High Voltage Power Transmission Lines Research Articles

Advanced Anti-icing and Deicing Strategies for Overhead Power Transmission Lines Based on Giant Magnetocaloric Effect of La0.7Ca0.254Sr0.046MnO3.

Perovskite manganates (AMnO3) exhibit diverse structural, thermal, electrical, and magnetic properties. Their strong magnetocaloric effect (MCE) near the Curie temperature (TC) makes them ideal for magnetic-thermal anti-icing and deicing in power transmission lines. Below TC, ferromagnetic AMnO3 produces heat through multiple mechanisms, with the changing magnetic field induced by the strong AC current, causing heat through magnetic hysteresis and eddy currents, alongside the direct MCE. Above TC, no heating is generated, as MCE is unfavorable, thus preventing additional energy loss at elevated temperatures. In this work, La0.7Ca0.254Sr0.046MnO3 with TC close to 0 °C were synthesized by solid-state reaction. It is found that particle size >10 μm is beneficial for a large MCE, based on the results of particle size dependence of MCE. The resulting maximum magnetic entropy change at 277 K is 7.69 J·kg-1·K-1, and an adiabatic temperature change of 3.87 K at 277 K is achieved under 5 T. The prototype cable is fabricated using a well-established wire drawing process. A climate-simulation chamber is employed for the anti-icing and deicing experiments. The prototype cables demonstrated a strong capability for deicing and anti-icing. This simple and cost-effective prototype cable shows significant potential for mitigating the icing problem of overhead high-voltage power transmission lines.

Numerical Analysis and Health Implications of Electric Fields from High Voltage Overhead Transmission Lines for Safety and Design Optimization

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.

İSTİSMARDAKI KABELLӘRDӘ ZӘDӘLӘRİN ARADAN QALDIRILMASININ MÜASİR ÜSULLARI

XLPE insulated power cables serve as essential components in medium and high voltage power transmission lines, yet maximizing their resource duration poses a significant challenge for consumers. Issues such as water treeings, electric treeings, and partial discharges within the insulation system accelerate cable aging over time. In response, a novel approach has been proposed in this study to mitigate these detrimental factors. The method involves injecting a specially formulated liquid into the cable insulation to address inhomogeneities, effectively rejuvenating the cable and extending its service life by 20-30 years, as indicated by the technology's name. Furthermore, to provide context on the practical implications, a succinct analysis of the Azerbaijani cable network is presented in this article. Also, in order to explain the real situation of power cables, a brief analysis of the Azerbaijani cable network was conducted in the article.

Wind-driven suspended triboelectric-electromagnetic hybrid generator with vibration elimination for environmental monitoring in the high-voltage power transmission line

The sustainable development of the high-voltage power transmission system puts forward more significant requirements IoT sensor network. Currently, a large number of the IoT sensors are installed on the high-voltage transmission lines, and environmental wind energy harvesting around the outdoor power transmission lines enables a promising and feasible solution to supply distributed sensors. However, the traditional floor-mounted wind energy nanogenerator with high requirements for placement and fixation is no longer applicable to the suspension scenario of the high-voltage power transmission lines. In this work, a wind-driven suspended triboelectric-electromagnetic hybrid generator (WS-TEHG) is designed as a suspended wind cup with a three-layered integrated structure, which can be integrated with the damping structure that hanged and installed on the power transmission line, demonstrating the simultaneously achieving high efficiency wind energy harvesting and the operation stability of the device. After the structural and material optimization, WS-TEHG can achieve efficient energy collection under wide-range of the wind speed from 2.6 to 17.3 m s−1, whose TENG and EMG produced instantaneous peak power from 0.2 to 7.9 mW and 0.6–85.1 mW, respectively. Moreover, a standardized power management based on LTC 3588-based double-channel circuit was established to co-manage the outputs of the two generating modules in the hybrid generator and enhance the continuous stability of the standardized voltage output, demonstrating a shorter undervoltage charge accumulation, a faster start-up process, a lower power consumption compared with the traditional power management. Finally, a self-powered environmental monitoring system by a WS-TEHG equipped with a standardized power management circuit was developed to provide the weather and climate information around the power transmission lines, thereby demonstrating a potential and feasible for large-scale self-powered application in the field of the high-voltage power transmission lines.

