Search Results (20)

Severe surface deformation induced by super-large mining height longwall extraction poses a significant threat to the safe operation of high-voltage transmission towers. In this study, a 330 kV straight-line transmission tower located above the 122104 working face of the Caojiatan Coal Mine was selected as a case study to investigate tower stability under mining-induced surface deformation and to develop corresponding protection technologies. An integrated monitoring system combining instantaneous and long-term measurements was established to characterize surface movement throughout the mining process. The results indicate that the maximum surface subsidence reached 7300 mm, while the maximum inclination and curvature attained 50 mm/m and 0.62 mm/m², respectively, reflecting intense deformation of the overlying ground. Numerical simulations based on ANSYS 2021R1 were conducted to systematically evaluate the effects of surface inclination, compressive deformation, and tensile deformation on the structural response of the transmission tower. The critical deformation thresholds leading to structural failure were identified as 30 mm/m for inclination, −7.2 mm/m for horizontal compression, and 7.7 mm/m for horizontal tension. Based on these findings, a comprehensive protection system was proposed, integrating tower body reinforcement, combined foundation reconstruction, surface subsidence monitoring, dynamic jacking-based rectification, and foundation grouting reinforcement. The proposed scheme was successfully implemented in field practice. Monitoring results demonstrate that, after reinforcement and rectification, differential settlement of the tower foundation was controlled within 20 mm, and tower inclination remained below 1‰. This ensured uninterrupted underground mining operations and continuous power transmission within the Caojiatan Coal Mine corridor. The outcomes of this study provide a practical reference for the protection of high-voltage transmission towers under similar mining conditions. Full article

With the expansion of the scale of ultra-high-voltage transmission lines and the complexity of the corridor environment, the traditional manual inspection method faces serious challenges in terms of efficiency, cost, and safety. In this study, based on power laser inspection technology with a high-precision servo control system, a complete set of laser point cloud processing technology is proposed, covering three core aspects: transmission line extraction, scene recovery, and operation status monitoring. In transmission line extraction, combining the traditional clustering algorithm with the improved PointNet++ deep learning model, a classification accuracy of 92.3% is achieved in complex scenes; in scene recovery, 95.9% and 94.4% of the internal point retention rate of transmission lines and towers, respectively, and a vegetation denoising rate of 7.27% are achieved by RANSAC linear fitting and density filtering algorithms; in the condition monitoring segment, the risk detection of tree obstacles based on KD-Tree acceleration and the arc sag calculation of the hanging chain line model realize centimetre-level accuracy of hidden danger localisation and keep the arc sag error within 5%. Experiments show that this technology significantly improves the automation level and decision-making accuracy of transmission line inspection and provides effective support for intelligent operation and maintenance of the power grid. Full article

With the continuous expansion of power grids and the advancement of ultra-high voltage (UHV) projects, transmission lines are increasingly traversing areas characterized by micro-terrain. These localized topographic features can intensify meteorological effects, thereby increasing the risks of hazards such as conductor icing and galloping, directly threatening operational stability. Enhancing the disaster resilience of transmission lines in such environments requires accurate and efficient terrain identification. However, conventional recognition methods often neglect the spatial alignment of the transmission lines, limiting their effectiveness. This paper proposes a deep learning-based recognition framework that incorporates a dual-branch network architecture and a cross-branch spatial attention mechanism to address this limitation. The model explicitly captures the spatial correlation between transmission lines and surrounding terrain by utilizing line alignment information to guide attention along the line corridor. A semi-synthetic dataset, comprising 6495 simulated samples and 130 real-world samples, was constructed to facilitate model training and evaluation. Experimental results show that the proposed model achieves classification accuracies of 94.6% on the validation set and 92.8% on real-world test cases, significantly outperforming conventional baseline methods. These findings demonstrate that explicitly modeling the spatial relationship between transmission lines and terrain features substantially improves recognition accuracy, offering important support for hazard prevention and resilience enhancement in UHV transmission systems. Full article

Electrification of the transport sector introduces operational issues in the electricity distribution network, such as excessive voltage deviation, substation overloading, and adverse power quality impacts on other network loads. These concerns are expected to grow as electrification expands to incorporate heavy vehicles such as trucks and buses due to their greater energy requirements and higher charging loads. Two strategies are proposed to support medium- and heavy-duty chargers which address their high power demand and mitigate power quality disturbances and the overloading of substations. The first is a dedicated feeder connected at the secondary of the substation directly to the charging station which aims to reduce the impact of high load on other customers. The second is the addition of a dedicated substation that solely provides power for charging stations in major corridors, alleviating stress on existing zone substations. Hosting capacity is measured using a voltage deviation index, describing the deviation in line voltage, which should experience a sag of no more than 6% of the nominal voltage, and a substation charging capacity index, describing the available capacity of each zone substation as a ratio of its total power capacity. Verification of the proposed strategies was performed on an MV-LV distribution network representative of an industrial Australian town with heavy-vehicle charging. Results showed that the network could handle ten 250 kW chargers, which was tripled to 35 with a dedicated feeder. The dedicated feeder alternatively allowed up to 10 megawatt-scale chargers, which was again tripled when a dedicated substation was introduced. Full article

