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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]

Electrocardiogram (ECG) signals are vital for diagnosing cardiac abnormalities, but they are corrupted by powerline interference noise, which can obscure critical features and compromise diagnostic accuracy. This paper investigates various filtration techniques aimed at effectively removing powerline interference noise from ECG signals. Different approaches, including average filters and moving average filters, are explored and compared to determine their efficacy in noise reduction while preserving important signal characteristics. Experimental evaluations are conducted using synthetic ECG signals contaminated with simulated powerline interference noise and real-world ECG recordings corrupted by actual powerline interference. The performance of each filtration technique is assessed based on metrics such as Root Mean Square Error (RMSE) and Percentage Root Mean Square Difference (PRD). The trade-offs between noise reduction effectiveness and preservation of ECG signal fidelity are analyzed to identify the most suitable approach for clinical applications. This paper provides valuable insights into the selection and implementation of filtration techniques for mitigating powerline interference noise in ECG signals. The findings contribute to the development of robust signal processing methods for improving the reliability and accuracy of ECG-based diagnostic systems. [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]

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]

In this paper, an organic, fully recyclable and eco-friendly 20-bit inkjet-printed chipless RFID tag is presented. The tag operates in the near field and is implemented by means of chains of resonant elements. The characterization and manufacturing process of the tag, printed with a few layers of a commercial organic ink on conventional paper substrate (DIN A4), are presented, and tag functionality is demonstrated by reading it by means of a custom-designed reader. The tags are read by proximity (through the near field), by displacing them over a resonator-loaded transmission line, and each resonant element (bit) of the tag is interrogated by a harmonic signal tuned to the resonance frequency. The coupling between the reader line and the resonant elements of the tag produce and amplitude modulated (AM) signal containing the identification (ID) code of the tag. [ABSTRACT FROM AUTHOR]

In high-voltage transmission lines, the tension tower needs to withstand the tension load of the overhead power line for a long time, which is prone to damage, and it is an important part of the inspection in the circuit inspection. In the modern circuit inspection process, operation and maintenance personnel mostly use unmanned aerial vehicles (UAVs) to photograph various parts of the tension tower, obtain inspection images, and manually classify and name the massive inspection images, which is low in accuracy and efficiency. Based on the above problems, this paper collects a large number of real-life UAV inspection images of various parts of a tension tower, and proposes the Stower-13 inspection image dataset, which is used to train the classification model to achieve automatic classification and naming of inspection images. Based on this dataset, this paper also proposes an improved MobileViT model, in which the Scale-Correlated Pyramid Convolution Block Attention Block (SCPCbam) module is introduced, which adds the Convolution Block Attention Module (CBAM) to the four branches of the original Scale-Correlated Pyramid Convolution (SCPC) module, so as to strengthen the ability of image multi-scale information extraction and improve the classification accuracy. This paper discusses a number of experiments on the model, and the experimental results show that the dataset proposed in this paper helps the model to understand the feature information. At the same time, the improved MobileViT model has a strong ability to extract image spatial feature information, the classification accuracy is higher than that of other models of the same type, so it is able to cope with a wide range of problems that arise in the course of practice, and it meets the practical needs of automatically naming transmission line inspection images. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a Mini‐LED display based on high mobility oxide thin film transistor (TFT) panel. The Mini‐LED display panel has a 160 × 160RGB pixel array with a pixel pitch of 0.6mm A new power line structure is adopted to minimize the IR drop of power line to achieve a uniform display. In this Mini‐LED display panel, a high mobility Ln‐IZO TFT is used, which helps to reduce the power of Mini‐LED panel. Both gate IC, source IC and fanout lines are placed at the top of the display, and a three‐sided borderless Mini‐LED display can be realized after laser cutting. Then 2×N display can be spliced by this 160×160RGB three‐sided borderless panel, such as 320×480 RGB(2×3 spliced). At last, a PWM driving method is introduced, which can achieve a better grayscale display. [ABSTRACT FROM AUTHOR]