Detection of partial discharge patterns in hybrid high voltage power transmission lines based on parallel recognition method

Due to their specially designed structures, the partial discharge detection of hybrid high-voltage power transmission lines (HHVPTL) composed of overhead lines and power cables has made it difficult to monitor the conditions of power transmission lines. A parallel recognition method for partial discharge patterns of HHVPTLs is proposed by implementing wavelet analysis and improved backpropagation neural network (BPNN) to address the shortcomings of low efficiency, poor accuracy, and inability to parallel analysis of current partial discharge (PD) detection algorithms for HHVPTLs. Firstly, considering the non-smoothness of the partial discharge of the HHVPTLs, the wavelet packet decomposition algorithm is implemented to decompose the PD of the HHVPTL and resolve the relevant signal indicators to form the attribute vectors. Then, BPNN is implemented as a classification model. A beetle optimization (DBO) algorithm based on orthogonal contrastive learning improvement is introduced to optimize the BPNN parameters since BPNN has a slow convergence problem and fails easily into a local optimum. The proposed IDBO-BPNN is employed as the model that recognizes and analyzes the parallel partial discharge patterns of HHVPTLs. Finally, the suggested model is implemented to investigate the local discharge data of an HHVPTL in the Kaggle Featured Prediction Competition and is compared with other algorithms. The experimental results indicate that the proposed model can more accurately identify whether PDs occur in an HHVPTL and detect phases where PDs occur, with higher overall accuracy and efficiency. An excellent practical performance is achieved. The proposed model can achieve the recognition accuracy of 95.5%, which is 5.3333% higher than that of the DBO-BPNN and far more than other recognition algorithms.

Design and Analysis of 400KV Extra High Voltage Power Transmission Lines in Lebanon

This paper aims to design and analyze an overhead AC extra high voltage transmission line in Lebanon, using ACSR conductors, to meet the growing demand for the future. The optimal design will consider various factors to achieve the best system efficiency and performance, while complying with regulations and safety standards, including EHV voltage level, conductor size, number of conductors per phase, cable sag, and other factors, as well as estimating and describing environmental impacts such as conductor surface potential gradient, corona loss, radio interference, and audible and random noise.

Heterogeneous public preferences for undergrounding high-voltage power transmission lines: The case of Seoul metropolitan area in South Korea

Local residents generally do not prefer the installation and operation of power infrastructure because of the perceived economic, health, environmental, and landscape risks associated with it. This study investigates public preferences for undergrounding high-voltage power transmission lines, which is a popular option to cope with conflicts related to transmission infrastructure. Undergrounding refers to burying overhead transmission lines underground. However, undergrounding projects are costly, making it difficult for local governments to conduct by themselves. Therefore, national-level support is required to conduct undergrounding of transmission lines. When national funds are used, considering heterogeneous public preferences is important, as the public may have a polarized preference towards the policy. This study utilized the choice experiment and consumer choice model to investigate public preferences for priorities and details of the high-voltage transmission line undergrounding policy. The latent class logit model, which incorporates preference heterogeneity by grouping the samples into a few classes, was utilized to investigate heterogeneous public preferences. Consequently, four distinct classes with different preference structures were identified. The results show that strong heterogeneity was observed, especially in the priority area for undergrounding. Moreover, heterogeneous public preferences were associated with the key demographics of respondents and perceptions towards transmission infrastructure.

Enhancing grid reliability through advanced insulator defect identification.

The article presents an innovative approach for detecting defects in insulators used in high-voltage power transmission lines, employing an enhanced Detection Transformer (DETR) model, termed IF-DETR. The study addresses the significant challenges in traditional insulator defect detection methods, such as the loss of small defect features and confusion with background features. Firstly, we propose a multi-scale backbone network to better extract features of small objects. Secondly, as the contextual information surrounding objects plays a critical role in detecting small objects, we introduce a fusion module composed of ECA-Net and SAU to replace the original attention module for improved contextual information extraction. Lastly, we introduce the insulator defect (IDIoU) loss to optimize the instability in the matching process caused by small defects. Extensive experiments demonstrate the model's effectiveness, particularly in detecting small defects, marking a notable advancement in insulator defect detection technology. The IF-DETR achieved a 2.3% increase in AP compared to existing advanced methods. This method not only enhances the accuracy of defect detection, crucial for maintaining the reliability and safety of power transmission systems but also has broader implications for the maintenance and inspection of high-voltage power infrastructure.

Automated monitoring of high-voltage transmission lines based on machine vision

Abstract This paper takes the automated monitoring of high-voltage transmission lines as the entry point and constructs an automated monitoring model of high-voltage transmission lines based on machine vision. Through the transmission equipment recognition algorithm to identify the type and location of the equipment in the inspection image, using image processing methods for the collected high-voltage transmission line image color image grayscaling and grayscale image stretching, and then grayscale image smoothing and segmentation, so as to achieve the identification of the location of high-voltage transmission line fault location. Simulation test for image processing and transmission equipment identification methods, and then carry out automated monitoring experiments with high-voltage transmission line conductor stranding as an example to verify the feasibility and reliability of the model in this paper. The results show that for the automatic detection of individual conductor strand breakage, the method of this paper detects the number of strand breakage is only 1-2 less or more than the actual number of strand breakage; there is a certain difference, but basically in line with the actual situation, and the method of this paper, on average, detects the efficiency of the method is faster than the traditional method by 5.69~7.18 s/m. The research to enhance the quality of automated monitoring of high-voltage power transmission lines has a certain application value.

