Power System Insulation Research Articles

Upper bound of overvoltage peak induced in power line network above lossless ground due to radiated electromagnetic disturbances

This paper deals with the assessment of the maximal peak of the overvoltage induced in a power-line network due to the field-to-wire coupling from an external electromagnetic disturbance. A worst-case analysis is here combined with the transmission line model to find the terminal overvoltage, induce by radiated electromagnetic disturbances of constrained energy density and bandlimits. The approach was applied to canonic power line network topologies, from statistic viewpoint, it is demonstrated that dominant coupling can be ascribed to the branch containing the most twisted segments. Accordingly, efforts have been devoted to find analytical solution to overvoltage peak upper bound for the coupling-dominant zigzag branch. In this connection, both versatile implicit solution and approximated explicit expressions of the upper bound are formulated, which reveals the relations between the upper bound of zigzag branch and its segments, quantitively interpreting the effect of segment orientations and length. Finally, numerical simulations corroborate the model validity and suggest that the estimations of upper bound are sufficiently accurate for analyzing practical power line network. This proposed approach will be instructive for power system insulation coordination and protection design.

Influence of Surface Discharge on Resin Degradation in Decay-like Fracture of Composite Insulators

Composite insulators have gradually become the preferred approach for electrical insulation in power systems, especially in polluted areas. Composite insulators consist of three main components: the shed, rod, and end fitting. Insulators withstand mechanical stresses via rods that are composed of glass-fiber-reinforced epoxy (GFRE). However, regardless of the high tensile strength of GFRE rods, in real-life operation, abnormal fractures have frequently been reported all over the world, which substantially increase the risk of major accidents in power systems. Fractural accidents mainly consist of brittle and decay-like fractures, which exhibit rather different morphologies at the cross sections. Brittle fracture has been effectively eliminated, while the mechanism of decay-like fracture has still not been clearly revealed. In this study, surface discharge tests were applied to investigate the discharge influence on the degradation of GFRE. The test successfully simulated the composition variation of the rods in real-life composite insulators with decay-like fractures. Moreover, it confirmed that the distinction between the characteristics of brittle fracture and decay-like fracture stems from epoxy degradation due to hydrolysis and carbonization. In addition, the respective influences of the resin type, glass fiber type, and acid liquid immersion on the degradation process were probed, and the degradation mechanism proposed in this research was verified. Based on the results, measures for preventing the development of decay-like fractures in real-life operations were determined.

Dynamic Sustainable Polyimide Film Combining Hardness with Softness via a "Mimosa-Like" Bionic Strategy.

Dielectric polyimides (PIs)are ubiquitous as insulation in electrical power systems and electronic devices. Generally, dynamic polyimide is required to solve irreversible failure processes of electrical or mechanical damage, for example, under high temperature, pressure, and field strength. The challenge lies in the design of the molecular structure of rigid polyimide to achieve dynamic reversibility. Herein, a low-molecular-weight polyimide gene unit is designed to crosslink with polyimide ligase to prepare the smart film. Interestingly, due to the variability of gene unit and ligase combinations, the polyimide films combining hardness with softness are designed into three forms via a "Mimosa-like" bionic strategy to adapt to different application scenarios. Meanwhile, the films have good degradation efficiency, excellent recyclability, and can be self-healable, which makes them reuse. Clearly, the films can be used in the preparation of ultrafast sensors with a response time ≈0.15 s and the application of corona-resistant films with 100% recovery. Furthermore, the construction of polyimide and carbon-fiber-reinforced composites (CFRCs) has been verified to apply to the worse environment. Nicely, the composites have the property of multiple cycles and the non-destructive recycle rate of carbon fiber (CF) is as high as 100%. The design idea of preparing high-strength dynamic polyimide by crosslinking simple polyimide gene unit with ligase could provide a good foundation and a clear case for the sustainable development of electrical and electronic polyimides, from the perspective of Mimosa bionics.

