bauxite found in nature. Adding more alumina makes them stronger, which is important for high voltage transmission. This paper aims to study the production process of bauxite-based insulators. We examined the insulators' structure using SEM images and EDAX spectrum analysis to see their formations, porosity ratio, and density. This research helps us learn more about these insulators and how they can be used effectively for high voltage transmission lines. [ABSTRACT FROM AUTHOR]

Summary: Maintaining proper current sharing among distributed generation (DG) units while regulating the output voltage is a challenging control issue in DC microgrids. The conventional droop control is widely used at the primary level of control to tackle this issue, but this method faces some limitations in voltage control and current sharing. To address this problem, this paper presents a new distributed secondary control method that determines the resistance of transmission lines by injecting an external pulse to the reference voltage of each converter and measuring output voltage and current changes. The proposed secondary control signal, denoted as Ui, enables simultaneous proportional current sharing and voltage restoration in the DC microgrid by correcting the droop coefficients based on the determined resistances. In order to ensure the stability of the proposed method, the small signal stability analysis of the closed‐loop system is conducted, considering various parameter changes. In contrast to similar methods, the proposed method introduces a new hybrid technique of voltage setpoint shifting and droop parameter adjustment that achieves precise proportional current sharing and voltage restoration, even when faced with varying resistive loads and constant power loads (CPLs). Additionally, the proposed method demonstrates outstanding characteristics, such as high convergence speed, the ability to determine transmission line resistances instead of assuming them to be known, and robustness in plug‐and‐play scenarios and communication system failures. The simulation results in MATLAB and experimental tests confirm the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to present the simulation, fabrication and testing of a novel ultra-wide band (UWB) band-pass filters (BPFs) with better transmission and rejection characteristics on a low-loss Taconic substrate and analyze using the coupled theory of resonators for UWB range covering L, S, C and X bands for radars, global positioning system (GPS) and satellite communication applications. Design/methodology/approach: The filter is designed with a bent coupled transmission line on the top copper layer. Defected ground structures (DGSs) like complementary split ring resonators (CSRRs), V-shaped resonators, rectangular slots and quad circle slots (positioned inwards and outwards) are etched in the ground layer of the filter. The circular orientation of V-shaped resonators adds compactness when linearly placed. By arranging the quad circle slots outwards and inwards at the corner and core of the ground plane, respectively, two filters (Filters I and II) are designed, fabricated and measured. These two filters feature a quasi-elliptic response with transmission zeros (TZs) on either side of the bandpass response, making it highly selective and reflection poles (RPs), resulting in a low-loss filter response. The transmission line model and coupled line theory are implemented to analyze the proposed filters. Findings: Two filters by placing the quad circle slots outwards (Filter I) and inwards (Filter II) were designed, fabricated and tested. The fabricated model (Filter I) provides transmission with a maximum insertion loss of 2.65 dB from 1.5 GHz to 9.2 GHz. Four TZs and five RPs are observed in the frequency response. The lower and upper stopband band width (BW) of the measured Filter I are 1.2 GHz and 5.5 GHz of upper stopband BW with rejection level greater than 10 dB, respectively. Filter II (inward quad circle slots) operates from 1.4 GHz to 9.05 GHz with 1.65 dB maximum insertion loss inside the passband with four TZs and four RPs, which, in turn, enhances the filter characteristics in terms of selectivity, flatness and stopband. Moreover, 1 GHz BW of lower and upper stopbands are observed. Thus, the fabricated filters (Filters I and II) are therefore evaluated, and the outcomes show good agreement with the electromagnetic simulation response. Research limitations/implications: The limitation of this work is the back radiation caused by DGS, which can be eradicated by placing the filter in the cavity and retaining its performance. Practical implications: The proposed UWB BPFs with novel resonators find their role in the UWB range covering L, S, C and X bands for radars, GPS and satellite communication applications. Originality/value: To the best of the authors' knowledge, for the first time, the authors develop a compact UWB BPFs (Filters I and II) with BW greater than 7.5 GHz by combining reformed coupled lines and DGS resonators (CSRRs, V-shaped resonators [modified hairpin resonators], rectangular slots and quad circle slots [inwards and outwards]) for radars, GPS and satellite communication applications. [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]

Unpredictable variations in load demand and unanticipated component failures are progressively impacting the operation of modern power systems, making system evaluation more stochastic in nature. Although deterministic approaches were formerly the norm for determining system status, probabilistic approaches have greatly improved the capacity to capture the stochastic behavior characteristic of power system operations. The presented work in the paper recommends the use of probabilistic modelling approaches with deterministic approaches, highlighting their crucial function in augmenting the reliability and security of contemporary power systems to unanticipated failures. In this paper, N − 1 security criteria based reliability of the composite power system (CPS) is proposed using an integrated deterministic and probabilistic framework (D-P) considering outage of the transmission line. For the deterministic approach (DA), line overloading on available lines is determined using the static security index (SSI). For the probabilistic approach (PA), reliability indices such as expected loss of power (ELOP), expected frequency of contingency (EFOC), expected loss of load (ELOL), probability of load curtailment (PLC), and expected duration of load curtailments (EDLC) are calculated. Further, for each contingency, a performance index is determined using both approaches to assess the severity of the contingency that occurred on the power system. Based on the N − 1 security criteria based reliability analysis using an integrated D-P framework, a credible critical set of transmission lines is obtained, which can serve as important information to system operators. The proposed techniques have been tested on IEEE 24 bus reliability test system (RTS). [ABSTRACT FROM AUTHOR]

