Operation Of Power Transmission Lines Research Articles

Fragility Analysis of a Transmission Tower-Line System Subjected to Wind and Ice Loads Considering Fatigue Damage

Disasters such as ice and wind can pose a serious threat to the normal operation of power transmission lines. Wind-induced fatigue damage can further reduce the load-carrying capacity of transmission towers, increasing their fragility to ice and wind disasters. To assess the comprehensive capability of transmission towers to resist extreme ice and wind disasters, this paper proposes a failure probability evaluation framework for transmission towers considering wind-induced fatigue damage under the coupled effect of ice and wind. Taking a certain transmission line in Hunan as an example, the failure probability caused by ice and wind disasters is calculated for different years of service. First, based on the historical meteorological data in three cities in Hunan, a joint probability model of wind speed and wind direction considering their correlation is established using the copula function. Then, based on this probability model, the wind-induced fatigue damage of transmission towers is calculated using the Miner linear damage theory and the S-N curve. Subsequently, the fragility of the tower under the coupled load of ice and wind is calculated for different years of service. Finally, by combining the structural fragility function with the joint probability distribution model of ice thickness and wind speed, the collapse probability of the transmission tower under the action of ice and wind disasters is calculated. The results indicate that the influence of wind-induced fatigue damage cannot be ignored when transmission towers encounter ice and wind disasters. With increasing service time, the ability of transmission towers to resist ice and wind disasters gradually decreases, and the failure probability also increases under extreme ice and wind conditions.

Analysis of electrical performance and assessment of aging state for retired high-voltage cable accessory insulation

The cable accessories constitute a vulnerable element and are prone to failures in the operation of power transmission lines. To investigate the changes in the electrical performance and aging state of high-voltage cable accessories with different operating time, the volume resistivity, breakdown electric field, dielectric constant, and trap parameters of insulation samples taken from retired cable accessories were characterized. The results indicate that there is a certain correlation between the macroscopic dielectric characteristics of cable accessory insulation and its aging state. With the increase of operating time, the volume resistivity and breakdown electric field decrease, while the dielectric constant initially increases and then decreases. The trap distribution of cable accessory insulation can effectively reflect its aging state. With the increase of operating time, the trap energy levels of the accessory insulation become shallower, and the trap density increases. The trap results of the accessory insulation show good consistency with the resistivity and breakdown field strength. Clustering analysis is also used to classify the test data, and the results validate that the trap energy levels and trap density of the insulation samples have better correlation with the insulation aging state of cable accessories than macroscopic dielectric parameters.

Exploration on automatic identification algorithm of transmission line mountain fire based on image recognition technology

In recent years, many places have experienced frequent mountain fires, which have become one of the main disasters in the operation of power transmission lines. However, traditional manual inspection and video monitoring methods can only detect a small amount of mountain fires, and require a large amount of manpower and material resources. In this paper, image recognition technology was used to study the automatic identification algorithm of transmission line mountain fires, and image recognition technology was used to denoise the extracted images. After that, feature extraction was performed on the successfully denoised image, and the image was enhanced to improve the clarity of the image and prepare for improving the recognition accuracy of mountain fires. Through experiments, it can be found that using image recognition technology to identify mountain fires not only has high accuracy and recognition speed, but also has a lower error rate compared to using satellite meteorological data. The recognition accuracy of image recognition technology was above 95 %, while the recognition accuracy of using satellite meteorological data was below 92 %.

Soil cover transformation after the laying of a high-voltage power line

Today the rate of anthropogenic transformations of the soil cover significantly exceeds the rate of its natural restoration. According to a modern digital soil map at a scale of 1 : 200,000 in the Leningrad Region anthropogenically modified subtypes of natural soils, which were formed as a result of human economic activity, predominate. The article considers anthropogenic changes in soils and soil cover of the territory of the high-voltage power line. The study area of 100×500 meters is located in the Tikhvinsky district between the settlements of Kalivets and Novaya Ust-Kapsha. The landscape of the territory belongs to the lake-glacial plain, the soil-forming rocks are lake-glacial sands and sandy loam. Natural soils that are not affected by technological works are found only in the forest, outside the clearing laid during the construction of the power line. These are Albic Podzol, Entic Podzol, Histic Albic Podzol, Histic Entic Podzol and Histic Gleysol. It was revealed that in the study area, the horizons of the original natural soils are partially or completely cut off, turbated, compacted, which led to the formation of their anthropogenically transformed subtypes: over-compacted, abraded, turbid and stratified. Sometimes soil material is exposed to the surface and moved over the study area by tens of meters. After the construction of the high-voltage line, new formations appeared in the soil cover, such as Podzol Nudispodic, buried soils and several types of non-soil formations. It is revealed that each technological operation (logging, installation of power transmission line supports, organization of places for technological operations and the creation of temporary roads) is characterized by its own special disturbances in the soil cover. Thus, after the construction of the power line, there were no natural soils with an undisturbed structure in the soil cover. In addition to the fundamental transformation of the soil cover at the site, natural vegetation was reduced, the mesorelief was partially disrupted and the microrelief was almost completely changed. All these anthropogenic transformations will affect the quality of the ecological functions of the soil cover. During the further operation of power transmission lines, such as clearing a cut-out clearing, updating fire-prevention mineralized strips, maintaining the power grid, disturbances of the soil cover will be periodically repeated, preventing the ecosystem from returning to its original state.