The electric field of transmission lines has serious negative impacts on residents’ production and life with the expansion of high voltage engineering. In order to study the influence of trees on the electric field of ultra-high voltage transmission lines, this paper conducted three-dimensional simulation calculations of the power frequency electric field of transmission lines based on the tree quantity and distribution. Firstly, in order to study the pattern of electric field strength distribution in transmission lines, the electric field strengths of transmission lines of different voltage levels were compared; the maximum-power-frequency electric field intensity of ultra-high voltage transmission lines occurs below the edge conductor. Secondly, by changing the number of trees, it was concluded that the electric field strength below the edge conductor gradually decreases with the number of trees. Finally, the maximum electric field strength value at 1.5 m below the edge conductor and the width of the transmission corridor decreased by changing the layout of the trees. The results show that studying the impact of a tree’s electromagnetic parameters on the power frequency electric field strength under transmission lines can help reduce the electric field strength and decrease the width of transmission corridors, which is of great significance for line design and cost savings. Full article

The high-speed railway project and the ultra-high-voltage transmission project represent two crucial components of China’s “new infrastructure”. As the construction of these two projects progresses rapidly, it is inevitable that instances of intersections will occur. Extreme conditions may cause damage to ultra-high voltage transmission cables. When a high-speed train passes by an ultra-high voltage transmission line, it poses a serious safety hazard. To address this issue, engineering examples were utilized to examine the protection structure scheme, protection distance, protection load, and construction procedures when a high-speed railway intersects a 1000 KV ultra-high voltage transmission line. A shed structure form and construction method for the electric power protection were proposed to ensure the safe operation of the high-speed railway while also achieving the safe and rapid construction of the high-speed railway protection structure in the safety zone of the approaching 1000 kV ultra-high voltage transmission line. The results indicated that the protection of high-speed railway crossings and 1000 kV ultra-high voltage transmission lines primarily focuses on line-break protection. The concrete shed structure with a straight wall and a flat roof was designed to meet the requirements of high-speed railway crossings. The line-break protection method enables the construction of an automatic warning protection corridor and a complete movable trolley quickly and safely within the safety zone near the transmission line. The implementation effect is, therefore, positive. It can be used as a reference point for other projects of a similar nature. Full article

Recently, significant attention has been paid to the large-scale use of renewable energy through high-voltage direct current (HVDC) because of its economic feasibility. At the same time, the growing demand for electricity and the increasing penetration of renewable energy sources have prompted the electric power industry to explore methods to optimize the use of the existing grid infrastructure. Dynamic thermal line rating (DTLR) is a technique that allows transmission lines to operate at their maximum capacity, considering their real-time operating conditions. The majority of existing research on this topic has focused predominantly on employing DTLR in alternating current systems and exploring their applications. This study presents a novel approach by applying DTLR to HVDC transmission corridors, with the aim of maximizing the utilization of their capacity and facilitating increased integration of renewable energy. The performance of the proposed approach is evaluated by conducting a case study for an HVDC transmission line in Alberta, Canada. On average, the mean increase in ampacity above the static rating is 64% during winter and 34% during summer. This additional capacity can be used to integrate wind energy, replacing coal-fired generation. This leads to a significant reduction in greenhouse gas emissions, also quantified in this contribution. Full article

Fast reconstruction of power lines and corridors is a critical task in UAV (unmanned aerial vehicle)-based inspection of high-voltage transmission corridors. However, recent dense matching algorithms suffer the problem of low efficiency when processing large-scale high-resolution UAV images. This study proposes an efficient dense matching method for the 3D reconstruction of high-voltage transmission corridors with fine-scale power lines. First, an efficient random red-black checkerboard propagation is proposed, which utilizes the neighbor pixels with the most similar color to propagate plane parameters. To combine the pixel-wise view selection strategy adopted in Colmap with the efficient random red-black checkerboard propagation, the updating schedule for inferring visible probability is improved; second, strategies for decreasing the number of matching cost computations are proposed, which can reduce the unnecessary hypotheses for verification. The number of neighbor pixels necessary to propagate plane parameters is reduced with the increase of iterations, and the number of the combinations of depth and normal is reduced for the pixel with better matching cost in the plane refinement step; third, an efficient GPU (graphics processing unit)-based depth map fusion method is proposed, which employs a weight function based on the reprojection errors to fuse the depth map. Finally, experiments are conducted by using three UAV datasets, and the results indicate that the proposed method can maintain the completeness of power line reconstruction with high efficiency when compared to other PatchMatch-based methods. In addition, two benchmark datasets are used to verify that the proposed method can achieve a better $F_1$ score, 4–7 times faster than Colmap. Full article

