Transmission Line Insulators Research Articles

Study on pollution flashover characteristic of insulators on 500 kV AC transmission lines in high‐altitude area

Pollution flashover performance of insulators is one of the key factors to be considered in the selection of external insulation for transmission lines at high-altitude areas. In pollution laboratories at Tibet high-altitude test base and Beijing ultra high voltage direct current (UHVDC) test base, artificial pollution tests of insulators adopted in AC 500 kV transmission project are performed both in sea-level region and real high-altitude regions, through which flashover voltages at typical equivalent salt deposit density are obtained. The relationship between altitude and flashover voltage is acquired as well.

Switching impulse discharge characteristics of UHV transmission line air gaps

The design of external insulation for transmission lines is usually based on real‐type experiments. With the increasing voltage level of the transmission lines, in order to better design the experiments and reduce the experiment workload in the future, this paper studies the switching impulse discharge characteristics of air gaps of an ultrahigh‐voltage (UHV) transmission line. A long air gap switching impulse breakdown voltage prediction method based on the leader discharge mechanism is proposed in this paper, and a continuous leader inception model is fitted for the air gaps in UHV transmission lines by calculating the factor R of the conductor–plane gaps. The method and the model can effectively predict the air gap breakdown voltage of transmission lines. The influence of tower width and conductor structure on air gap breakdown characteristics of UHV transmission lines is studied by the method and the model proposed this paper. The results show that, as the width of the tower increases, the breakdown voltage decreases, and as the gap length increases, the influence of the tower width on the breakdown voltage decreases. The conductor structure has no obvious influence on the discharge characteristics of transmission line air gaps. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Electric field analysis and structure design of the box of bird guard used in 220 kV transmission line

Bird activities including the defecation, nesting, and flight are easy to cause electrical faults of overhead transmission lines, study on the prevention measures of bird damage to transmission lines is of great significance to ensure the stable and reliable operation of the power system. With the establishment of finite element simulation model, the effects of box of bird guard with different material on the electric field and potential distribution on transmission line insulators are studied. Besides, combined with the theory of air discharge and the results of simulation, the influence of rainwater on the air gap around the insulator breakdown characteristics is studied when the water is drained from a scupper at the bottom of the box of bird guard, and a reasonable design scheme for the box of bird guard scupper is proposed. The research results here can provide a guidance for the selection and key parameters’ design of the box of bird guard.

Study on Hydrophobicity Detection of Composite Insulators of Transmission Lines by Image Analysis

Hydrophobicity of the composite insulators is a parameter which is closely related to the insulation properties. In order to determine whether the insulator in the transmission line needs to be withdrawn, it is necessary to objectively and accurately determine the hydrophobicity grade of the composite insulator. The study on hydrophobicity detection of composite insulators of transmission lines by image analysis is proposed in this paper, by which the hydrophobicity of composite insulators can be measured timely. The grayscale, median filtering, and histogram equalization of the hydrophobic images are fulfilled sequentially, and the water drops (or water marks) region is segmented by binary large object analysis and four parameters related to water repellency are extracted. In addition, the improved support vector machine algorithm is adopted to calculate the hydrophobicity of composite insulators. The results show that seven typical hydrophobic levels of insulators can be recognized by the proposed hydrophobicity detection method whose accuracy is more than 91%.

Technology of Actual Wind Deviation Monitoring for Suspension Insulator Strings Based on Improved Edge Detection