Modeling Grounding Systems Response to Current Impulses Considering Nonlinear Effects

Modeling grounding systems is necessary for the calculation of ground potential rise (GPR), power system simulations and insulation coordination studies. In this work, a methodology for estimating equivalent circuit parameters through the optimization of the time-domain impulse response was developed. It allows to obtain equivalent circuits with positive parameters that accurately represent grounding systems considering both effects related to frequency and soil ionization. Additionally, linear and nonlinear equivalent circuits for calculating the impulse response of typical grounding systems were proposed. The Nelder-Mead optimization method was applied to adjust the circuit parameters. For evaluating the methodology developed and the proposed models, data from impulse current tests was used. It was found that the use of nonlinear circuits increases the accuracy of the simulated response, resulting in errors of less than 4% in the estimation of GPR. The proposed methodology allows obtaining representative circuits of typical grounding systems used in the electrical system. The circuits can be used for systemic studies and calculation of GPR considering short-circuit or lightning currents.

Image Characteristic Extraction of Ice-Covered Outdoor Insulator for Monitoring Icing Degree

Serious ice accretion will cause structural problems and ice flashover accidents, which result in outdoor insulator string operating problems in winter conditions. Previous investigations have revealed that the thicker and longer insulators are covered with ice, the icing degree becomes worse and icing accident probability increases. Therefore, an image processing method was proposed to extract the characteristics of the icicle length and Rg (ratio of the air gap length to the insulator length) of ice-covered insulators for monitoring the operation of iced outdoor insulator strings. The tests were conducted at the artificial climate room of CIGELE Laboratories recommended by IEEE Standard 1783/2009. The surface phenomena of the insulator during the ice accretion process were recorded by using a high-speed video camera. In the view of the ice in the background of the picture of fuzzy features and high image noise, a direct equalization algorithm is used to enhance the grayscale iced image contrast. The median filtering method is conducted for reducing image noise and sharpening the image edge. The maximum entropy threshold segmentation algorithm is put forward to extract the insulators and its surface ice from the background. Then, the modified Canny operator edge detection algorithm is selected to trace the boundaries of objects through the extraction of information about attributes of the endpoints of edges. After we obtained the improved Canny edge detection image for both of the ice-covered insulators and non-iced insulators, the icing thickness can be obtained by calculating the difference between the edge of the non-iced insulators image and the edge of the iced insulator image. Besides, in order to identify the icing degree of the insulators more accurately, this paper determines the location of icicles by using the region growth method. After that, the icicle length and Rg can be obtained to monitor the icing degree of the insulator. It will be helpful to improve the ability to judge the accident risk of insulators in power systems.

Characterizing the behavior of current pulses in corona discharge

The pulse stage of corona discharge, which can lead to the dangerous degradation of insulation in power systems, is closely examined in relation to the applied voltage and the gas pressure.

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.

Analysis of training techniques of ANN for classification of insulators in electrical power systems

Identifying defects in electrical power systems during field inspections is a difficult task, since faults are generally not visible and may be intermittent. To find possible adverse conditions, specific inspection equipment is used. The ultrasound detector is the equipment normally used to inspect outdoor insulating systems; however, using it demands operator experience. To improve the defect condition classification, artificial intelligence techniques are applied to assist the operator in the decision task and thereby facilitate the identification of faulty insulating devices in the grid. The training of artificial neural network (ANN) models is an important step in solving the classification problem. This study aims to evaluate the training capacity in terms of the performance of different optimisation methods for the calculation of the mean square error after convergence. Traditional methods such as Gradient Descent and its variations will be presented, as well as methods that employ high computational effort such as quasi-Newton and Levenberg–Marquardt. In order to base these concepts, a review will be presented on the use of these algorithms and on the problem of classification of insulators in distribution networks. The results show that there is a considerable performance difference between the calculation methods.