Power-line inspection is an important means to maintain the safety of power networks. Light detection and ranging (LiDAR) technology can provide high-precision 3D information about power corridors for automated power-line inspection, so there are more and more utility companies relying on LiDAR systems instead of traditional manual operation. However, it is still a challenge to automatically detect power lines with high precision. To achieve efficient and accurate power-line extraction, this paper proposes an algorithm using entropy-weighting feature evaluation (EWFE), which is different from the existing hierarchical-multiple-rule evaluation of many geometric features. Six significant features are selected (Height above Ground Surface (HGS), Vertical Range Ratio (VRR), Horizontal Angle (HA), Surface Variation (SV), Linearity (LI) and Curvature Change (CC)), and then the features are combined to construct a vector for quantitative evaluation. The feature weights are determined by an entropy-weighting method (EWM) to achieve optimal distribution. The point clouds are filtered out by the HGS feature, which possesses the highest entropy value, and a portion of non-power-line points can be removed without loss of power-line points. The power lines are extracted by evaluation of the other five features. To decrease the interference from pylon points, this paper analyzes performance in different pylon situations and performs an adaptive weight transformation. We evaluate the EWFE method using four datasets with different transmission voltage scales captured by a light unmanned aerial vehicle (UAV) LiDAR system and a mobile LiDAR system. Experimental results show that our method demonstrates efficient performance, while algorithm parameters remain consistent for the four datasets. The precision F value ranges from 98.4% to 99.7%, and the efficiency ranges from 0.9 million points/s to 5.2 million points/s. Full article

High-voltage and ultra-high-voltage overhead power lines are important to meet the electricity demand of our daily activities and productions. Due to the overgrowth of trees/vegetation within the corridor area, the distance between the power lines and its surroundings may break through the safety threshold, which could cause potential hazards such as discharge and fire. To ensure the safe and stable operation of the power lines, it is necessary to survey them regularly so that the potential hazards from the surroundings within the power line corridor could be investigated timely. This paper is motivated to quickly and accurately survey the power line corridor with the 3D point clouds. The main contributions of this paper include: (1) the spatial line clustering is proposed to accurately classify and complete the power line points, which can greatly overcome the sparsity and missing of LiDAR points within the complex power line corridor. (2) The contextual relationship between power lines and pylon is well investigated by the grid-based analysis, so that the suspension points of power lines on the pylon are well located. (3) The catenary plane-based simplification of 3D spatial distance calculation between power lines and ground objects facilitates the survey of the power line corridor. Experimental results show that the accuracy of safety distance surveying is 5 cm for power line corridors of all voltage levels. Compared to the ground-truth point-to-point calculation, the speed of surveying is enhanced thousands of times. It is promising to greatly improve both the accuracy and efficiency of surveying the potential hazards of power line corridor. Full article

Overhead high-voltage conductors are the chief components of power lines and their safety has a strong influence on social and daily life. In the recent decade, the airborne laser scanning (ALS) technique has been widely used to capture the three-dimensional (3D) information of power lines and surrounding objects. Most of the existing methods focused on extraction of single conductors or extracted all conductors as one object class by applying machine learning techniques. Nevertheless, power line corridors (PLCs) are built with multi-loop, multi-phase structures (bundle conductors) and exist in intricate environments (e.g., mountains and forests), and thus raise challenges to process ALS data for extraction of individual conductors. This paper proposes an automated method to extract individual subconductors in bundles from complex structure of PLCs using a combined image- and point-based approach. First, the input point cloud data are grouped into 3D voxel grid and PL points and separated from pylon and tree points using the fact that pylons and trees are vertical objects while power lines are non-vertical objects. These pylons are further separated from trees by employing a statistical analysis technique and used to extract span points between two consecutive pylons; then, by using the distribution properties of power lines in each individual span, the bundles located at different height levels are extracted using image-based processing; finally, subconductors in each bundle are detected and extracted by introducing a window that slides over the individual bundle. The orthogonal plane transformation and recursive clustering procedures are exploited in each window position and a point-based processing is conducted iteratively for extraction of complete individual subconductors in each bundle. The feasibility and validity of the proposed method are verified on two Australian sites having bundle conductors in high-voltage transmission lines. Our experiments show that the proposed method achieves a reliable result by extracting the real structure of bundle conductors in power lines with correctness of 100% and 90% in the two test sites, respectively. Full article