Finding out the wind deviation fault of the insulators of transmission lines in time can not only help people better complete the wind bias warning and prevention work, but also reduce the economic loss and the maintenance difficulty. A technology of Actual Wind Deviation Monitoring for Suspension Insulator Strings Based on Improved Edge Detection is proposed in this paper. It can calculate the actual wind deviation angle and distance of the insulator through image processing technology and camera calibration. Firstly, the video monitoring device is installed on the tower to collect the field insulator images, and the R + G improved grayscale processing and median filtering are carried out. Secondly, two-dimensional Otsu threshold segmentation is applied to the pre-processed image, and the insulator string target is obtained by combining morphological filtering and connection domain extraction. Then, the improved Kirsch operator is used to obtain the complete single-pixel wide edge of the insulator string. Searching the left and right boundary points of each insulator separately and the center points of each insulator can be calculated. Finally, these center points are transformed into world coordinates by camera calibration and fitted by least square method (LSM). The deviation angle $\theta $ of the insulator string can be obtained according to the slope of the fitting line, and the deviation distance $d$ according to the length of the insulator string. When $\theta $ is greater than 7.5° and $d$ is greater than 300mm, an alarm is issued to alert the staff. We analyze the performance of the technology by a series of experiments, the maximum error between the proposed method and the manual method is 8.72% and the minimum is 1.01%. Moreover, by analyzing 200 field insulator images, the identification accuracy are 93.75% and 91.36% respectively, which shows that the proposed method is effective and practical. It provides a new idea for the wind deviation monitoring of suspension insulator strings.

Development and Application of Live Replacement of Insulator Suspension Tool Components for Transmission Lines

Transmission line insulators will reduce the insulation level and become low-value insulators because of lightning flashover. Toughened glass insulators are used in 500kV Tongfeng 1 and 2 lines in Tonghua area. Most umbrella skirts will break and fall off after lightning flashover, which greatly reduces the insulation performance. It needs to be replaced in time, but frequent blackouts will bring great losses and reduce the reliability of power supply. Aiming at the frequent lightning hazards and lightning strikes on transmission lines in Tonghua area, a tool assembly for live replacement of insulators for transmission lines is developed. Through the application of this tool, the live operation mode is adopted to eliminate such defects. The operation time can be arranged and implemented in a very timely manner, which avoids the threat of long-term defects, effectively reduces the outage time of equipment, enhances the stability of power grid, and greatly improves the reliability of power supply of lines. Finally, taking the live line insulator suspension tool as an example, the economic benefit analysis is given, and the feasibility and correctness of the tool are verified..

Fiber Bragg grating monitors for thermal and stress of the composite insulators in transmission lines

Running composite insulators are prone to failure due to their harsh surrounding work environment, which directly affects the safe operation of transmission lines. This paper puts forward the method of using fiber Bragg grating (FBG) as the monitors to parameters correlated with thermal and stress of the composite insulators in transmission lines at working status. Firstly, monitoring points are found out by the mechanical test on composite insulator samples. Secondly, based on the monitoring theory, this paper introduces the feasibility design frame of the composite insulator with FBG implanted in the rod and the online monitor system. At last, it describes applications of this monitor system in the field of transmission lines.

Prediction model of insulator contamination degree based on adaptive mutation particle swarm optimisation and general regression neural network

The contaminants accumulated on the surface of transmission line insulator mainly come from the suspended particles in the air. Therefore, it is necessary to consider meteorological factors and environmental factors in the prediction of insulator contamination degree. In view of the advantages of generalised regression neural network (GRNN) in the aspects of fault tolerance and robustness, this study uses it to predict equivalent salt deposit density (ESDD). Furthermore, the adaptive mutation particle swarm optimisation and GRNN prediction model is proposed in this study. According to adaptive algorithm and mutation algorithm, the inertia weight and acceleration factor of particles are dynamically adjusted to achieve the purpose of searching global optimal smoothing factor. The optimisation method can effectively avoid the premature convergence of particle swarm optimisation (PSO) and solve the drawback that PSO is easy to fall into the local optimal value. The results show that the prediction model proposed in this study can effectively predict the insulators ESDD, and the prediction error is less than the GRNN and PSO–GRNN models. The research can provide guidance for the development of a more scientific and rational maintenance plan to achieve effective control of the contaminants of the line.