Isolator Detection in Power Transmission Lines using Lightweight Dept-wise Convolution with BottleneckCSP YOLOv5

The detection of insulators is of great importance in power transmission lines. This is because accurate detection ensures reliability and continuity of energy transmission, preventing line interruptions. The proposed method in this study utilizes the DWB-YOLOv5 (Dept-wise convolution with BottleneckCSP YOLOv5) model to effectively detect insulators, contributing to the safe and uninterrupted operation of power lines. In the suggested approach, the DWB-YOLOv5 model is employed to detect insulators. The bottleneckCSP module enhances the accuracy of targets at various scales, while the depth-wise c2onvolution module assists in reducing the model's complexity. Images undergo preprocessing steps such as automatic orientation and resizing. The preprocessed images are fed into the DWB-YOLOv5 model to extract deep features, perform object detection, and conduct classification. The insulator detection model obtained through this method exhibits a minimum of 8.53% better mean average precision (mAP) performance compared to existing methods. This study represents a significant step towards ensuring the safe and uninterrupted operation of power transmission lines. Accurate detection of insulators facilitates the smooth functioning of lines, ensuring reliability and continuity in energy transmission. The proposed method offers important advantages such as high accuracy, lightweight design, and efficiency.

Anomaly detection based on lightweight deep learning algorithms

The safe and reliable operation of power transmission lines is the key to the sustainable and stable operation of power grids. Using the artificial intelligence techniques for the channel status monitoring greatly improves the inspection efficiency of transmission lines. However, the discrimination is mostly conducted on the cloud side, which does not meet the requirement of real-time processing. In this paper, we build an intelligent monitoring system for transmission lines based on edge computing. According to the specific characteristics of the real-world power filed applications, a lightweight deep learning algorithm model is designed. It is then transplanted on a self-developed AI chip and a field test is carried out. The experimental results show that the model designed in this paper balances well between the accuracy, the model size and the inference speed. It realizes status local discrimination of the transmission lines, and promising detection results are obtained.

Minimization of Electric Power Losses on 132 kV and 220 kV Uganda Electricity Transmission Lines

The classical minimization of power losses in transmission lines is dominated by artificial intelligence techniques, which do not guarantee global optimum amidst local minima. Revolutionary and evolutionary techniques are encumbered with sophisticated transformations, which weaken the techniques. Power loss minimization is crucial to the efficient design and operation of power transmission lines. Minimization of losses is one way to meet steady grid supply, especially at peak demand. Thus, this paper has presented a gradient technique to obtain optimal variables and values from the power loss model, which efficiently minimizes power losses by modifying the traditional power loss model that combines Ohm and Corona losses. Optimality tests showed that the unmodified model does not support the minimization of power losses on transmission lines as the Hessian matrix portrayed the maximization of power losses. However, the modified model is consistent with the gradient method of optimization, which yielded optimum variables and values from the power loss model developed in this study. The unmodified (modified) models for Bujagali-Kawanda 220 kV and Masaka West-Mbarara North 132 kV transmission lines in Uganda showed maximum power losses of 0.406 (0.391) and 0.452 (0.446) kW/km/phase respectively. These results indicate that the modified model is superior to the unmodified model in minimizing power losses in the transmission lines and should be implemented for the efficient design and operation of power transmission lines within and outside Uganda for the same transmission voltages.

Triggering Mechanism of Extreme Wind over the Complex Mountain Area in Dali Region on the Yunnan-Guizhou Plateau, China

Wind disasters are responsible for significant physical destruction, injury, loss of life, and economic damage. This study examined the extreme wind triggering mechanism over a typical mountain area with complex terrain, i.e., Dali city in Yunnan Province on the Yunnan-Guizhou Plateau in China. Using the observation data, we first optimized the Weather Research and Forecasting (WRF) model configuration and parametrization schemes for better simulating the wind in this area using a 1-month simulation. Then, the triggering mechanism of extreme wind was investigated by performing a series of sensitive experiments based on a typical extreme wind case. The results indicate that terrain uplift is critical for triggering the local 8–9-scale (the wind velocity between 17.2 and 24.4 m/s) extreme winds over high topography regions. When a large-scale atmospheric circulation is passing, accompanied with regional terrain lifting, the instantaneous wind velocity can reach 9- to 10-scale (the mean wind velocity between 20.8 and 28.4 m/s), causing broken power lines. These results suggest that it is essential to avoid sites where these factors can affect the operation of power transmission lines, or to establish warning systems in the existing systems.