With the rapid development of social economy, the demand for electric power engineering is gradually increasing. The power supply system is constantly developing in the direction of large space and automation, and various high and new technologies are also constantly improving. The power monitoring data access control system is used to monitor and control the power production and supply process and improve the power supply efficiency. The further development of the region also has a higher demand for power and energy supply. For the problem that the natural environment of transmission and distribution lines in various power grids is uncertain, which makes the line operation unsafe. This paper proposed a power monitoring data access control system based on BP (back propagation, abbreviated as BP) neural network. This paper described the related concepts of BP neural network and power monitoring system, and described the functions and construction methods of power monitoring data access control system. On this basis, relevant experiments were carried out to verify the performance of the proposed system. The experimental results showed that the fault detection accuracy of the traditional algorithm was about 93 %, while the fault detection accuracy of the algorithm in this paper was more than 98 %. The highest accuracy rate was 99.88 %, and the accuracy rate of fault detection was greatly improved. [ABSTRACT FROM AUTHOR]

Monitoring and controlling of transmission lines become easier in real time with synchrophasor measurements technology. Phasor Measurement Units (PMUs) provide the time-stamped synchrophasor data of the system buses and transmission lines with a high reporting rate. In this paper, a mathematical model is implemented that allows the simulation of the characteristics of the spread of transmission line switching with load variations. In the model, the transmission lines are divided into three parts defined as susceptible, infected and recovered transmission lines inspired from epidemic model. In this paper, Reliability Test System (RTS − 1979) is divided into three zones to simulate the line switching spread behaviour with load variation for reliability and vulnerability analysis of the synchrophasor smart grid network. The anomaly exists with synchrophasor measuring devices due to cyber intrusion in communication network or failure of devices makes the system observable with the characterization of vulnerable behaviour of 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]

In this article, a novel transmission line model consisting of open stubs and a one-end connected coupled line is introduced as an alternative to the standard quarter wavelength transmission line (QWTL). The new transmission line unit is used to realize a highly compact branch-line balun. Even and odd mode analysis is employed to extract the closed-form design equations. To substantiate the theoretical analysis, a branch-line balun with f 0 = 0.9 GHz is implemented on a biodegradable substrate material and tested. The developed prototype is having a relative circuit area of 11.2% of the conventional balun. The measured results exhibit that the return loss is better than 20 dB. A good match is found between the simulated and tested results. [ABSTRACT FROM AUTHOR]

To solve the problem of bolt defects in unmanned aerial vehicle inspection that are difficult to identify quickly and accurately, this paper proposes a defect detection method based on the improved YOLOv5 anchor mechanism. Firstly, the Normalized Wasserstein distance (NWD) evaluation metric and the Intersection over Union evaluation metric are combined, and the experiment determines the appropriate weight for this combination. This way, the sensitivity of using IoU alone to small objecet detection anchor box threshold changes was reduced. Furthermore, Convolutional Block Attention Module is included into the head network architecture of yolov5 in order to prioritize significant information and suppress irrelevant features. Omni-dimensional Dynamic Convolution (ODConv) is used to replace convolution in MobileNetv2. The combination module is used as the new backbone of the YOLOv5 model. It simultaneously enhances the model's capability to extract bolt defect object information, minimizes calculation requirements, and achieves lightweight detection across the entire model. Compared with the original algorithm, the model detection Accuracy Precision (AP) is increased by 30.1%, the mean Accuracy Precision is increased by 30.4%. Other evaluation metrics of the model, such as GFlOPs and Parameters, all decreased slightly. The above results show that the improved algorithm proposed in this paper greatly improves the detection accuracy of the model on the premise of ensuring that the model is as small as possible. [ABSTRACT FROM AUTHOR]

With the development of communication technology, the interference from passive intermodulation to the communication system has become increasingly severe. Locating the source of passive intermodulation and then repairing or replacing the device experiencing passive intermodulation is a reliable method. Therefore, this paper proposes a dual-frequency signal localization method based on the principle of phase ranging to accurately locate the passive intermodulation sources in RF cables. This method switches the test signal frequency to obtain the phase of passive intermodulation signals at different frequencies to localize the passive intermodulation source. This paper analyzes the principle of the passive intermodulation localization method based on dual-frequency signals, establishes a localization system for experiments, and finally, analyzes the experimental error to propose an optimization strategy. Through experimental verification, this method can stabilize the positioning error of a passive intermodulation source in a transmission line less than 0.06 m. Meanwhile, this method has high positioning accuracy and the advantages of slight computational complexity, fast positioning speed, and only a small number of requirements on hardware resources. It can work in communication scenarios like satellite and base stations, providing a new technical solution for localizing passive intermodulation interference sources in 5G and 6G communication systems. [ABSTRACT FROM AUTHOR]