Experimental study on impact of high voltage power transmission lines on silicon photovoltaics using artificial neural network

The recent trend of renewable energy has positioned solar cells as an excellent choice for energy production in today’s world. However, the performance of silicon photovoltaic (PV) panels can be influenced by various environmental factors such as humidity, light, rusting, temperature fluctuations and rain, etc. This study aims to investigate the potential impact of high voltage power transmission lines (HVTL) on the performance of solar cells at different distances from two high voltage levels (220 and 500 KV). In fact, HVTLs generate electromagnetic (EM) waves which may affect the power production and photocurrent density of solar cells. To analyze this impact, a real-time experimental setup of PV panel is developed (using both monocrystalline and polycrystalline solar cells), located in the vicinity of 220 and 500 KV HVTLs. In order to conduct this study systematically, the impact of HVTL on solar panel is being measured by varying the distance between the HVTL and the solar panels. However, it is important to understand that the obtained experimental values alone are insufficient for comprehensive verification under various conditions. To address this limitation, an Artificial Neural Network (ANN) is employed to generate HVTL impact curves for PV panels (particularly of voltage and current values) which are impractical to obtain experimentally. The inclusion of ANN approach enhances the understanding of the HVTL impact on solar cell performance across a wide range of conditions. Overall, this work presents the impact study of HVTL on two different types of solar cells at different distances from HVTL for two HV levels (i.e., 220 and 500 KV) and the comparison study of HVTL impact on both monocrystalline and polycrystalline solar cells.

Method for Determining the Resonant Frequencies of Extra High Voltage Power Transmission Line

Method for Determining the Resonant Frequencies of Extra High Voltage Power Transmission Line

Uncovering the Neurobiological Consequences of High-Voltage Electrical Field Exposure on the Visual Working Memory of Macaques and Also Using Spiking Neural Network Model

High-voltage (HV) power transmission lines running near cities and villages can cause severe damage (Mental and physical). Due to the magnetic and electric fields they produce. This study aimed to investigate the effects of high-voltage (HV) electric fields on the spiking neural network model of the brain and biological and behavioral models of visual working memory. To achieve this goal, macaques were studied for their cognitive functions, expression of the NMDA receptor gene, MRI-assisted analysis of brain anatomy, and variations in blood sodium and potassium concentrations. The experimental group of macaques was exposed to a 3kV/m high-voltage field for four hours a day for one month. Computational models were then evaluated using experimental parameters. According to the results, it was observed that being exposed to high-voltage electric fields led to a reduction in the expression of the NMDA receptor gene, as well as a decrease in the levels of Sodium and potassium ions in the blood plasma. Additionally, analysis assisted by MRI showed a decrease in the volume of the hippocampus and amygdala after exposure to the electric field. In conclusion, the results of cognitive, genetic, blood, and MRI tests, along with the spiking neural network model, elucidate the mechanism of the visual working memory deterioration in macaques due to high-voltage electric field exposure.

The Finite Elements Method application to assesment the impact of turbulence generated by wind turbines on their location in close proximity of overhead high voltage power transmission lines

The Finite Elements Method application to assesment the impact of turbulence generated by wind turbines on their location in close proximity of overhead high voltage power transmission lines

Heterogeneous public attitudes toward high-voltage power transmission lines and willingness to pay for undergrounding projects

On the path to carbon neutrality by 2050, the expansion and improvement of high-voltage power transmission lines (HV-PTL) is a critical and unavoidable energy issue that may become a potential source of public conflict. However, the discussion on this issue in South Korea has been insufficient. In this study, we analyzed public attitudes toward HV-PTLs and classified people into subgroups based on their common characteristics using latent class models. In addition, we used the contingent valuation method to estimate the public's willingness to pay (WTP) for the conversion of overhead lines to underground cables, focusing on the differences among the identified subgroups. According to the empirical analysis, people in South Korea can be divided into four classes based on their perceived need for resident participation in the decision-making process, perceived health risk, and perceived property loss risk. According to the WTP analysis using the spike model, the estimated mean and median WTP values were KRW 4184 (USD 3.8) and KRW 2632 (USD 2.4) per household per month, respectively. In addition, we found a significant difference in WTP by class. Those who perceived HV-PTL as risky were less willing to pay for undergrounding projects compared with those whose perceived risk was relatively low. This study contributes to the understanding of academics and policymakers on the relationship between public attitudes toward HV-PTL and overhead to underground conversion.