Non-Uniform Distribution of Contamination on Composite Insulators in HVDC Transmission Lines

In recent years, the air particulate pollutants formed by the combustion of fossil fuels and the emission of industrial waste gases have constantly been produced, and the polluted particles deposit also seriously affects social production and people’s lives. For instance, pollution-induced flashover is seriously threatening the safe operation of the power system, while insulator pollution non-uniformity has great influence on the flashover voltage of insulators. Therefore, in this paper both field contamination experiments of HVDC (High Voltage Direct Current) transmission lines and wind tunnel contamination simulation tests were conducted, and pollution non-uniformity coefficient KT/B, KW/L and KH/M were proposed and obtained. The results showed that the degree of contamination on top surface and leeward side is heavier than that on bottom surface and windward side. Thus, in the DC energized condition, contamination along the string is also non-uniform, and serious pollution occurs mainly in the high voltage terminal. In order to explain the uneven distribution phenomenon along the string, the coupling-physics model of composite insulator string was established and using the finite element method, the electric field around the insulator was simulated. Furthermore, basing on the field charging theory, the value of electric field force on particles around the insulator surface was calculated and the mechanism of non-uniformity along the insulator sting was then explained. The results are very important for guiding insulation design and field anti-pollution works.

Evaluation of the electrical properties and mechanical behavior of insulator’s composite core in harsh environments

Recent developments in applying composites in different industries result in replacing traditional materials with them. Polymer matrix composites have become one of the most popular advanced materials in the industries due to their peculiar properties, appropriate cost, and various and easy manufacturing methods. In this project, electrical, physical and mechanical properties of glass fiber reinforced polymer (GFRP) composites including acid absorption, breakdown voltage, and tensile strength have been investigated in order to be used as insulators in power transmission lines. In order to identify the chemical structure of neat resins and their composites, and also determining the possibility of bonding between polymer and glass, Fourier Transform Infrared Spectroscopic (FTIR) test was conducted. Regarding high voltage tests, a direct correlation was found between the amount of absorbed moisture by the specimens and the amount of breakdown voltage. The composites were degraded because of exposing, and this behavior was verified by Scanning Electron Microscopy (SEM) and Atomic Absorption Spectrometry (AAS) analysis. The results indicated a drop of 2.53% and 2.83% in tensile strength for E-glass epoxy and polyester composites with acid aging, respectively. Also, the breakdown voltage declined to 32 and 21 kV mm−1 after the moisture content reached 0.1% and 0.27% for E-glass epoxy and polyester composites, respectively. It can be concluded that epoxy matrix composite is more resistant to acid exposure compared to polyester matrix composite and is more suitable to be used in power transmission lines.

Metal Contamination Distribution Detection in High-Voltage Transmission Line Insulators by Laser-induced Breakdown Spectroscopy (LIBS).

The fast detection of classical contaminants and their distribution on high-voltage transmission line insulators is essential for ensuring the safe operation of the power grid. The analysis of existing insulator contamination has traditionally relied on taking samples during a power cut, taking the samples back to the lab and then testing them with elemental analysis equipment, especially for sugars, bird droppings, and heavy metal particulates, which cannot be analysed by the equivalent salt deposit density (ESDD) or non-soluble deposit density (NSDD) methods. In this study, a novel method called laser-induced breakdown spectroscopy (LIBS) offering the advantages of no sample preparation, being nearly nondestructive and having a fast speed was applied for the analysis of metal contamination. Several LIBS parameters (laser energy and delay time) were optimized to obtain better resolution of the spectral data. The limit of detection (LOD) of the observed elements was obtained using a calibration curve. Compared to calibration curves, multivariate analysis methods including principal component analysis (PCA), k-means and partial least squares regression (PLSR) showed their superiority in analyzing metal contamination in insulators. Then, the elemental distribution of natural pollution was predicted using LIBS to fully capture information about the bulk elements (Na, Ni, Cu, Mn, Ca, etc.) of entire areas with PLSR. The results showed that LIBS could be a promising method for accurate direct online quantification of metal contamination in insulators.