The antenna cabin is a strong scattering source of various military platforms, and its stealth effect directly affects the stealth effect of military platforms such as missiles. Aiming at limitations of stealth FSS radome, design method of absorbing electromagnetic window structure is carried out in this paper. Based on the transmission line model, this paper introduces its working mechanism, proposes an analytical method and a complete design method. The structure proposed in this paper realizes pass-band at X-band (8-10GHz) and absorption in S-band (2-4GHz). After a series of simulations and optimizations, at least 10dB absorption in S-band and less than 1 dB insert loss in 8-10GHz are realized. [ABSTRACT FROM AUTHOR]

Pins are essential connecting components in power transmission lines. Their extensive use yet leads to frequent defects. Given the small size of a pin and many similar components, the detection of such defects is not ideal, which is a technological problem in the identification and diagnosis of power defects. In response to the large size, complex background, and on-site requirements, such as real-time detection, of power transmission lines, this paper proposes a method to detect pin defects based on TPH-MobileNetv3 (Transformer prediction Head Mobilenetv3). This paper modifies and adds a self-attention layer to MobilNetV3-Small to improve the feature extraction capability of small targets after downsampling. A feature fusion structure with layers of self-attention and a convolutional block attention module (CBAM) is added to the neck network, and a transformer prediction head are added to the head network so that different scale characteristics can be fused and focused from space and channels to strengthen the detection of small targets. Compared with the traditional MobileNetV3, the detection accuracy of the algorithm in this paper has been raised by 24%, as shown in the detection results of measured data. Moreover, compared with the mainstream algorithms with the same detection accuracy, this algorithm not only reduces the model size and significantly enhances detection efficiency but also satisfies the requirement of edge image processing of power inspection. [ABSTRACT FROM AUTHOR]

One of the most important challenges of smart grids is the congestion of transmission lines. A flexible smart grid with demand-side resources can be a suitable solution to manage transmission lines congestion. This paper proposes a multi-objective model with the aim of congestion management through generation rescheduling considering cost and emission purposes in a flexible smart grid. An inconvenience cost for consumers is defined to model the consumers' unsatisfactory as a consequence of participating in demand response programs (DRPs). Furthermore, a smart grid flexibility index (SGFI) has been presented to show the available flexibility of smart grid as a result of DRPs and gas turbine generators as fast response resources. The DRPs could increase the flexibility of the smart grids due to their impact on flattening the load curve, but this may cause some inconveniences for consumers. On the other hand, participation of consumers in DRPs and the power output gas turbine are associated with uncertainty. In this paper, the uncertainty of consumer's participation in the DRPs has been modeled by Fuzzy-Markov. The proposed multi-objective particle swarm optimization (MOPSO) has been implemented on the IEEE 30-bus system. The results show that the total operation cost including the generation cost, DRP cost, inconvenience cost of consumers, and pollution is reduced. In fact, the share of generation of expensive generators is reduced. [ABSTRACT FROM AUTHOR]

Aiming at the problem that it is impossible to accurately transport the aerial ground wire repair robot to the repair point and efficiently repair the ground wire broken strands and scattered strands, this paper designs an aerial ground wire repair robot based on Unmanned Aerial Vehicle (UAV). Firstly, the mechanical structure of the overhead ground wire repair robot is selected and designed, and the information transmission and the cooperative operation of each module are realized. A landing mark based on ArUco code is designed, which uses C++ for visual navigation, and then uses the double closed‐loop Proportional Integral Derivative (PID) control method to control the position and attitude of the UAV, so as to realize the tracking of the robot position by the UAV. At the same time, the mechanical structure and the control method of the UAV hanging device are designed to cooperate with the overhead ground wire repair robot to ensure the accurate completion of the repair operation. Finally, a UAV‐based aerial ground wire repair robot prototype was developed and successfully applied to the repair operation of the broken strand of the aerial ground wire of the 66 to 67 tower of the 500 kV Jiangzi line in Ya'an. It is verified that the UAV‐based aerial ground wire repair robot studied in this paper has a good engineering application value. [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]