UAV High-Voltage Power Transmission Line Autonomous Correction Inspection System Based on Object Detection

With the development of technology, unmanned aerial vehicles (UAVs) are playing an increasingly important role in the inspection of high-voltage power transmission line. The traditional inspection method relies on the operator to manually control the drone for inspection. Although many companies are using real-time dynamic carrier phase differencing technology to achieve high-precision positioning of UAVs, when UAVs fly autonomously at high altitudes to photograph specific objects, the objects tend to deviate from the center of the picture. To address this error, in this paper, an autonomous UAV inspection system based on object detection is designed. (1) To detect inspection objects, the corresponding dataset is established on the basis of the UAV autonomous inspection task. (2) To obtain the position information of the target object, a lightweight object detector based on the YOLOX network model is designed. First, the backbone is replaced with MobileNetv3. Next, in the neck structure, the Ghost module is introduced and depthwise convolution is applied instead of normal convolution. Then, to embed the location information into the channel attention, coordinate attention is introduced after the output feature layer of the backbone, enabling the lightweight network to operate on a larger area of focus. Finally, to improve the accuracy of the bounding box regression, the α-DIOU loss function is introduced. (3) To obtain the best image acquisition position, the results of object detection combined with the real-time status of the UAV are used. (4) To enable the UAV to complete the final corrections, position control and altitude control are used. Compared to the original YOLOX tiny, the new model improves the mAP_0.5:0.95 metric by about 2 percentage points, with a significant reduction in the number of parameters and computation, while running at 56 FPS on Nvidia NX. This system can effectively solve the problem of the target deviating from the center of the picture when the UAV takes pictures during a high-altitude autonomous inspection, verified by many actual flight experiments.

Effects of parameter adjustment on the electromagnetic field of an overhead power transmission line model

Studies have shown that high-voltage power transmission lines emit electromagnetic radiation, which has adverse effects on human health. This paper presents the effects of parameter adjustment on the electric and magnetic fields of an overhead power transmission line model at human height. A finite element software, COMSOL multiphysics, was used to simulate the electric and magnetic fields. The electric and magnetic fields generated by the 1200-kV and 220-kV overhead power transmission line models were first computed and the models were validated by comparing the simulation results with those of previous studies. Numbers of parameter were adjusted in order to investigate their effects on the electric and magnetic field distributions. Based on the results, the electric field intensity increases with an increase in the voltage of the conductors. The magnetic field density increases with an increase in the current carried by the conductors. A voltage of 700 kV results in an electricity field intensity that exceeds the residential safety limit (50 kV/m) set by the International Commission on Non-Ionizing Radiation Protection. Hence, a proper right-of-way is needed to ensure that residential areas are at a safe distance away from transmission towers.

Предел передаваемой мощности управляемой линии электропередачи высокого напряжения для режимов на границе статической устойчивости

The use of series compensation devices is one of the methods to increase the capacity of a power transmission line. In addition, the use of controlled series compensation devices affects the steady-state stability of the electric power system. It is also widely known that automatic excitation control of generators has a positive effect on the stability of the system. Thus, it is reasonable to analyze the influence of the adjustable parameters of the controlled series compensation device on the line capacity when considering modes at the boundaries of the stability regions, taking into account automatic excitation controllers on synchronous generators of the power plant. Methods of mathematical modeling of the electric power system, the theory of long-distance power lines and electromechanical transients, methods of analyzing the stability of electric power systems are used. The original software in the C ++ programming language is used as a modeling tool. The authors have selected the regulation laws parameters of controlled series compensation device and automatic excitation controller, provided that steady-state stability is maintained. The stability regions of the electric power-engineering system under study are constructed depending on the tuning parameters of the considered devices. A technique is proposed to select the coefficients of complex regulation of the devices to increase the capacity of a high-voltage power transmission line. The proposed method of the complex selection of regulation coefficients of controlled devices provides the possibility of obtaining their optimal values in a controlled electric power system to ensure stability.

