Search Results (15)

This paper presents a simple thermoelectrical temporal surface method for numerically studying the appearance of a dry band on a polluted insulator. The proposed method combines an empirical expression of the pollution layer surface conductivity, expressed as a function of the temperature and equivalent salt deposit density (ESDD), and a surface approach for modeling the pollution layer, using thermoelectrical temporal simulations based on the finite element method (FEM). Using different material substrates, pollution layer thicknesses, and ESDD levels, the reliability and limitations of the simple thermoelectrical numerical model have been studied. The numerical results obtained demonstrated that the proposed thermoelectrical model can dynamically simulate the dry band appearance in accordance with the experimental results in terms of the temporal evolution of the temperature and the pollution layer resistance, as well as the evolution of the voltage drop and E-field along the dry band formation zone. The results also demonstrate the influence of the material substrate and the pollution layer thickness, which directly influence the thermal aspect of the dry band formation. The simple thermoelectrical numerical surface model was used to study the dry band appearance on a uniformly polluted 69 kV insulator. The results obtained enabled a dynamic simulation of the appearance of the first dry band, which appeared in the middle of the insulator, and to deeply investigate the evolution of the surface temperature, electric potential, and E-field distributions along the insulator. The proposed simple thermoelectrical model combined with the empirical model is able to simulate the influence of a non-uniform pollution layer. Hence, the proposed model provides a simple numerical tool for studying the evolution of the potential and E-field distributions along uniformly and non-uniformly polluted insulation equipment to identify the probability of a region of high dry band appearance relative to the insulator material and geometry. This can aid in the development of new types of mitigation methods to improve the performance of all types of insulators under polluted conditions. Full article

Railway system insulators are affected by pollution, altitude, and other environmental situations during operation, which causes reduced electrical performance or even flashover accidents. These factors threaten the safety of railway operations in high-altitude areas. However, the natural contamination characteristics of a railroad in a plateau area is still unclear. In this study, a natural pollution accumulation test for railway insulators in a high-altitude area was carried out, and the distribution rules of nonsoluble deposit density (NSDD), equivalent salt deposit density (ESDD), NSDD/ESDD ratio, and nonuniformity (T/B) of the pollution distribution of the tested insulators were calculated. Meanwhile, the chemical compositions of the pollution from different test sites were analyzed. The differences of pollution accumulation between railway insulators and suspended insulators of a power system and the influencing factors were compared and analyzed by combining with a numerical simulation. The results show that the pollution level of railroad insulators is mainly distributed in level b and above. A pollution sample is mainly composed of sodium chloride, while the NSDD/ESDD ratio of pollution is mostly distributed from 0 to 5, with T/B value ranges from 1/0.62 to 1/1.76. The amount of insulator contamination is influenced by the location inside and outside the tunnel. Additionally, the pollution amount is influenced by the structure and type of insulators. Finally, this paper studies the creepage distance and structural height required by railway insulators in a plateau area according to the natural pollution accumulation characteristics of railway insulators, which can provide a reference for a railway electrical external insulation configuration in a high-altitude area. Full article

Polymer is an insulating substance that has become increasingly popular in recent years due to its benefits. Light density, superior dielectric and thermal properties, and water-resistant or hydrophobic properties are only a few of the benefits. The presence of impurities or pollutants on the insulator’s surface lowers its dielectric capacity, which can lead to current leakage. The influence of seawater and fly ash pollutants on the distribution of the electric field and the current density of the insulator was simulated in this study. The finite element method was used to execute the simulation (FEM). Polymer insulators are subjected to testing in order to gather current leakage statistics. The tested insulator is exposed to seawater pollution, which varies depending on the equivalent salt density deposit value (ESDD). The pollutant insulator for fly ash varies depending on the value of non-soluble deposit density (NSDD). The existence of a layer of pollutants increased the value of the electric field and the value of the surface current density, according to the findings. Both in simulation and testing, the ESDD value of seawater pollutants and the NSDD value of fly ash contaminants influenced the value of the leakage current that flowed. The greater the ESDD and NSDD values are, the bigger the leakage current will be. Full article