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]

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 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]

This paper exhibits the design and implementation of a compact dual-band bandpass filter on paper substrate. The proposed filter which works on the principle of signal interference technique has a parallel combination of short-circuited coupled line and an H-shaped network of transmission lines with open stubs. Due to the superposition of signals of the two transmission paths, a second order dual-band bandpass response with four transmission zeroes is achieved. To validate the proposed design, theoretical analysis using the lossless transmission line model is carried out and acknowledged. The developed dual-band filter prototype with center frequencies 1.17 GHz and 4.06 GHz has 3-dB fractional bandwidths of 82.56% (0.69–1.656 GHz) and 20.59% (3.645–4.481 GHz), respectively. The simulated and experimental results are in good congruence with each other. The proposed dual-band bandpass filter can be used in various wireless applications, for example, Global System for Mobile Communications (880–915 MHz), Aircraft surveillance (960–1215 MHz), Indian Regional Navigation Satellite System (1.164–1.188 GHz), Amateur radio (1.24–1.30 GHz), Global Positioning System (1.559–1.61 GHz), Satellite phones (1.616–1.626 GHz), and Satellite communication (3.7–4.2 GHz). [ABSTRACT FROM AUTHOR]

This article presents an overview of the generalized negative-refractive-index transmission-line (G-NRI-TL) and summarizes the design equations that determine the frequencies of each of its four passbands. Specific multiband devices to which G-NRI-TLs have been applied are discussed: both a dual-band coupled-line coupler operating at 2.7 and 4.7 GHz and a printed single-ended all-pass cell with two pairs of right- and left-handed bands are explained. The details of how each may be fabricated in a fully-printed layout are provided and simulated and measured results are given. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE 22:459-468, 2012. [ABSTRACT FROM AUTHOR]

Much of oil-filled (OF) cable has been used for a long time as 66- to 500-kV extrahigh-voltage cable. Sometimes we can see extremely degraded tan δ oil (several tens of percent of tan δ, for example) in joint boxes, etc. The values of tan δ calculated by a simple combination model of paper/oil show that the oil-impregnated paper with such a high tan δ oil likewise has an extremely high tan δ, which must result in thermal breakdown. However, such an event has not taken place up to the present in actually operated transmission lines. This fact suggests that some mechanism for the suppression of tan δ has acted in the paper insulation impregnated with degraded tan δ oil. Therefore, we investigated in detail the tan δ characteristics of paper impregnated with extremely high tan δ oil. In addition, based on the investigation results, we developed a method for simulation of heat generation by dielectric loss in an OF cable joint (which has degraded tan δ oil). © 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 178(1): 1-10, 2012; Published online in Wiley Online Library (). DOI 10.1002/eej.21184 [ABSTRACT FROM AUTHOR]

The temperature dependence of chromatic dispersion is examined for various types of fiber. Its coefficient is found to depend strongly on the dispersion slope. Dispersion-flattened fiber has a significantly low coefficient of -0.0005 (ps/nm/km)/°C, compared with 0.0038(ps/nm/km)/°C for large-core nonzero dispersion-shifted fiber. Transmission lines with low dispersion slopes consisting of pure silica core fiber and dispersion-compensating fiber also exhibit low coefficients of less than -0.001 (ps/nm/km)/°C because of their compensating effects. The different techniques have been proposed to minimize temperature effect on optical fibers such as using multipoint temperature measurement techniques, coupling technique, using different materials which can withstand high degree temperature without fluctuations in performance. [ABSTRACT FROM AUTHOR]

