Equivalent Salt Deposit Density Research Articles

Research on the prediction method of porcelain insulator pollution degree based on electric field monitoring

The online monitoring of insulator surface pollution states is crucial for predicting/preventing pollution flashover accidents. This paper conducts artificial pollution tests on porcelain insulators at five pollution levels to obtain the electric field signal during the flashover process. Subsequently, the time-frequency performance of the electric field signal waveform at various discharge stages is discussed in detail. Finally, a method for predicting pollution degrees by combining back propagation (BP) neural networks and non-contact electric field signal monitoring is proposed and validated. Research results indicate that during the pollution flashover process of the porcelain insulator, the peak value of the electric field signal shows an upward trend in sections. As the equivalent salt deposit density (ESDD) increases, the curves of electric field values rise. The development of dry-band arcing clearly distorts the electric field signal waveform at its crest and trough parts, increasing the total harmonic distortion (THD) rate. The THD can reach 100–130 % when closing to flashover, with the third harmonic acting as the main component. By taking kmax (the rising rate of the E-field signal amplitude), g (the ratio of Emax to Erms), K3 (the third harmonic coefficient), and THD as inputs to the BP neural network model, an ESDD prediction with a relative error lower than 10.63 % is realized. This research can offer novel technical support for predicting pollution degrees.

Simulation and experimental research on laser cleaning of glass insulators

The pollution flashover of glass insulators can be effectively mitigated through regular or irregular cleaning. However, the existing cleaning methods are difficult to popularize on a large scale due to labour intensive, high cost or low safety. The effectiveness and safety of laser cleaning on glass insulators has been analyzed in this paper. A number of artificial contaminated and clean glass insulators are tested. By measuring the equivalent salt deposit density (ESDD) and the non-soluble deposit density (NSDD) before and after cleaning, laser cleaning can reduce both of them to different degrees. The main factors affecting the maximum temperature of the contamination layer include the class of pollution, laser power and scanning velocity during laser cleaning. When addressing pollution levels above class b, by employing a laser scanning velocity of 8 m/s and adjusting the laser power within the range of 80–200 W, the pollution class after laser cleaning reduces effectively to class b or lower. To verify the safety of laser cleaning, simulations and experimental analyses are carried out. The result demonstrates that sufficient safety can be satisfied when laser cleaning is applied to clean glass insulators.

Analysis of Natural Pollution Accumulation Characteristics of Insulators for Railroads in High-Altitude Environment

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.

Visual characterization of pollution and moisture parameters of the polluted HTV silicone rubber surface with hyperspectral imaging technology

The application of high temperature vulcanized (HTV) silicone rubber materials in transmission lines insulators has been extensive. However, with the accumulation of pollution and moisture on the surface of HTV silicone rubber, the insulation reliability gradually decreases, which may even lead to flashover. In this paper, hyperspectral imaging technology is utilized as a rapid and effective tool for the visual characterization of pollution and moisture parameters of the polluted HTV silicone rubber. Based on the analysis of reflection spectra, it has been determined that the pollution degree has a positive effect and the moisture content has a negative effect on the reflection characteristics of HTV silicone rubber, respectively. Further quantitative analysis of reflectance values at various moisture conditions reveals that exponential relationships can be observed between reflectance values and moisture contents at a certain wavelength. At the same time, linear correlations between reflectance values and pollution degrees (quantified as equivalent salt deposit density (ESDD)) at a certain wavelength are also proposed. By integrating the exponential and linear relationships, a double-exponential model is formulated to concurrently characterize the ESDD and moisture content (MC). Furtherly, from the perspective of engineering application, to enhance the model’s robustness, a set of equations combining spectral indexes and spectral shape feature parameters is initially formulated for the calculating of ESDD and MC. Given the synchronous inversion and visualization capabilities of pollution and moisture parameters of the polluted HTV silicone rubber surface, the visual characterization model serves as a valuable tool for protecting against pollution flashover failures and designing power equipment insulation.