Negative Consequences of High Voltage Power Transmission Lines in Residential Areas and Recommendations for Their Mitigation

Background and objective Urbanization and the expansion of the city limits had led to high voltage power transmission systems being placed in the vicinity of residential areas. Depending on the intensity of the electromagnetic fields caused by these systems and according to the duration of radiation and the distance from these systems, the effect of this exposure on human health varies. A higher voltage can definitely create stronger magnetic fields, which have a negative impact on humans and even the environment. Therefore, it is necessary to investigate the severity of these damages and negative consequences in residential areas where exposure to electromagnetic fields is high so that it can help formulate the necessary policies and plans for the mitigation of damages. Method In this applied study, the library method, interviews with stakeholders, testing of electromagnetic fields, and field visits were used to collect data. The interviews were used to survey the attitudes and perceptions. Laboratory results of electromagnetic fields were used for analysis and making conclusions. Results According to the reports, the lack of production of specialized content by the country’s health planners, the lack of development of criteria and indicators for possible consequences of the manifestations of modernity and, as a result, the impossibility of risk assessment against other threats have caused the inattention and negligence of people and rulers in Iran about the risk of exposure to electric and magnetic fields. On the other hand, the results of assessments showed that the electromagnetic field values in urban closed spaces were lower (due to the presence of walls and buildings that act as shields) and in open spaces were higher than the recommendations of international standards (ICNIRP and IEEE). Therefore, the management of damages caused by high-voltage power transmission lines requires the adoption of various approaches and procedures, which include policy-making, social capacity building, and technical solutions. Conclusion Considering that there is no law related to the negative impact of electromagnetic fields on health in Iran, we recommend a bill entitled “reduction of damages caused by electromagnetic fields” to be submitted to the Islamic Council of Iran and be implemented in the upstream laws.

Dual-Space Graph-Based Interaction Network for RGB-Thermal Semantic Segmentation in Electric Power Scene

Real-time scene comprehension is the basis for automatic electric power inspection. However, existing RGB-based scene comprehension methods may achieve unsatisfied performance when dealing with complex scenarios, insufficient illumination or occluded appearances. To solve this problem, by cooperating visual and thermal images, the Dual-Space Graph-based Interaction Network (DSGBINet) is proposed to achieve all-day time semantic segmentation of power equipment in high-voltage power transmission line and electric transformer substation scenes. Specifically, modality-specific features are first extracted via two separate backbone networks with the same architecture. Multi-modality high-level features are first fused via long-range relationship in coordinate space. Then, multi-modality features from regular grids are further clustered and assigned to vertices in feature space. Cross-graph and inner-graph regional relations are utilized for reasoning and enhancement, which could exploit the mutual benefits and extract rich contextual information in a semantic view. Furthermore, to overcome the huge scale difference and the inherent characteristic of thermal images, the idea of multi-task learning is integrated into the decoding process. The edge detection and semantic segmentation are achieved collaboratively, which could segment the different power equipment more accurately and completely. The comparative and ablation experiments on the proposed two RGB-T semantic segmentation datasets evaluate the effectiveness and robustness of the proposed network compared with existing state-of-the-art methods. The extended experiments on the public datasets further demonstrate the superiority of the proposed method. Our dataset and code will be released at: <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/hhujiang/DSGBINet</uri> .

Design and Application of a UAV Autonomous Inspection System for High-Voltage Power Transmission Lines

As the scale of the power grid continues to expand, the human-based inspection method struggles to meet the needs of efficient grid operation and maintenance. Currently, the existing UAV inspection system in the market generally has short endurance power time, high flight operation requirements, low degree of autonomous flight, low accuracy of intelligent identification, slow generation of inspection reports, and other problems. In view of these shortcomings, this paper designs an intelligent inspection system based on self-developed UAVs, including autonomous planning of inspection paths, sliding film control algorithms, mobile inspection schemes and intelligent fault diagnosis. In the first stage, basic data such as latitude, longitude, altitude, and the length of the cross-arms are obtained from the cloud database of the power grid, while the lateral displacement and vertical displacement during the inspection drone operation are calculated, and the inspection flight path is generated independently according to the inspection type. In the second stage, in order to make the UAV’s flight more stable, the reference-model-based sliding mode control algorithm is introduced to improve the control performance. Meanwhile, during flight, the intelligent UAV uploads the captured photos to the cloud in real time. In the third stage, a mobile inspection program is designed in order to improve the inspection efficiency. The transfer of equipment is realized in the process of UAV inspection. Finally, to improve the detection accuracy, a high-precision object detector is designed based on the YOLOX network model, and the improved model increased the mAP0.5:0.95 metric by 2.22 percentage points compared to the original YOLOX_m for bird’s nest detection. After a large number of flight verifications, the inspection system designed in this paper greatly improves the efficiency of power inspection, shortens the inspection cycle, reduces the investment cost of inspection manpower and material resources, and successfully fuses the object detection algorithm in the field of high-voltage power transmission lines inspection.