This document is a correction notice for a research paper titled "A Drone Based Transmission Line Components Inspection System with Deep Learning Technique." The authors have identified errors in the figures and main body paragraphs of the paper and have provided corrected versions of the figures. They have also made changes to the abstract and introduction sections. The paper discusses the use of a drone to detect and analyze transmission line components for defects, utilizing deep learning techniques and convolutional neural networks. The authors acknowledge the errors in the original paper and apologize for any confusion caused. The research is funded by the Korean Ministry of the Interior and Safety. The authors of the paper are Zahid Ali Siddiqui and Unsang Park. [Extracted from the article]

Failure of vulnerable lines in the power system often results in tidal shifts, and triggering chain failures and their corresponding transmission sections are concentrated manifestations of the weak links in the power system. It is very important to identify the vulnerable lines and search the transmission section to prevent the chain faults as well as to analyze the stability of the power system. Aiming at the problems of inaccurate search of vulnerable lines, difficulties adapting to the complex and changing power system as well as wrong selection and omission of transmission section search in the existing references, this paper proposes an algorithm for searching vulnerable lines and their key transmission sections based on the graph theory and PMU (phasor measurement unit) data. First, the method combines with the graph theory and PMU data to construct the grid topology map. Second, the comprehensive indicators for screening vulnerable lines are proposed by fully considering the network topology and line capacity, which combines with power exchange efficiency and energy fluctuation probability. Third, the distance matrix in the Floyd algorithm is transformed into a unit group that can store more elements, which reduces the traversal times of the algorithm and improves computational efficiency. The fast localization of transmission cross sections associated with vulnerable lines is realized. Finally, the critical transmission cross sections are screened according to the line outage distribution factor and line safety margin. The IEEE 39-bus system is selected for simulation experiments, and the simulation results show that the key transmission section search method proposed in this paper can better adapt to the variable power grid and is faster and more accurate than the other common method. [ABSTRACT FROM AUTHOR]

When using high-voltage transmission lines for energy transmission in loess hilly regions, local extreme wind fields such as turbulence and high-speed cyclones occur from time to time, which can cause many kinds of mechanical and electrical failures, seriously affecting the reliable and stable energy transmission of the power grid. The existing research focuses on the wind field simulation of ideal micro-terrain and actual terrain with mostly single microterrain characteristics. Model boundary constraints and the influence of constrained boundaries are the main problems that need to be solved to accurately model and simulate complex flow fields. In this paper, a flow field simulation method based on circular boundary constraints is carried out. During the study, the influence of the model boundary and the selection conditions of themodeling range are systematically analyzed. It is more suitable to make sure that the air domain is 4 times higher than the height of the hill undulations, in addition to ensuring that there should be a minimum of 400 m between the study region and the boundary. Then, an actual terrain model of a power grid line in Shanxi is established, through the method proposed in this paper, the wind speed at the location of the transmission tower line under different wind directions is analyzed, and it is found that when the incidence direction is 45 degrees north by east the wind speed is the highest. The findings demonstrate that the circular boundary model has the advantage of more easily adjusting the wind incidence direction, in addition to theoretically reducing the errors caused by traditional models in boundary processing. It can accurately obtain the distribution characteristics of the flow field affected by the terrain, and quickly screen out the extreme working conditions that are most harmful to the transmission lines in the actual transmission line for energy transmission in complex loess hilly regions. [ABSTRACT FROM AUTHOR]

On the transmission line, the invasion of foreign objects such as kites, plastic bags, and balloons and the damage to electronic components are common transmission line faults. Detecting these faults is of great significance for the safe operation of power systems. Therefore, a YOLOv5 target detection method based on a deep convolution neural network is proposed. In this paper, Mobilenetv2 is used to replace Cross Stage Partial (CSP)-Darknet53 as the backbone. The structure uses depth-wise separable convolution to reduce the amount of calculation and parameters; improve the detection rate. At the same time, to compensate for the detection accuracy, the Squeeze-and-Excitation Networks (SENet) attention model is fused into the algorithm framework and a new detection scale suitable for small targets is added to improve the significance of the fault target area in the image. Collect pictures of foreign matters such as kites, plastic bags, balloons, and insulator defects of transmission lines, and sort theminto a data set. The experimental results on datasets show that themean Accuracy Precision (mAP) and recall rate of the algorithm can reach 92.1% and 92.4%, respectively. At the same time, by comparison, the detection accuracy of the proposed algorithm is higher than that of other methods. [ABSTRACT FROM AUTHOR]