Edge Intelligent Perception Method for Power Grid Icing Condition Based on Multi-Scale Feature Fusion Target Detection and Model Quantization

Insulator is an important equipment of power transmission line. Insulator icing can seriously affect the stable operation of power transmission line. So insulator icing condition monitoring has great significance of the safety and stability of power system. Therefore, this paper proposes a lightweight intelligent recognition method of insulator icing thickness for front-end ice monitoring device. In this method, the residual network (ResNet) and feature pyramid network (FPN) are fused to construct a multi-scale feature extraction network framework, so that the shallow features and deep features are fused to reduce the information loss and improve the target detection accuracy. Then, the full convolution neural network (FCN) is used to classify and regress the iced insulator, so as to realize the high-precision identification of icing thickness. Finally, the proposed method is compressed by model quantization to reduce the size and parameters of the model for adapting the icing monitoring terminal with limited computing resources, and the performance of the method is verified and compared with other classical method on the edge intelligent chip.

Воздействие космической погоды на наземные технологические системы

This review, offered for the first time in the Russian scientific literature, is devoted to various aspects of the problem of the space weather impact on ground-based technological systems. Particular attention is paid to hazards to operation of power transmission lines, railway automation, and pipelines caused by geomagnetically induced currents (GIC) during geomagnetic disturbances. The review provides information on the main characteristics of geomagnetic field variability, on rapid field variations during various space weather mani-festations. The fundamentals of modeling geoelectric field disturbances based on magnetotelluric sounding algorithms are presented. The approaches to the assessment of possible extreme values of GIC are considered. Information about economic effects of space weather and GIC is collected. The current state and prospects of space weather forecasting, risk assessment for technological systems from GIC impact are discussed. While in space geophysics various models for predicting the intensity of magnetic storms and their related geomagnetic disturbances from observations of the interplanetary medium are being actively developed, these models cannot be directly used to predict the intensity and position of GIC since the description of the geomagnetic field variability requires the development of additional models. Revealing the fine structure of fast geomagnetic variations during storms and substorms and their induced GIC bursts appeared to be important not only from a practical point of view, but also for the development of fundamentals of near-Earth space dynamics. Unlike highly specialized papers on geophysical aspects of geomagnetic variations and engineering aspects of the GIC impact on operation of industrial transformers, the review is designed for a wider scientific and technical audience without sacrificing the scientific level of presentation. In other words, the geophysical part of the review is written for engineers, and the engineering part is written for geophysicists. Despite the evident applied orientation of the studies under consideration, they are not limited to purely engineering application of space geophysics results to the calculation of possible risks for technological systems, but also pose a number of fundamental scientific problems.

Space weather impact on ground-based technological systems

This review, offered for the first time in the Russian scientific literature, is devoted to various aspects of the problem of the space weather impact on ground-based technological systems. Particular attention is paid to hazards to operation of power transmission lines, railway automation, and pipelines caused by geomagnetically induced currents (GIC) during geomagnetic disturbances. The review provides information on the main characteristics of geomagnetic field variability, on rapid field variations during various space weather mani-festations. The fundamentals of modeling geoelectric field disturbances based on magnetotelluric sounding algorithms are presented. The approaches to the assessment of possible extreme values of GIC are considered. Information about economic effects of space weather and GIC is collected. The current state and prospects of space weather forecasting, risk assessment for technological systems from GIC impact are discussed. While in space geophysics various models for predicting the intensity of magnetic storms and their related geomagnetic disturbances from observations of the interplanetary medium are being actively developed, these models cannot be directly used to predict the intensity and position of GIC since the description of the geomagnetic field variability requires the development of additional models. Revealing the fine structure of fast geomagnetic variations during storms and substorms and their induced GIC bursts appeared to be important not only from a practical point of view, but also for the development of fundamentals of near-Earth space dynamics. Unlike highly specialized papers on geophysical aspects of geomagnetic variations and engineering aspects of the GIC impact on operation of industrial transformers, the review is designed for a wider scientific and technical audience without sacrificing the scientific level of presentation. In other words, the geophysical part of the review is written for engineers, and the engineering part is written for geophysicists. Despite the evident applied orientation of the studies under consideration, they are not limited to purely engineering application of space geophysics results to the calculation of possible risks for technological systems, but also pose a number of fundamental scientific problems.