Measurement and Denoising of Partial Discharge Signal in High Voltage Cables using Wavelet Transform

A huge amount of exploration propagated over the past decade investigates the characterization of Partial Discharge (PD) inception in cable ideology. Underground cables are passed down as surrogate for over hauling in congested areas. The intention of this research is to examine the feasibility of exploring insulation defects present in High Voltage (HV) Cable setup by employing PD disclosure under alternating current (AC) Voltage. Study of PD characteristics has a congregate of predictable distinguished contraption to prove the probity and the affirmation of electrical insulation of Power System. In this work, the cable is exposed into the measurement of PD signal under artificially conceived defects. PD signal parameters are mainly depends on the size of void and applied voltage. In general, the measured PD signal is depraved with interferences. To identify the exact characteristics of PD distinctive and its severity, the PD signal is subjected to Wavelet Transform (WT) for denoising. Different types of WT families with various level is used for de-noising. To identify the effectiveness of the WT for de-noising guidelines like Signal to Reconstruction Error Ratio (SRER) and Reduction in Noise Level (RNL) are used.

Autonomous Self-Healing of Electrical Degradation in Dielectric Polymers Using In Situ Electroluminescence

Summary Dielectric polymers are ubiquitous as electrical insulation in electrical power systems and electronic devices. Electrical treeing is typically regarded as an irreversible degradation process of dielectric polymers subjected to high electric stresses, which significantly limits their lifespan and endangers the reliability of electronics and electrical power systems. Here, we report self-healing polymers consisting of microcapsules that are capable of completely restoring the dielectric properties as a direct response to electrical tree degradation. We design the microcapsules with a relatively higher dielectric constant than polymer matrix to guide the propagation of electrical trees. The electroluminescence generated in situ during electrical treeing of polymers triggers crosslinking of the healing agents released from the capsules to repair the electrically damaged areas under ambient conditions. Notably, the breakdown strength of the mended region is largely enhanced upon healing, which was initiated at different locations. The integration of autonomous healing capability into dielectric materials opens new avenues to smart polymers for electronics and energy applications.

Infrared Evaluation Classification Method for Deteriorated Insulator Based on Bayesian Algorithm

The insulation state detection of transmission line insulators in power systems is essential to ensure the reliability of transmission power supply. Aiming at the low accuracy of the infrared diagnostic fault diagnosis method for porcelain insulators in transmission lines, this paper proposes a classification method based on Bayesian algorithm for the classification of infrared map degradation degree of insulators. Bayesian algorithm is used to mine the correspondence between the characteristic parameters of the insulator infrared inspection map and the insulator state represented by the map, so as to improve the Bayesian network structure and finally classify the map. The results show that the method can effectively classify the operating state of insulators. The accuracy of the power insulator state classification model based on Bayesian algorithm reaches 94.2%.A new method of intelligent detection and diagnosis for evaluating the deterioration of insulators is proposed. This method has the advantage of high stability and accuracy.

Plasma treatment to improve the hydrophobicity of contaminated silicone rubber — the role of LMW siloxanes

Silicone rubber is widely used in power system insulation for its hydrophobicity and hydrophobicity transfer to prevent pollution flashover. The influence of low molecular weight (LMW) siloxanes on hydrophobicity of contaminated silicone rubber after plasma jet treatment was investigated in this study. Experimental results show that plasma jet treatment for several seconds can significantly improve the hydrophobicity of contaminated silicone rubber. LMW siloxanes play an important role in the quick recovery of hydrophobicity induced by plasma jet treatment. Extraction of the LWM siloxanes from the silicone rubber decreases the contact angle after plasma treatment. Fourier transform infrared (FTIR) spectroscopy shows that hydrophobic groups appear on the surface of the contamination layer. The hydrophobicity improvement of contaminated silicone rubber results from LMW siloxanes transferred to the contamination layer during plasma treatment and the LMW siloxanes are mostly original uncrosslinked siloxanes in the silicone rubber. The molar mass distributions of the LMW siloxanes in hydrophobic contamination of treated specimens were similar with naturally transferred ones. X-ray photoelectron spectroscopy shows that an inorganic layer appears after plasma aging, which obscures the transfer of LMW siloxanes and reduce the hydrophobicity during plasma treatment.