A Study on the Life-Time Assessment Ways and Various Failure Types of 154 kV Porcelain Insulators Installed in South Korea

In this study, we investigated 154-kV porcelain insulators with various failure types and discussed the causes of the failures. In South Korea, 1,223,538 154 kV porcelain insulators (produced by a foreign company) are in active service in 2017, installed in overhead power transmission lines. Among them, 797,659 (65.19%) have been used over 30 years in active service. Porcelain insulators employed in transmission lines need to exhibit a high electrical resistance, mechanical strength, stability, and ability to maintain satisfactory performance under various environments. In this study, a life-time assessment strategy is proposed for the 154 kV porcelain insulators according to the operational circumstances. The life-time extrapolation of porcelain insulators in 154-kV transmission lines is very challenging, owing to the complex aging process. As the first step of the life-time extrapolation, we characterized the failure types. Various factors such as temperature, rain, dust, acids, corrosion, vibrations, and mechanical and electrical stresses, over a long period of time can lead to various types of failures in porcelain insulators.

Voltage Distribution and Flashover Performance of 220 kV Composite Insulators under Different Icing Conditions

Composite insulators are widely used in modern power systems to provide electrical insulation and mechanical support for transmission lines and substations. However, the insulation strength will decrease greatly under the combined conditions of ice-covering and contamination, and icing flashovers may take place under these serious conditions. In this paper, AC flashover tests of different artificially ice-covered 220 kV composite insulators were carried out in a multi-function artificial climate chamber under energized ice accumulation conditions. The test results indicate that, with the increasing of ice thickness, the flashover voltages decrease and tend to saturation. The icing flashover voltages can be increased by adding booster sheds, but excessive booster sheds can lead to lower flashover voltages under heavy icing conditions. The voltage distributions of the iced insulators were measured using experimental methods. The results show that, the air gaps withstand most of the applied voltage. The zinc oxide (ZnO) resistors that are contained in the insulators can influence the voltage distributions of the iced insulators, but have little affect on the icing flashover voltages. The work done in this paper can provide reference for the design and type selection of outdoor composite insulators in cold climate regions.

Insulator Fault Detection Based on Spatial Morphological Features of Aerial Images

Because insulators provide electrical insulation and mechanical support for electric transmission lines, these components are of paramount importance to safe and reliable operations of power systems. However, insulators are often considered to be prone to different faults, e.g., bunch-drop, which demands a novel solution for accurate fault detection and fault location. Current research efforts have primarily focused on the bunch-drop fault of glass insulators, and the study of ceramic insulators has not been reported to date. To this end, this paper proposes an algorithmic solution for the bunch-drop fault detection for both glass and ceramic insulators based on spatial morphological features, which can be integrated into an unmanned aerial vehicle-based inspection system. Color models can be established based on the unique color features of both glass and ceramic insulators. Next, the target areas of the insulators can be identified according to the color determination combined with the insulator’s spatial features. The target area is morphologically processed to highlight the fault location, and the rules are established based on the spatial feature differences between the insulators with and without faults. Consequently, the fault location can be accurately identified, and the coordinates can be determined. The performance of the proposed solution is evaluated in comparison with existing solutions. The numerical results demonstrate that the proposed solution can detect the bunch-drop faults of insulators with a better than average detection rate. In addition, the performance is assessed and validated in terms of robustness and real-time performance.