Design and implementation of power mobile inspection system based on Improved Particle Swarm Optimization

Power line inspection is a basic work to effectively guarantee the safe operation of power transmission lines, improve the safe and reliable operation of power transmission lines, and reduce the occurrence of faults. Mobile inspection system is used to analyze the main influencing factors of power grid, and multiple linear regression method, BP neural network method and grey system theory method are used to detect the mobile inspection system. In order to obtain more accurate detection results, a combination algorithm based on improved particle swarm optimization (IPSO) is adopted, and the detection results of the three methods are optimally combined to obtain the final detection value. The analysis of an example shows that this method can effectively improve the detection accuracy and get better detection results.

Design of patrol and control platform for power network based on UAV and VR

Since the beginning of the twenty-one th century, with the rapid development of China’s economy and the continuous progress of China’s power industry, it has contributed an indelible force to the development of China’s socialist undertakings The construction of power grid is very important to the development of society. The normal operation of the power grid can not be separated from regular inspection of power grid equipment and lines, so as to keep abreast of and understand the operation of power transmission lines and changes in the surrounding environment and Line Protection Areas Is the power supply enterprise a heavy daily work. Manual inspection is a traditional inspection method, but also the main way of transmission line inspection. Due to the complex terrain of the transmission line corridor, there are almost no patrol roads in some sections along the route in some harsh conditions such as river-crossing or high mountains and steep mountains. This patrol method has great labor intensity and difficult working conditions Transmission lines can not get timely feedback, and can not observe the real-time intuitive operation of lines and equipment. In this case, in response to the national “Internet +” strategic thinking, we initiated the “Internet +”, “UAV +” and “VR +” all-ecological power grid patrol mode Realize the power network equipment long-distance inspection, all-round inspection, real-time simulation inspection, inspection in bad environment, so that the cause of power inspection can take off.

Rockfall hazard identification and assessment of the Langxian- Milin section of the transmission line passage of Central Tibet Grid Interconnection Project

In order to select the location of transmission towers in Central Tibet Grid Interconnection Project and provide hazard prevention strategies for the safe operation of power transmission lines, we used remote sensing technology to carry out the rockfall interpretation, according to which the space distribution for the rockfall hazard was identified. Then, on-site investigation and UAV aerial survey were conducted in the typical section. Using the scoring method, we selected eight factors including topography, lithology, rock structure, slope structure, hydrogeological conditions, vegetation development, historical rockfall, and slope stability status. The results of the study showed that 116 rockfalls were identified in the transmission line passage of Central Tibet Grid Interconnection Project. Since the rockfall linear density of the Langxian-Milin section was greater than that of other sections, this section was selected as a typical survey section, and assessments were conducted in this section. The study area was classified as high serious, serious, medium serious, and low serious four levels.

Synergy of the future: high voltage insulated power cables and railway‐highway structures

The rationalisation of the territorial resources leads to consider carefully the possibilities of using motorway and railway infrastructures (existing or planned ones) for cable line installation within them. The full compatibility of such synergy ‘transport – electrical power transmission’ involves different branches of engineering. The study provides an overview of the research undertaken for a fully reliable use of this combination. The manuscript aims at highlighting a procedural approach that should be followed in order to analyse all the key elements involved in the safe operation of power transmission lines hosted in transport infrastructures. First, the geometrical compatibility between different types of power transmission technologies, (i.e. gas insulated lines and high-voltage direct/alternating current insulated cable lines), and transport infrastructures (i.e. motorway galleries, railway galleries and railway prospection tunnels) is considered. Subsequently, the behaviour and magnitude of the magnetic field generated by the different power transmission technologies inside the transport infrastructures are presented. Moreover, the study analyses the effects of a phase-to-screen short circuit that could occur inside the hosting facility. Finally, an analysis of the reliability of the synergy between power transmission systems and transport infrastructures is discussed.

A Novel Algorithm for Fault Type Fast Diagnosis in Overhead Transmission Lines Using Hidden Markov Models

Power transmission lines are one of the most important components of electric power system. Failures in the operation of power transmission lines can result in serious power system problems. Hence, fault diagnosis (transient or permanent) in power transmission lines is very important to ensure the reliable operation of the power system. A hidden Markov model (HMM), a powerful pattern recognizer, classifies events in a probabilistic manner based on fault signal waveform and characteristics. This paper presents application of HMM to classify faults in overhead power transmission lines. The algorithm uses voltage samples of one-fourth cycle from the inception of the fault. The simulation performed in EMTPWorks and MATLAB environments validates the fast response of the classifier, which provides fast and accurate protection scheme for power transmission lines.