Power system load growth and transmission corridor constraints are driving industry activity in the area of high surge impedance loading (HSIL). Examples include compact structure design and uprating existing transmission lines. Recent research relating electric field uniformity to transmission line capacity and critical flashover voltage underscored the need for better overvoltage data to quantify insulation margins for HSIL design. To that end, this work extends the finite difference time domain (FDTD) method with distributed corona losses to transmission lines with bundled conductors. The model was adapted for practical use in high-volume statistical transient simulation and applied to an example 500 kV line. Transients included line energization and trapped charge reclosing. Overvoltage profiles and statistical distributions were generated from 9500 simulations obtained by random breaker close timing and variation in line length and altitude. Distributed corona losses reduced 98th percentile line-to-ground switching overvoltages by 4%–14% of nominal. The estimated line-to-ground switching surge flashover probability was 54%–80% lower with corona loss. Corona had less impact on line-to-line overvoltages, but the effects were still notable. Results highlight the importance of considering detailed overvoltage profiles and accounting for corona loss attenuation when seeking to carefully quantify insulation design margins. Full article

Electric power transmission and maintenance is essential for the power industry. This paper proposes a method for the efficient extraction and classification of three-dimensional (3D) targets of electric power transmission facilities based on regularized grid characteristics computed from point cloud data acquired by unmanned aerial vehicles (UAVs). First, a spatial hashing matrix was constructed to store the point cloud after noise removal by a statistical method, which calculated the local distribution characteristics of the points within each sparse grid. Secondly, power lines were extracted by neighboring grids’ height similarity estimation and linear feature clustering. Thirdly, by analyzing features of the grid in the horizontal and vertical directions, the transmission towers in candidate tower areas were identified. The pylon center was then determined by a vertical slicing analysis. Finally, optimization was carried out, considering the topological relationship between the line segments and pylons to refine the extraction. Experimental results showed that the proposed method was able to efficiently obtain accurate coordinates of pylon and attachments in the massive point data and to produce a reliable segmentation with an overall precision of 97%. The optimized algorithm was capable of eliminating interference from isolated tall trees and communication signal poles. The 3D geo-information of high-voltage (HV) power lines, pylons, conductors thus extracted, and of further reconstructed 3D models can provide valuable foundations for UAV remote-sensing inspection and corridor safety maintenance. Full article

The rapid growth of the network of high-voltage power transmission lines (HVPTLs) is inevitably covering more forest domains. However, no direct quantitative measurements have been reported of the effects of HVPTLs on vegetation growth. Thus, the impacts of HVPTLs on vegetation growth are uncertain. Taking one of the areas with the highest forest coverage in China as an example, the upper reaches of the Minjiang River in Fujian Province, we quantitatively analyzed the effect of HVPTLs on forest landscape fragmentation and vegetation growth using Landsat imageries and forest inventory datasets. The results revealed that 0.9% of the forests became edge habitats assuming a 150 m depth-of-edge-influence by HVPTLs, and the forest plantations were the most exposed to HVPTLs among all the forest landscape types. Habitat fragmentation was the main consequence of HVPTL installation, which can be reduced by an increase in the patch density and a decrease in the mean patch area (MA), largest patch index (LPI), and effective mesh size (MESH). In all the landscape types, the forest plantation and the non-forest land were most affected by HVPTLs, with the LPI values decreasing by 44.1 and 20.8%, respectively. The values of MESH decreased by 44.2 and 32.2%, respectively. We found an obvious increasing trend in the values of the normalized difference vegetation index (NDVI) in 2016 and NDVI growth during the period of 2007 to 2016 with an increase in the distance from HVPTL. The turning points of stability were 60 to 90 meters for HVPTL corridors and 90 to 150 meters for HVPTL pylons, which indicates that the pylons have a much greater impact on NDVI and its growth than the lines. Our research provides valuable suggestions for vegetation protection, restoration, and wildfire management after the construction of HVPTLs. Full article

The security of high-voltage power transmission corridors is significantly vital to the national economy and daily life. With its rapid development, LiDAR (Light Detection and Ranging) technology has been widely applied in the inspection of transmission lines. As the basis of potential hazard detection, a robust and precise power line model is a necessary requirement for rapid and correct clearance. Thus, this paper proposes a novel method for high-voltage bundle conductor reconstruction, which can precisely reconstruct each sub-conductor. First, points in high-voltage power transmission corridors are detected and classified into four categories; second, for classified power lines, single power line spans are extracted, and bundle conductors are identified by analyzing the single spans’ fitting residuals; and then, each sub-conductor of bundle conductors is extracted by a projected dichotomy method on the XOY and XOZ planes, respectively; finally, a double-RANSAC (random sample consensus)-based algorithm was introduced to reconstruct each power line. The proposed method makes use of the distribution of bundle conductors in high-voltage transmission lines, and our experiments showed that it could preferably reconstruct the real structure of bundle conductors robustly with a high precision better than 0.2 m. Full article