As a result of lightning strikes, pollution, and ice, overhead distribution wires might be short-circuited and trip. As a result, researchers have developed a new lightning protection composite insulator. There is still a need to test its pollution and icing performance. Based on the finite element and field test method, this paper studies the electric field distribution and AC (Alternating Current) breakdown characteristics of polluted novel lightning protection insulators under icing conditions. Firstly, the finite element calculated results show that this novel insulator’s electric field distribution is different from that of a conventional insulator. The locations with sizeable electric fields are located in the insulation section, and the electric field in the arrester section is tiny. In addition, when the insulator surface is covered with ice, there is an increase in the electric field along the surface and pin electrodes. Compared with the dry conditions, when there is an ice layer and icicle, electric field peaks increase by 48.85% and 46.08%, respectively. Secondly, the test results show that there are three types of arc paths in different pollution levels. The arc paths are related to ESDD (equivalent salt deposit density) under icing conditions. U_f shows a downward trend with increased pollution levels, and the maximum flashover voltage is 2.70 times more than the minimum. Finally, four fitting methods are proposed in this paper. After comparing the goodness of fit of different functions, the quadratic function and negative power function with the constant term are recommended as empirical formulas for calculating flashover voltage of novel insulators under icing conditions in different pollution levels. The research results of this paper have a specific guiding role for the selection of the external insulation of transmission lines and structural optimization of novel insulators. Full article

Among the main causes of outdoor insulation failures is their poor specifications in terms of leakage distances. This happens when the selected criteria are unable to cope with all the stresses imposed by the changes in environmental pollutions. Therefore, it is important for utilities to fully understand the actual pollution characteristics of the service environment in which the insulators are operating. In this paper, the pollution severity and performance of some 13.2 kV ceramic insulators, sampled in different areas of a Canadian aluminum factory, are assessed. The investigations were performed taking into account the influence of air humidity. Various characteristics were investigated to assess the pollution levels of the insulators, such as equivalent salt deposit density (ESDD) and non-soluble deposit density (NSDD), surface resistance, and leakage current characteristics (density, 3rd harmonic amplitude, and phase). It was witnessed that the insulators, collected around the factory, were much more polluted in comparison to the initial expectation. The pollution level should not be considered static due to the environmental parameters’ dynamics. Lessons to learn: the reliability of an electrical grid is dependent on components whose own reliability is strongly affected by external factors, of which there is often a poor awareness. If care is not taken to re-evaluate the post-installation pollution levels of the insulators, the light may simply turn out! Full article

There is a vital need to understand the flashover process of polymeric insulators for safe and reliable power system operation. This paper provides a rigorous investigation of forecasting the flashover parameters of High Temperature Vulcanized (HTV) silicone rubber based on environmental and polluted conditions using machine learning. The modified solid layer method based on the IEC 60507 standard was utilised to prepare samples in the laboratory. The effect of various factors including Equivalent Salt Deposit Density (ESDD), Non-soluble Salt Deposit Density (NSDD), relative humidity and ambient temperature, were investigated on arc inception voltage, flashover voltage and surface resistance. The experimental results were utilised to engineer a machine learning based intelligent system for predicting the aforementioned flashover parameters. A number of machine learning algorithms such as Artificial Neural Network (ANN), Polynomial Support Vector Machine (PSVM), Gaussian SVM (GSVM), Decision Tree (DT) and Least-Squares Boosting Ensemble (LSBE) were explored in forecasting of the flashover parameters. The prediction accuracy of the model was validated with a number of error cost functions, such as Root Mean Squared Error (RMSE), Normalized RMSE (NRMSE), Mean Absolute Percentage Error (MAPE) and R. For improved prediction accuracy, bootstrapping was used to increase the sample space. The proposed PSVM technique demonstrated the best performance accuracy compared to other machine learning models. The presented machine learning model provides promising results and demonstrates highly accurate prediction of the arc inception voltage, flashover voltage and surface resistance of silicone rubber insulators in various contaminated and humid conditions. Full article

Surface pollution deposition in a high voltage surface can reduce the surface flashover voltage, which is considered to be a serious accident in the transmission of electric power for the high conductivity of pollution in wet weather, such as rain or fog. Accordingly, a rapid and accurate online pollution detection method is of great importance for monitoring the safe status of transmission lines. Usually, to detect the equivalent salt deposit density (ESDD) and non-soluble deposit density (NSDD), the pollution should be collected when power cut off and bring back to lab, time-consuming, low accuracy and unable to meet the online detection. Laser-induced breakdown spectroscopy (LIBS) shows the highest potential for achieving online pollution detection, but its application in high voltage electrical engineering has only just begun to be examined. In this study, a LIBS method for quantitatively detecting the compositions of pollutions on the insulators was investigated, and the spectral characteristics of a natural pollution sample were examined. The energy spectra and LIBS analysis results were compared. LIBS was shown to detect pollution elements that were not detected by conventional energy spectroscopy and had an improved capacity to determine pollution composition. Furthermore, the effects of parameters, such as laser energy intensity and delay time, were investigated for artificial pollutions. Increasing the laser energy intensity and selecting a suitable delay time could enhance the precision and relative spectral intensities of the elements. Additionally, reducing the particle size and increasing the density achieved the same results. Full article