Predicting the Class of Salt Contamination for Wind Turbine Blade under a Lightning Strike Using Fuzzy Inference System and Probabilistic Neural Network

This study predicts the class of salt contamination for wind turbine blades that undergo a lightning strike using a fuzzy inference system (FIS) and a probabilistic neural network (PNN). The experiment uses four classes of equivalent salt deposit density to determine the salt contamination status for a wind turbine blade. The greatest degree of salt contamination is 338.9 µg/cm2. The rotational speeds of the blades are set as 0, 50, 100, and 150 rpm. Many lightning strike surge experiments are conducted for different types of salt-contaminated blades. The lightning current signals in the grounding line are measured using a high-frequency current transformer. This study uses an experimental method to determine the effect of salt contamination on wind turbine blades during lightning strikes. In terms of prediction, FIS and PNN are used to predict the four classes of salt contamination. The peak absolute value and the average power of the measured signals are the input datasets for the FIS and the PNN. The predictions for the ESDD classes are 94.8% for a FIS and 88.8% accurate for a PNN. The research results show that the proposed method accurately predicts the salt contamination class for wind turbine blades.

The Characteristic Analysis of ESDD and NSDD Detection of Composite Insulators Based on Hyperspectral Technology

Pollution flashover of insulators has been viewed as a common issue existing in the area of power systems for a long term. However, traditional detection methods such as equivalent salt density and leakage current (LC) can hardly satisfy the requirements of the progressing smart grid. Herein, a novel highly-efficient method is proposed for classifying the pollution degree detection of insulators based on hyperspectral technology. The insulating sheets and actual insulators were set as the research object and their hyperspectral images are obtained. Moreover, the data for describing the characteristic wavelengths and the G color components of the samples were extracted from the images as the characterization of the equivalent salt deposit density (ESDD) and nonsoluble deposit density (NSDD) respectively. The ESDD and NSDD detection model is established based on the multiple linear regression (MLR) algorithm and the random forest (RF) algorithm. Ultimately, the proposed model reaches a detection accuracy of above 84% on the insulating sheets and 75% on the actual insulators, which can be viewed as acceptable. The hyperspectral imaging technique has considerable potential for the non-contact detection of ESDD and NSDD.

<b>Method for Estimating Equivalent Salt Deposit Density on Insulator Surfaces Using Meteorological and Topographical Information Provided by Public Institutions</b>

Traditionally, the design and maintenance of electric power facilities of electric railways in bay areas have been carried out according to a uniform classification of pollution based on distance from the coast and other factors. In order to improve the safety of these facilities and save labor for maintenance, it is necessary to subdivide this uniform classification according to the actual pollution situation. Therefore, we propose a method for estimating the Equivalent Salt Deposit Density on insulator surfaces at any point on an open section using meteorological and topographical information provided by public institutions.

A Study of the Cleansing Effect of Precipitation and Wind on Polluted Outdoor High Voltage Glass Cap and Pin Insulator

In this work, the extent of natural cleansing effect of rainfall, wind and fog or a combination of these on an insulator string were investigated. Results showed that pollution losses progress with time, with a considerable fraction of losses occurring within 15 minutes of testing. While wind alone played little or no role in surface cleansing, it increases the extent of cleansing by rainfall. The topsides of insulators were found to be more affected by natural cleansing compared to the underside. Equivalent Salt Deposit Density (ESDD) and Non-Soluble Deposit Density (NSDD) measurements were carried out. ESDD was found to be higher in the lower disc irrespective of the weather condition the insulator string has been subjected to. NSDD measurements established no pattern on how natural cleansing was impacted by disc position on a string, demonstrating the random nature of pollution-cleansing cycle of outdoor insulators. Insulator performance was assessed by high voltage AC tests and monitoring of partial discharge events using Radio Frequency antennas and a High Frequency Current Transformer (HFCT). Measured output by the HFCT showed that leakage current decreases uniformly with time, and the speed at which this occurs is an indication of the intensity of natural cleansing activity.

Numerical Analysis and Experimental Study of the Laser Cleaning of Ceramic Insulator Contamination

Contamination flashover of insulators is one of the main threats to the safety of power systems, and regular cleaning of insulator surface pollution is an effective solution to this problem. In this paper, the laser cleaning of ceramic insulators is studied via simulations and experiments. The adhesion between a contamination layer and an insulator surface is estimated. A laser cleaning model for contaminated insulators is established, and a numerical analysis of the thermal stress field distribution characteristics of laser cleaning is carried out. Various factors that affect the thermal stress field distribution, including the laser power, laser scanning speed and thickness of the contamination layer, are also analysed. The optimal cleaning parameters for the best performance of laser cleaning are obtained through simulation and experiments. The result shows if the equivalent salt deposit density (ESDD) is 0.05 mg/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , and the nonsoluble deposit density (NSDD) is 0.25 mg/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , the best cleaning effect could be achieved when the laser power is 100 W and the scanning speed reached 6000 mm/s.

