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.

Reducing the Nursery Pesticide Footprint with Laser-guided, Variable-rate Spray Application Technology

Nursery producers are challenged with growing a wide range of species with little to no detectable damage from insects or diseases. Growing plants that meet consumer demand for aesthetics has traditionally meant routine pesticide application using the most time-efficient method possible, an air-blast sprayer, despite its known poor pesticide application efficiency. New variable-rate spray technology allows growers to make more targeted applications and reduce off-target pesticide loss. In this study, a prototype laser-guided variable-rate sprayer was compared with a traditional air-blast sprayer. Pesticide volume, spray application characteristics, and the control of powdery mildew were evaluated over the course of two growing seasons. Spray application characteristics were assessed using water-sensitive cards (WSCs) and DepositScan software. This prototype sprayer reduced pesticide volume by an average of 54% across both years despite being tested against a low rate (<250 L⋅ha−1). In 2016, the conventional sprayer had more than double the deposit density on target WSCs among distal trees than the variable-rate sprayer; however, within proximal trees, there was no difference between the two sprayer types. In 2017, when the trees were larger, within both the distal and proximal trees, the conventional sprayer had greater deposit density on target WSCs than the variable-rate sprayer. In 2016, coverage on target WSCs was nearly 7-fold greater with the conventional treatment than with the variable-rate treatment. In 2017, when trees were larger, there was greater coverage on target WSCs in proximal trees (3.8%) compared with those in distal trees (1.0%) regardless of the sprayer type. This variable-rate spray technology provided acceptable control of powdery mildew severity on individual branches and whole trees and maintained the incidence of powdery mildew to levels comparable to that occurring among trees sprayed with a traditional air-blast sprayer. Therefore, the variable-rate spray technology has the potential to effectively control disease, dramatically reduce the pesticide footprint, and preserve natural resources such as ground and surface water, soil, and beneficial insects found within and around nurseries.

Advancing Sustainability in Tree Crop Pest Management: Refining Spray Application Rate with a Laser-guided Variable-rate Sprayer in Apple Orchards

Advanced variable-rate spray technology, which applies pesticides based on real-time scanning laser rangefinder measurements of plant presence, size, and density, was developed and retrofitted to existing sprayers. Experiments were conducted to characterize the application of four programmed spray rates (0.03, 0.05, 0.07, or 0.09 L·m−3 of crop geometric volume) when applied to Malus domestica Borkh. ‘Golden Delicious’ apple trees using this crop sensing technology. Water-sensitive cards (WSCs) were used as samplers to quantify spray coverage, deposits, and deposit density in the target and nontarget areas, and an overspray index based on a threshold of greater than 30% coverage was calculated. The application rate ranged from 262 L·ha−1 at the programmed spray rate of 0.03 L·m−3 to 638 L·ha−1 at the rate of 0.09 L·m−3. For a given WSC position, spray coverage and deposits increased as the spray rate increased. WSC positions 1 and 2 were oversprayed at all rates. The effect of spray rate on deposit density varied with WSC positions, with high densities achieved by low spray rates for WSCs closest to the sprayer but by high spray rates for WSCs positioned either deeper within or under the canopy. When coalescing deposits were accounted for, deposit densities met or exceeded the recommended pesticide application thresholds (insecticides 20–30 droplets/cm2; fungicides 50–70 droplets/cm2) at all WSC positions for each spray rate tested. The lowest spray rate reduced off-target loss to the orchard floor by 81% compared with the highest rate, dramatically reducing potential exposure to nontarget organisms, such as foraging pollinators, to come into contact with pesticide residues. Applying the lowest rate of 0.03 L·m−3 met deposit density efficacy levels while reducing spray volume by 83% compared with the orchard standard application of 1540 L·ha−1 and by 87% compared with the 1950 L·ha−1 application rate recommended when using the tree row volume method. Thus, there is potential for growers to refine pesticide application rates to further achieve significant pesticide cost savings. Producers of other woody crops, such as nursery, citrus, and grapes, who use air-assisted sprayers, may be able to achieve similar savings by refining pesticide applications through the use of laser rangefinder-based spray application technology.

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.

An alternative approaches to predict flashover voltage on polluted outdoor insulators using artificial intelligence techniques

This paper presents an alternative approach for predicting critical voltage of pollution flashover by using Artificial Intelligence (AI) technique. Data from experimental works combined with the theoretical results from well-known theoretical modelling are used to derive algorithm for Artificial Neural Network (ANN) and Adaptive Neuro-fuzzy Inference System (ANFIS) for determining critical voltage of flashover. Series of laboratory testing and measurement are carried for 1:1, 1:5 and 1:10 ratios of top to bottom surface salt deposit density on cup and pin insulators. Insulators variables such as height H, diameter D, form factor F, creepage distance L, equivalent salt deposit density (ESDD) and flashover voltage correction are identified and used to train the AI network. Comparative studies have evidently shown that the proposed (AI) technique gives the satisfactory results compared to the analytical model and test data with the Coefficient of determination R-Square value of more than 97%.

Analysis of Pollution in High Voltage Insulators via Laser-Induced Breakdown Spectroscopy

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.

Influence of Arc Flash Performance and ESDD Measurement of Bushings Tainted by Nitrates

Tainting devastate the feat of bushings. Conductors are insulated inside the bushing that carry a high voltage current through a grounded enclosure. An aspiration is to study the pollution performance of bushings tainted by Nitrates.Arc flash tests of 1kV,11kV,17.5kV bushings are tainted by three types of salts such as NaCl, NaNO3, KNO3. The morsels are negotiated under habitual environment as per IEC 60507. The impact of tainting salts with their solubility on Equivalent Salt Deposit Density (ESDD) and bushings arc flash voltage are scrutinized. The effect of tainted salts on arc flash fruition, the sway of volume conductivity and Equivalent Salt Deposit Density (ESDD) under different percentages are also scrutinized. The research upshot reveals that the Equivalent Salt Deposit Density (ESDD) rate escalated with escalating salt content. When salt concentration gets escalated then conductivity also get escalated. When Equivalent Salt Deposit Density (ESDD) get Escalated then the arc flash voltage and leakage current get slacken. Finally, the graphs are drawn between ESDD and Arc flash voltage, Conductivity and Salt concentration, Arc flash voltage and Leakage current are obtained using MATLAB software.

Flashover Performance and Process of Suspension Insulator Strings Artificially Covered with Snow

Snow accumulates on the surface of insulator string, causing a decrease in its electrical performance, seriously threatening the reliable operation of the power grid. Most previous studies have focused on iced insulators; however, there is a lack of research on snow-covered insulators. In this paper, to reveal the influencing mechanism that snow has on the electrical characteristics of insulator string, based on an artificial snowing test in a chamber, the effects of equivalent salt deposit density, applied voltage type, and snow thickness on the flashover performance of snow-covered insulators are analyzed, and the flashover process is investigated. The results show that the relationship between the arc flashover gradient and the equivalent salt deposit density is a power function with a negative exponent, which is similar to that of polluted and ice-covered insulator strings. For the insulator strings with the same snow accretion, the direct current (DC) arc flashover gradient is lower than the alternating current (AC) arc flashover gradient. The relationship between arc flashover gradient and snow thickness is also a power function. The formation of a dry band during the flashover of snow-covered insulator string is similar to the flashover of the polluted insulator, and the arc propagation along the surface of the snow-covered insulator is similar to the flashover of the iced insulator.