Introduction: The secure operation of electric power transmission lines is essential for the economy and society. However, external factors such as plastic film and kites can cause damage to the lines, potentially leading to power outages. Traditional detection methods are inefficient, and the accuracy of automated systems is limited in complex background environments. Methods: This paper introduces a Weighted Spatial Attention (WSA) network model to address the low accuracy in identifying extraneous materials within electrical transmission infrastructure due to background texture occlusion. Initially, in the model preprocessing stage, color space conversion, image enhancement, and improved Large Selective Kernel Network (LSKNet) technology are utilized to enhance the model's proficiency in detecting foreign objects in intricate surroundings. Subsequently, in the feature extraction stage, the model adopts the dynamic sparse BiLevel Spatial Attention Module (BSAM) structure proposed in this paper to accurately capture and identify the characteristic information of foreign objects in power lines. In the feature pyramid stage, by replacing the feature pyramid network structure and allocating reasonable weights to the Bidirectional Feature Pyramid Network (BiFPN), the feature fusion results are optimized, ensuring that the semantic information of foreign objects in the power line output by the network is effectively identified and processed. Results: The experimental outcomes reveal that the test recognition accuracy of the proposed WSA model on the PL (power line) dataset has improved by three percentage points compared to that of the YOLOv8 model, reaching 97.6%. This enhancement demonstrates the WSA model's superior capability in detecting foreign objects on power lines, even in complex environmental backgrounds. Discussion: The integration of advanced image preprocessing techniques, the dynamic sparse BSAM structure, and the BiFPN has proven effective in improving detection accuracy and has the potential to transform the approach to monitoring and maintaining power transmission infrastructure. [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]

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]

Examines the characteristics of travelling waves along the non-linear transmission lines for monolithic integrated circuits. Analysis of slow-wave structures like MIS and Schottky-barrier strip lines; Examination of suitable equivalent circuits leading to characteristic wave equations; Parameters of the non-linearity, dispersion and dissipation and the boundary conditions of practical devices.

Transmission line (TL) Parameter Identification (PI) method plays an essential role in the transmission system. The existing PI methods usually have two limitations: (1) These methods only model for single TL, and can not consider the topology connection of multiple branches for simultaneous identification. (2) Transient bad data is ignored by methods, and the random selection of terminal section data may cause the distortion of PI and have serious consequences. Therefore, a multi-task PI model considering multiple TLs’ spatial constraints and massive electrical section data is proposed in this paper. The Graph Attention Network module is used to draw a single TL into a node and calculate its influence coefficient in the transmission network. Multi-Task strategy of Hard Parameter Sharing is used to identify the conductance of multiple branches simultaneously. Experiments show that the method has good accuracy and robustness. Due to the consideration of spatial constraints, the method can also obtain more accurate conductance values under different training and testing conditions. [ABSTRACT FROM AUTHOR]

This paper presents the new upper bounds of channel width required in multi- layer channel routing under a wiring rule in which horizontal wires must be wired in the odd-numbered layers and vertical wires in the even-numbered layers. In (M ≧ 4)-layer channel routing, it is proved the upper bound is equal to [(dc +k)/[M/2]], where dc is the channel density, and k is 9 when M = 5, 7 when M is even, and 13 when M is odd and greater than 5. These upper bounds are obtained by presenting the multiple-layer channel routing algorithms, which wire the channels in a column-by-column manner. [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 methodology for the evaluation of long-term exposure to the overhead line magnetic field is presented, in this paper. The developed methodology is based on the ambient temperature measurements and phase conductors' height measurements to find a linear regression model to determine phase conductors' height changes for different ambient temperatures. Based on the overhead transmission line geometry, and datasets about historical overhead line phase current intensity values and ambient temperatures long-term magnetic field exposure can be determined. For magnetic flux density determination, a method based on artificial neural networks is used. The methodology is applied to the case study of overhead line that connect substations Sarajevo 10 and Sarajevo 20. A period of one year is analyzed and magnetic flux density values are determined. The obtained results indicate that during the analyzed period for significant amounts of time magnetic flux density values surpass the recommended values for long-term exposure. [ABSTRACT FROM AUTHOR]