Prediction of Dielectric Breakdown of OHTL Insulators Using Contact Angle Measurements

Porcelain insulators used in overhead transmission lines (OHTL) are exposed to pollution when operational. To observe the effect of external pollution on these insulators, the relationship between the flashover voltage and surface contamination was studied. The flashover voltage drops sharply when contaminants in the wind are deposited on the surface of the insulators in a humid environment. Under wet conditions, the flashover voltage demonstrates a difference of approximately 10 kV depending on the contamination levels. The higher the equivalent salt deposit density, the lower the contact angle. In particular, the flashover voltage under wet conditions decreases exponentially when the contact angle is below 30°. In this case, the condensation area becomes considerably wider, thus exhibiting the difference in the area of the electrolytic conductive film layer forming the leakage path on the surface. Depending on the equivalent salt deposit density and contact angle, the area of condensation is more than doubled. To measure the level of contamination on the surface using this principle, a contact angle measurement method was adopted to predict the dielectric breakdown of the insulator.

Electric Field Distribution and AC Breakdown Characteristics of Polluted Novel Lightning Protection Insulator under Icing Conditions

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. Uf 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.

Experimental study of porcelain and toughened glass suspension insulators under desert contamination

In this paper, the performance of porcelain and toughened glass suspension insulators artificially polluted with desert contamination is investigated experimentally. The withstand flashover voltage (FOV), and equivalent salt deposit density (ESDD) of desert contaminated insulators have been studied and reported. Artificial pollution testing was carried out, and desert contaminations were prepared in advance for four solutions (NaCl, CaSO4, KCl, and CaO) of different concentration levels to investigate the influence of desert contamination on the insulators of transmission lines. The flashover analyses are completed on 11 kV insulators with artificial pollution coatings. The contaminations materials are (a) Desert Salt Pollution-Dry pollution (b) Natural Fog Condition. Results have proven that flashover voltage decreased with the increase in the dry dessert pollution level at constant pressure and temperature condition. However, the study has also revealed that in the case of natural fog conditions, the flashover voltage of porcelain and toughened glass disc insulator became much lower than the dry test. From the results, it can be detected that engineers can predict and plan for the maintenance schedule of the poor performance of the insulators under different effluence environmental conditions. The study tested the effect of AC voltage flashover on the suspension insulators. However, the DC voltage is suggested to be used and results to be compared with the current study.

Study on Fast Contamination Characteristics of Cap and Pin Insulators in Straight Flow Wind Tunnel Simulation

Artificial simulation of rapid insulator contamination can obtain the contamination characteristics of suspension insulators in a short time, providing important reference for the electrical design, operation and maintenance of external insulation. To obtain the contamination characteristics of insulators closer to those under the natural environment, this paper proposed a test method for artificial simulation of rapid natural contamination of insulators using the characteristic parameters of straight-flow wind tunnel, and carried out the artificial rapid natural contamination test of cap and pin insulators under different wind speeds, wind directions, contamination duration and contaminant concentrations. The test results showed that with the wind speed increasing from 2.2 m/s to 7.5 m/s, the contamination degree of insulator surface gradually increased firstly and then decreased, and reached the maximum near 4.5 m/s. With the increase in contaminant concentration, the contamination degree of insulator surface increased, and tended to be saturated when the dust spreading speed was 54 g/min. With the extension of contamination duration, the contaminant accumulation on insulator surface was slow in the initial stage, accelerated in the middle stage, and then slowed down and gradually saturated in the later stage. Under the same contamination conditions, standard, double-shed and triple-shed insulators presented high-to-low equivalent salt deposit density (ESDD) successively on their top and bottom surfaces, and the ratios of ESDD on the top and bottom surfaces were 1:1.20:0.9 and 1:0.63:0.53, respectively.

Experimental-based models for predicting the flashover voltage of polluted SiR insulators using leakage current characteristics

This study aims to predict the flashover voltage (FOV) of silicone rubber (SiR) insulators. Accordingly, it benefits from two methods, including an artificial neural network (ANN) model and a FOV gradient fitting model. The FOV and leakage current (LC) tests are carried out on one un-aged and three aged specimens under uniform and longitudinal non-uniform pollution circumstances. The proposed ANN model is designed based on equivalent salt deposit density (ESDD), pollution non-uniformity degree, aging time, LC first harmonic magnitude I 1 , and total harmonic distortion. Furthermore, a FOV gradient model is proposed based on ESDD, I 1 , and creepage distance. To validate the proposed models, the FOV and LC tests are conducted on two different types of SiR insulators. Then, the predicted FOV from the ANN model and calculated FOV from the voltage gradient model are obtained. The results indicate that the relative errors of the ANN model and FOV gradient fitting model are &lt;6.4 and 7.3%, respectively.