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. Full article

High-voltage bushings play a crucial role in energy conveyance. Their specialized electric structure makes the bushing more vulnerable to surface discharge. However, the influence of a vertical electric field on the surface flashover of bushing structures remains unclear. To investigate this mechanism, four simplified bushing samples were built and the influence of pollution, leakage length, and the electric field component vertical to the dielectric surface on flashover properties of the bushing samples were tested. It was found that the surface pollution level was the decisive factor that influenced flashover voltage. When the leakage length and form factor were the same, the pollution flashover of the bushing structure was lower than that of the post structure. It was also found that increasing the leakage length was not very effective in improving the flashover voltage of bushings when the equivalent salt deposit density (ESDD) was high. No obvious correlation was found between pollution flashover voltage and electric field stress. Furthermore, the uneven wetting flashover performance of the bushings was tested. Under this condition, the flashover voltage decreased with an increase of the electric field component vertical to the dielectric surface. In addition, the electric field distribution of the samples was calculated and the results were in accordance with the experimental results. Full article

Anti-pollution flashover of insulator is important for power systems. In recent years, haze-fog weather occurs frequently, which makes discharge occurs easily on the insulator surface and accelerates insulation aging of insulator. In order to study the influence of haze-fog on the surface discharge of room temperature vulcanized silicone rubber, an artificial haze-fog lab was established. Based on four consecutive years of insulator contamination accumulation and atmospheric sampling in haze-fog environment, the contamination configuration appropriate for RTV-coated surface discharge test under simulation environment of haze-fog was put forward. ANSYS Maxwell was used to analyze the influence of room temperature vulcanized silicone rubber surface attachments on electric field distribution. The changes of droplet on the polluted room temperature vulcanized silicone rubber surface and the corresponding surface flashover voltage under alternating current (AC), direct current (DC) positive polar (+), and DC negative polar (−) power source were recorded by a high speed camera. The results are as follows: The main ion components from haze-fog atmospheric particles are NO₃⁻, SO₄²⁻, NH₄⁺, and Ca²⁺. In haze-fog environment, both the equivalent salt deposit density (ESDD) and non-soluble deposit density (NSDD) of insulators are higher than that under general environment. The amount of large particles on the AC transmission line is greater than that of the DC transmission line. The influence of DC polarity power source on the distribution of contamination particle size is not significant. After the deposition of haze-fog, the local conductivity of the room temperature vulcanized silicone rubber surface increased, which caused the flashover voltage reduce. Discharge is liable to occur at the triple junction point of droplet, air, and room temperature vulcanized silicone rubber surface. After the deformation or movement of droplets, a new triple junction point would be formed, which would seriously reduce the dielectric strength of room temperature vulcanized silicone rubber. Full article

Equivalent salt deposit density (ESDD) and non-soluble deposit density (NSDD) measurements are a basic requirement of power systems. In order to predict the site pollution severity (SPS) of insulators, a new method based on random forests (RFs) is proposed. Using mutual information (MI) theory and RFs, the weights of factors related to the SPS of insulators are analyzed. The samples of contaminated insulators are extracted from the transmission lines of high voltage alternating current (HVAC) and high voltage direct current transmission (HVDC). The regression models of RFs and support vector machines (SVM) are constructed and compared, which helps to support the lack of information in predicting NSDD in previous works. The results are as follows: according to the mean decrease accuracy (MDA), mean decrease Gini, (MDG), and MI, the types of the insulators (including surface area, surface orientation, and total length) as well as the hydrophobicity are the main factors affecting both ESDD and NSDD. Compared with NSDD, the electrical parameters have a significant effect on ESDD. For the influence factors of ESDD, the weights of the insulator type, hydrophobicity, and meteorological factors are 52.94%, 6.35%, and 21.88%, respectively. For the influence factors of NSDD, the weights of the insulator type, hydrophobicity, and meteorological factors are 55.37%, 11.04%, and 14.26%, respectively. The influence voltage level (vl), voltage type (vt), polarity/phases (pp) exerted on ESDD are 1.5 times, 3 times, and 4.5 times of NSDD, respectively. The influence that distance from the coastline (d), wind velocity (wv), and rainfall (rf) exert on NSDD are 1.5 times, 2 times, and 2.5 times that of ESDD, respectively. Compared with the natural contamination test and the SVM regression model, the RFs regression model can effectively predict the contamination degree of insulators, and the relative error of the predicted ESDD and NSDD is 8.31% and 9.62%, respectively. Full article