The utilization of wind power all-DC systems with DC collection and transmission is an effective solution for the extensive development of wind power in deep-sea areas. However, in the event of faults occurring in wind power all-DC systems, the fault propagation speed is extremely rapid, with a wide-ranging impact, and to date, there are no complete DC engineering references available. It is crucial to research the topology and fault isolation methods applicable to large-scale offshore wind power all-DC systems in deep-sea areas. This paper proposes a novel series-connected all-DC system topology and presents corresponding fault isolation methods for internal faults in wind turbine units and faults in high-voltage DC transmission lines. The system simulation model was constructed using PSCAD/EMTDC (v4.6.3), and simulations were conducted for internal faults in the wind turbine units and DC transmission line short-circuit faults. The simulation results demonstrate that the proposed system can isolate various DC faults while maintaining stable operation, thereby validating the effectiveness of the control strategies and fault isolation methods proposed in this paper. [ABSTRACT FROM AUTHOR]

Electric grids with buses that are mapped to geographic latitude and longitude are useful for a growing number of applications, such as data visualization, geomagnetically induced current calculations, and multi-energy coupled infrastructure simulations. This paper presents a methodology for validating the quality of geographic coordinates for a power system model, and to assign coordinates to buses with missing or low-quality coordinates. This method takes advantage of geographic indicators already intrinsic to a grid model, such as branch length as implied by impedance and susceptance parameters. The coordinate assignment process uses an approach inspired by graph drawing, that lays out the vertices (buses) and edges (transmission lines), formulated as a nonlinear programming problem with soft edge length constraints. The layout method is very computationally fast and scalable to large power system cases. The method is demonstrated in this paper using a 37-bus test case and a 6717-bus test case, both publicly available, along with a large actual grid model. The results show that, for cases with only a few errors in the coordinates, cases with no coordinates known beforehand, and others in between, this method is able to assign reasonable geographic coordinates to best match known data about the grid. [ABSTRACT FROM AUTHOR]

To address the issue of multiobjective control in multienergy systems with diverse operational objectives, a two-stage optimization framework based on expected point tolerance has been proposed in this paper. In the first stage, a single objective function is used for optimization control to obtain the expected point of the multiobjective optimization problem. Then, in the second stage, by defining the allowable deviation between each optimization objective and the expected point, the original multiobjective optimization problem is transformed into a single objective optimization problem solution with tolerance measurement. Finally, in the simulation scene of a multienergy system, it is demonstrated that compared with the optimal results under each single objective method, the proposed method increases power line loss, maximum voltage deviation, new energy consumption, and economy by 2.22, 2.30, 1.02, and 2.45 times, respectively. Compared with the suboptimal results, the proposed method reduces power line loss by 22.26, 1.74, 1.09, and 0.97 times, respectively. Combining the shape of the Pareto frontier, it is demonstrated that the proposed method can comprehensively consider the needs of multiple power optimization objectives for forming a more reasonable and effective system optimization scheduling and also provide a new approach for solving multiobjective optimization problems. [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]

Line loss refers to the electrical energy that is dissipated as heat during the transmission and distribution of electricity through power lines. However, unusual causes, such as grid topology mismatch and communication failure, can cause abnormal line loss. Efficient abnormal line loss detection contributes not only to minimizing energy wastage and reducing carbon emissions but also to maintaining the stability and reliability of the entire distribution network. In actual situations, the cause of abnormal line loss is not labeled due to the expensive labor cost. This paper proposes a hierarchical abnormal line loss identification and category classification model, considering the unlabeled and unbalanced sample problem. First, an abnormal line loss identification model-based random forest is established to detect whether the line loss is abnormal. Then, an abnormal line loss category classification model is developed with semi-supervised learning for line loss abnormal category classification, considering the unlabeled samples. The real dataset in China is utilized to validate the performance of the proposed model. Its reliability implies the potential to be applied to real-world scenarios to improve the management level and safety of the power grid. [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]