The need of creating a new nominal creepage distance in accordance with heaviest pollution 500 kV overhead line insulators

Abstract The flashovers on insulators, caused by severe pollution, has posed the biggest threat on the safe operation of power systems the insulators contamination, and it is an important problem, special in polluted. The aperiodic occurrence of widespread contamination related outages cause serious damages to the transmission lines, the worst behavior is up to 500 kV overhead lines. The exceptional level of pollution measured on those insulators, especially for the bottom surface for the non-soluble salt deposit density (NSDD) component, where the values are outside of the standard limit given in the currently IEC standard. The results provide important reference for the insulators design, maintenance of operational transmission line insulators and flashover warnings. It should be highlighted that results fall out of the limit of the IEC standard and that in order to plot those values in the graph the limits for the highest NSDD values have been increased from 4 to 20 g/cm2. This clearly shows the unusually high values of the NSDD components measured on those insulators. The case study has been realized on 837,000 insulators for 9000 towers in 500 kV powers lines. This clearly shows the unusual characteristics of the coast and desert environment of the 500 kV overhead lines, and the needs of update in the IEC standards has been researched.

The discrimination method as applied to a deteriorated porcelain insulator used in transmission lines on the basis of a convolution neural network

Based on the analysis of the principle and structure of a convolutional neural network (CNN) model used for in-depth learning, an intelligent discriminant diagnosis method for porcelain fuselage insulators in transmission lines is proposed. Firstly, the infrared image of a porcelain insulator is extracted, and then Lenet is used to optimize the network structure. Finally, the model of fixed parameters is formed by training. The model has high classification and judgment robustness and offers accuracy under different conditions such as: temperature, humidity, position of deterioration on the insulator, and thermal load, which allows weight-sharing in the CNN model under different environmental conditions. Based on the experimental data from an infrared heating experiment using a porcelain deteriorated insulator, this work uses the back-propagation gradient descent method to train the model, to form an intelligent detection model for deteriorated insulators. This method has the advantages of high accuracy and robustness, and represents a new method for intelligent detection of deteriorated insulators.

Sensoring Leakage Current to Predict Pollution Levels to Improve Transmission Line Model via ANN

Pollution insulator is a serious threat to the safety operations of electric power systems. Leakage current detection is widely employed in transmission line insulators to assess pollution levels. This paper presents the prediction of pollution levels on insulators based on simulated leakage current and voltage in a transmission tower.The simulation parameters are based on improved transmission line model with leakage current resistance insertion between buses. Artificial neural network (ANN) is employed to predict the level of pollution with different locations of simulated leakage current and voltage between two buses. With a sufficient number of training, the test results showed a significant potential for pollution level prediction with more than 95% Correct Classification Rate (CCR) and output of the ANN showed high agreement with Simulink results.

Image Segmentation Method of Insulator in Transmission Line Based on Weighted Variable Fuzzy C-Means

Image Segmentation Method of Insulator in Transmission Line Based on Weighted Variable Fuzzy C-Means

A Random Forest Model Based Pollution Severity Classification Scheme of High Voltage Transmission Line Insulators

Tower insulators in electric power transmission network play a crucial role in preserving the reliability of the system. Electrical utilities frequently face the problem of flashover of insulators due to pollution deposition on their surface. Several research works based on leakage current (LC) measurement has been already carried out in developing diagnostic techniques for these insulators. Since the LC signal is highly intermittent in nature, estimation of pollution severity based on LC signal measurement over a short period of time will not produce accurate results. Reports on the measurement and analysis of LC signals over a long period of time is scanty. This paper attempts to use Random Forest (RF) classifier, which produces accurate results on large data bases, to analyze the pollution severity of high voltage tower insulators. Leakage current characteristics over a long period of time were measured in the laboratory on porcelain insulator. Pollution experiments were conducted at 11 kV AC voltage. Time domain analysis and wavelet transform technique were used to extract both basic features and histogram features of the LC signal. RF model was trained and tested with a variety of LC signals measured over a lengthy period of time and it is noticed that the proposed RF model based pollution severity classifier is efficient and will be helpful to electrical utilities for real time implementation.

System for monitoring partial discharges occurring in overhead power transmission line insulators based on ultraviolet radiation registration

System for monitoring partial discharges occurring in overhead power transmission line insulators based on ultraviolet radiation registration