The cleaning effect of heavy rain (the rainfall reaches 5 mm every day) on surface contamination of insulators is more effective than dew, fog, mist, and other light rain conditions which can initiate leakage currents and increase the likelihood of flashover. It is well understood that heavy rain can wash away contamination from the surface of high voltage (HV) insulators and thereby reduce the risk of pollution flashover. This study examines the cleaning effect of natural wetting conditions on HV insulators on four 500 kV transmission lines in Hunan Province, China. Historical meteorological data, monthly equivalent salt deposit density (ESDD) and non-soluble deposit density (NSDD) measurements taken over a period of five years were analyzed to investigate the relationship between rainfall intensity and insulator cleaning. The measured data show that the ESDD/NSDD changes with the seasonal variation, which accumulates in dry season (January–April, about 117–122 days) and is washed off in the wet season (June–October, about 118–127 days). According to the measured data, the ESDD and NSDD on the surface of insulators were affected by the rainfall intensity (in the dry season it is about 1 mm/day and in the wet season it is about 5 mm/day). Based on a comparison of the four study sites, we propose a mathematical model to show the functional relationship between rainfall intensity and insulator self-cleaning capability. The mathematical model’s coefficient of determination (R²) is greater than 0.9 and the effective rate of self-cleaning capability reaches 80%. Full article

Natural polluted insulator surfaces are always coated with various kinds of soluble constituents, and those constituents affect flashover performance differentially. Currently, this fact is not considered either in laboratory experiments or field pollution degree measurements, causing the existing insulation selection method to be deficient. In this paper, a systematic study on insulator flashover voltage gradient correction involving different types of soluble pollution constituents is presented. Using a typical type glass insulator as the sample, its flashover tests, polluted by typical soluble chemicals (NaCl, NaNO₃, KNO₃, NH₄NO₃, MgSO₄, Ca(NO₃)₂ and CaSO₄), were carried out. Then, the flashover gradient correction was made by combining the flashover performance of each soluble constituent, the equivalent salt deposit density (ESDD) contribution of the seven constituents, and the saturation performance of CaSO₄. The correction agreed with the flashover test results of insulator polluted by three types of soluble mixture. Research results indicate that the flashover gradient correction method proposed in this paper performs well in reducing the calculating error. It is recommended to carry out component measurements and flashover gradient correction to better select outdoor insulation configuration. Full article

Silicone rubber insulators are replacing the conventional ceramic and porcelain insulators rapidly in power transmission and distribution industry. Very limited field knowledge is available about the performance of silicone rubber insulators in polluted and contaminated environments and therefore need further investigation. A comprehensive analysis of silicone rubber sheets (intended for coating outdoor insulators) was carried out in this paper based on experimental results. The main performance parameters analyzed were arc inception voltage and flashover voltage. Dependence of these parameters on equivalent salt deposit density (ESDD), non-soluble salt deposit density (NSDD), relative humidity, ambient temperature, fog rate, dry band formation, dry band location and number of dry bands were investigated extensively. Insulator orientation and its effect on performance were also studied. The authors believe that this paper will provide a comprehensive knowledge about the flashover characteristics of silicone rubber insulators under humid, contaminated and dry band conditions. These results could be used in the selection and design of silicone rubber insulators for polluted environments. Full article

The accurate estimation of deposits adhering on insulators is of great significance to prevent pollution flashovers which cause huge costs worldwide. Researchers have developed sensors using different technologies to monitor insulator contamination on a fine time scale. However, there is lack of analysis of these data to reveal spatial and temporal characteristics of insulator contamination, and as a result the scheduling of periodical maintenance of power facilities is highly dependent on personal experience. Owing to the deployment of novel sensors, daily Equivalent Salt Deposit Density (ESDD) observations of over two years were collected and analyzed for the first time. Results from 16 sites distributed in four regions of Hubei demonstrated that spatial heterogeneity can be seen at both the fine and coarse geographical scales, suggesting that current polluted area maps are necessary but are not sufficient conditions to guide the maintenance of power facilities. Both the local emission and the regional air pollution condition exert evident influences on deposit accumulation. A relationship between ESDD and PM₁₀ was revealed by using regression analysis, proving that air pollution exerts influence on pollution accumulations on insulators. Moreover, the seasonality of ESDD was discovered for the first time by means of time series analysis, which could help engineers select appropriate times to clean the contamination. Besides, the trend component shows that the ESDD increases in a negative exponential fashion with the accumulation date (ESDD = a − b × exp(−time)) at a long time scale in real environments. Full article