Combining edge devices with intelligent inspection for transmission lines can fulfill the demand for real‐time defect detection in the field. However, there has been limited research on algorithms suitable for edge devices with low computational power and memory, and the existing research primarily focuses on CPU optimization. To address these issues, this paper proposes a real‐time defect detection method for transmission line endpoints based on YOLO‐GSS (YOLOv8 with Mosaic‐9, G‐GhostNet, S‐FPN, and Spatial Intersection over Union (SIoU) modifications). First, the authors improve the input of the YOLOv8 network using Mosaic‐9 to increase the number of input features in the training phase and enhance algorithm robustness. Next, the authors introduce G‐GhostNet and S‐FPN to enhance the backbone and neck sections while improving inference speed and accuracy. Finally, the authors modify the Complete Intersection over Union loss function of YOLOv8 using SIoU to further improve the detection accuracy. Experimental results demonstrate that compared to the original YOLOv8, the proposed method achieves a 5x increase in inference speed on Nvidia Jetson NX edge devices and a 7.7% improvement in accuracy, meeting the real‐time defect detection requirements for transmission line field inspections. [ABSTRACT FROM AUTHOR]

Ensuring the safety of transmission lines necessitates effective insulator defect detection. Traditional methods often need more efficiency and accuracy, particularly for tiny defects. This paper proposes an innovative insulator defect recognition method leveraging YOLOv8s-SwinT. Combining Swin Transformer and Convolutional Neural Network (CNN) enhances the model's understanding of multi-scale global semantic information through cross-layer interactions. The improved BiFPN structure in the neck achieves bidirectional cross-scale connections and weighted feature fusion during feature extraction. Additionally, a new small-target detection layer enhances the capability to detect tiny defects. The experimental results showcase outstanding performance, with precision, recall, and mAP reaching 95.6%, 95.3%, and 97.7%, respectively. This boosts detection efficiency and ensures high accuracy, providing robust support for real-time detection of tiny insulator defects. [ABSTRACT FROM AUTHOR]

In order to evaluate the risk of transmission line tripping due to wildfires, it is necessary to predict the breakdown voltage of the insulation gap under the flame. Firstly, this paper studies the breakdown prediction of rod–plane gaps under the full-flame bridging of wooden cribs; it then obtains the breakdown voltage and the leakage current values of full-flame bridging considering different sizes of wooden cribs and different gap distances. Then, a multi-physical field simulation is carried out to obtain the flame gap characteristic parameters, such as spatial temperature. The feature quantity is normalized and reduced in dimension, and a prediction model for gap breakdown voltage under flame conditions based on a support vector machine (SVM) is established. Finally, the DC withstand voltage values and corresponding characteristic quantities under different flame gap conditions are used as sample sets to test the prediction model. The results show that the prediction error for small gap breakdown voltage is less than 2.6%. The samples were tested under different flame intensities for training and prediction, and the error was less than 3.3%. The small gap data for 30~60 cm is used to predict the breakdown voltage of the long gap for 100~140 cm, and the error is less than 3.2%. Compared with the fitting correction formula method proposed in existing research, the error is reduced by 11.5% and 4.4%, respectively, which verifies the effectiveness of the SVM prediction model. [ABSTRACT FROM AUTHOR]

The distribution system is easily affected by extreme weather, leading to an increase in the probability of critical equipment failures and economic losses. Actively scheduling various resources to provide emergency power support can effectively reduce power outage losses caused by extreme weather. This paper proposes a mobile energy storage system (MESS) scheduling strategy for improving the resilience of distribution networks under ice disasters. First, the influence of wind and ice loads on power transmission lines is analyzed, and a detailed fault statistical model of transmission lines under an ice disaster is established. Then, the MESS scheduling problem considering the coupling of transportation-distribution networks is transformed into a two-stage optimization problem. The first stage determines the optimal configuration scheme for MESS, and in the second stage, the optimal path selection for MESS can be obtained. Finally, the effectiveness and feasibility of the algorithm proposed in this paper are verified through an improved IEEE-33 node testing system. [ABSTRACT FROM AUTHOR]