The failure arc paths of the novel device combining an arrester and an insulator under different pollution levels

Lightning strokes on transmission lines could trigger insulation failure if no protective measures are taken. Typically, a lightning arrester is used for this purpose. In order to combine the insulator and the lightning arrester as a single entity, a novel lightning protection composite insulator, combining an arrester and an insulator was developed for 10 kV distribution lines. Studied in this paper are the various arc paths of the novel insulator. The arc path tests under both AC and impulse voltage were conducted. The findings indicate that low, medium, high, very high, and extremely heavy pollutions caused different types of arcings under AC voltage. In addition, arc paths were affected by both the pollution level and the magnitude of impulse voltage. Based on the arc paths recorded by a high-speed camera, the flashover modes can be divided into three categories (flashover of the air gap, flashover of silicone rubber sheds in insulation section, and flashover of the whole insulator). More specifically, we defined and analyzed 14 types of arc paths in detail, and the critical pollution level (0.1 mg/cm2) of normal operation were obtained. Further, the statistical probability of each arc under impulse voltage was calculated. Due to the complexity of the arc paths under the switching impulse voltage, a 90% probability distribution figure of arc paths with different Us (switching impulse voltage) and ESDD (equivalent salt deposit density) was presented according to the test results. At last, we discuss the impulse voltage waveform corresponding to the typical arc path and describe the research prospect. The research results in this paper present the failure modes of the novel lightning protection insulator, and the results can be used for designing insulators for various pollution levels.

Characterisation parameter of atmospheric pollutant concentration for external insulation

Currently, the equivalent salt deposit density (ESDD) is adopted to characterise the pollution degree and many environmental pollution parameters are used to characterise air pollution. However, the relationships between ESDD and environmental pollution parameters are not clear. For the purpose of studying the influence of environmental factors such as haze-fog, high-conductivity fog on the insulators contamination and the equivalence between artificial salt fog and natural highly conductive pollutions, a parameter named equivalent soluble salt concentration (ESSC) was proposed to measure the soluble salt amount of the atmospheric air in this study. Based on the measuring principle, an ESSC measurement platform was developed. The developed platform was tested in the laboratory and used to measure the ESSC in the field. According to the experimental results, it was found that the soluble components deposited on the specimen surface in the field are the same as that in the atmospheric air nearby. As the pollution deposition is an accumulative process, it is expected that combined with ESDD, the ESSC can be used to predict the ESDD, which would be of significance to study the accumulated mechanism of insulator contamination, as well as to the external insulation design.

Lessons to Learn from Post-Installation Pollution Levels Assessment of Some Distribution Insulators

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!

Forecasting Flashover Parameters of Polymeric Insulators under Contaminated Conditions Using the Machine Learning Technique

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.

Impact of sugar factory pollutants on the insulators’ impurity

This paper presents the impact of pollutants on the impurity of substation insulator around the sugar factory. We have conducted experiment and calculated the equivalent salt deposit density (ESDD) to determine pollutant’s level, which measure the conductivity of pollutants in insulators. Then synchronized with the weight of NaCl, so the conductivity is the same as the conductivity of pollutants. The results of experimental data from pollutants attached to the polymer isolator are in the medium category, with a value of 0.37 mg/cm2.

Contamination deposition and discharge characteristics of outdoor insulators in fog-haze conditions

This investigation focuses on the fog-haze weather, a new threat to the outdoor insulators in many developing countries, and the effects of adhesive properties of particles on surface discharge of outdoor insulators in fog-haze conditions. In a fog-haze chamber to simulate the fog-haze condition, the adhesive properties of haze particles and the leakage current and flashover voltage were analysed with different fog-haze parameters. It was found that with the increasing duration of fog-haze and the fog conductivity the equivalent salt deposit density (ESDD) and the leakage current increased and the flashover voltage decreased. This investigation focuses on the dynamic process of ice accretion and induced surface discharges along a suspension insulator string in relation with the icicle characteristics in icing conditions, especially with the increase in the conductive and soluble components. The obtain results will be beneficial to improve the operating reliability of outdoor insulator in power system in fog-haze conditions.