The theme of the paper is to emphasize the detection and classification of faults and their site location in the transmission line using machine learning techniques which help to indemnify the foul-up of the humans in identifying the site and type of occurrence of fault. Moreover, the transient stability is a supreme one in power systems and so the disturbances like faults are required to be separated to preserve the transient stability. In general, the protection of the transmission line includes the installation of relays at both ends of the line that constantly monitor voltages and currents and operate unless a fault occurs on a line. Therefore, this paper intends to introduce a novel transmission line protection model by exploiting the hybrid optimization concept to train the Convolutional Neural Network (CNN). Here, the fault detection, classification and site location are diagnosed by using CNN which is trained and tested by making use of diverse synthetic field data derived from the simulation models of distinct types of transmission lines. Hence, the location and the type of faults will be predicted by the CNN depending on the fault signal characteristics which are optimally trained by a new hybrid algorithm named Chicken Swarm Insisted Spotted Hyena (CSI-SH) Algorithm that hybrids both the concept of Spotted Hyena Optimization (SHO) and Chicken Swarm Optimization (CSO). Finally, the proposed method based on CNN for fault classification and site location of transmission lines is implemented in MATLAB/Simulink and the performances are compared with various measures like classification accuracy, fault detection rate and so on. [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]

In this paper, at the L-band, we design and verify an ultra-thin easy-realized absorber (LUTA) based on metasurface and magnetic material. The absorptivity achieves over 90% at 1–2.51 GHz (86.04% fractional bandwidth), covering the whole L-band (1–2 GHz) and the partial S-band (2–4 GHz). The total thickness of the LUTA is as low as 3.7 mm, corresponding to 0.012λ0 at the lowest operating frequency, which greatly breaks through the Rozanov limit. The excellent performance is achieved through analyzing the transmission line model of a basic absorber and then designing the metasurface layer with required impedance characteristics to make the impedance of the LUTA match with the air at the designed frequency band. The simulated absorption, power loss density, and the surface current distributions of the LUTA verify the design method, while the measured results demonstrate that the LUTA has the superiority of easy-fabrication, polarization independent, wide angle incidence, and high absorption at the whole L-band. The LUTA has great application potentials in the fields of L-band electromagnetic stealth and radar cross section reduction. [ABSTRACT FROM AUTHOR]

Electric pylons are crucial components of power infrastructure, requiring accurate detection and identification for effective monitoring of transmission lines. This paper proposes an innovative model, the EP-YOLOv8 network, which incorporates new modules: the DSLSK-SPPF and EMS-Head. The DSLSK-SPPF module is designed to capture the surrounding features of electric pylons more effectively, enhancing the model's adaptability to the complex shapes of these structures. The EMS-Head module enhances the model's ability to capture fine details of electric pylons while maintaining a lightweight design. The EP-YOLOv8 network optimizes traditional YOLOv8n parameters, demonstrating a significant improvement in electric pylon detection accuracy with an average mAP@0.5 value of 95.5%. The effective detection of electric pylons by the EP-YOLOv8 demonstrates its ability to overcome the inefficiencies inherent in existing optical satellite image-based models, particularly those related to the unique characteristics of electric pylons. This improvement will significantly aid in monitoring the operational status and layout of power infrastructure, providing crucial insights for infrastructure management and maintenance. [ABSTRACT FROM AUTHOR]

The optimal functioning of the power system is crucially dependent upon the sound protection of its major stakeholder, i.e., the transmission line, as it is prone to fault. To maintain the integrity of the power system and protect costly power system equipment, protective relaying is necessary to provide a steady and affordable supply of electricity. Relays recognize, classify, and identify transmission line faults using input signals of voltage and current. Many artificial intelligent methods based on Expert Systems, Artificial Neural Networks, Fuzzy Logic, Support Vector Machines, Wavelet-based systems, and deep learning techniques are being investigated to improve modern digital relays’ consistency, speed, and accuracy. This paper is a comprehensive and all-inclusive survey that reviews and incorporates Phasor Measurement Unit (PMU) and Global Positioning System (GPS) approaches together with all of these intelligent transmission line safety strategies and concepts. Initial investigators will benefit from this study by being able to examine, evaluate, and analyze a variety of approaches with references for all relevant contributions. [ABSTRACT FROM AUTHOR]

Achieving a balance between accuracy and efficiency in target detection applications is an important research topic. To detect abnormal targets on power transmission lines at the power edge, this paper proposes an effective method for reducing the data bit width of the network for floating-point quantization. By performing exponent prealignment and mantissa shifting operations, this method avoids the frequent alignment operations of standard floating-point data, thereby further reducing the exponent and mantissa bit width input into the training process. This enables training low-data-bit width models with low hardware-resource consumption while maintaining accuracy. Experimental tests were conducted on a dataset of real-world images of abnormal targets on transmission lines. The results indicate that while maintaining accuracy at a basic level, the proposed method can significantly reduce the data bit width compared with single-precision data. This suggests that the proposed method has a marked ability to enhance the real-time detection of abnormal targets in transmission circuits. Furthermore, a qualitative analysis indicated that the proposed quantization method is particularly suitable for hardware architectures that integrate storage and computation and exhibit good transferability. [ABSTRACT FROM AUTHOR]

Lightning is a major cause of tripping faults in overhead transmission lines. Multi-chamber lightning arresters are widely used to protect high-voltage lines from lightning because of their reliable arc-quenching performance. This paper analyzes the development and quenching process of an arc after a lightning breakdown arrester and studies the quenching mechanism of a multi-chamber arc structure based on its structural characteristics. We built an impulse-current test platform and carried out an impulse-current test for the multi-chamber arrester. The arc motion was captured by a high-speed camera, and the height, speed, and temperature of the arc ejection were obtained by signal processing. The multi-chamber arrester structure is optimized by using the maximum arc ejection height and the maximum ejection speed as metrics to find the optimal combination of the quenching-hole diameter and depth and the gap distance of the multi-chamber structure. [ABSTRACT FROM AUTHOR]