Analysis of Electric Field and Current Density for Different Electrode Configuration of XLPE Insulation

The most important aspect influencing the circumstance and characteristics of electrical discharges is the distribution of electric field in the gap of electrodes. The study of discharge performance requires details on the variation of maximum electric field around the electrode. In electrical power system, the insulation of high voltage power system usually subjected with high electric field. The high electric field causes the degradation performance of insulation and electrical breakdown start to occur. Generally, the standard sphere gaps widely used for protective device in electrical power equipment. This project is study about the electric field distribution and current density for different electrode configuration with XLPE barrier. Hence, the different electrode configuration influences the electric field distribution. This project mainly involves the simulation in order to evaluate the maximum electric field for different electrode configuration. Finite Element Method (FEM) software has been used in this project to perform the simulation. This project also discusses the breakdown characteristics of the XLPE. The accurate evaluation of electric field distribution and maximum electric field is an essential for the determination of discharge behavior of high voltage apparatus and components. The degree of uniformity is very low for pointed rod-plane when compared to other two electrode configurations. The non- uniform electric distribution creates electrical stress within the surface of dielectric barrier. As a conclusion, when the gap distance between the electrodes increase the electric field decrease.

New result on maximum entropy threshold image segmentation based on P system

In this paper, maximum entropy threshold image segmentation based on P system is studied. A new P system and related interaction rules are designed, and particle swarm optimization (PSO) algorithm with different inertia weights is adopted as the evolution operator of new P system. Some typical experiments are carried out to show the advantage of given algorithm, which finally is successfully applied to the image segmentation of breakdown insulator in power system.

Influence of algae growth on the external insulation performance of HVDC insulators

In recent years, microorganisms such as algae have been found on composite and RTV coated insulators in humid environment in southwest and southern China. Algae growth poses a potential threat to the outer insulation of electrical power system because of the special features of biological foul. Insulator samples with algae growth were obtained from transmission towers of 500 kV Tianguang DC transmission line and the influence of algae growth on the external insulation performance was studied in this paper. A measurement circuit was used to measure the partial surface conductivity of algae and non-algae dots on insulator surfaces. Water spray classification method was used to test the hydrophobicity of algae and non-algae parts of the insulators. An image processing method was proposed to discern algae on the insulator surfaces and calculate the algae coverage rate. The withstand capability of insulator were tested at working voltage and 1.2 times working voltage. The research results showed that the presence of algae increased the local salt distribution and reduced the hydrophobicity of insulator surfaces. The results also indicated that impacts of algae contanmination to withstand capability of insulators were limited when the algae coverage rate was less than 20%.

Determination of Hydrophobic Contact Angle of Epoxy Resin Compound Silicon Rubber and Silica

Epoxy resin is a thermosetting polymeric material which is very good for application of high voltage outdoor insulator in electrical power system. This material has several advantages, i.e. high dielectric strength, light weight, high mechanical strength, easy to blend with additive, and easy maintenance if compared to that of porcelain and glass outdoor insulators which are commonly used. However, this material also has several disadvantages, i.e. hydrophilic property, very sensitive to aging and easily degraded when there is a flow of contaminants on its surface. The research towards improving the performance of epoxy resin insulation materials were carried out to obtain epoxy resin insulating material with high water repellent properties and high surface tracking to aging. In this work, insulating material was made at room temperature vulcanization, with material composition: Diglycidyl Ether Bisphenol A (DGEBA), Metaphenylene Diamine (MPDA) as hardener with stoichiometric value of unity, and nanosilica mixed with Silicon Rubber (SiR) with 10% (RTV21), 20% (RTV22), 30% (RTV23), 40% (RTV24) and 50% (RTV25) variation. The usage of nanosilica and Silicon Rubber (SIR) as filler was expected to provide hydrophobic properties and was able to increase the value of surface tracking of materials. The performance of the insulator observed were contact angle of hydrophobic surface materials. Tests carried out using Inclined Plane Tracking procedure according to IEC 60-587: 1984 with Ammonium Chloride (NH4Cl) as contaminants flowed using peristaltic pumps. The results show that hydrophobic contact angle can be determined from each sample, and RTV25 has maximum contact angle among others.

Electrohydrodynamic behavior of water droplets on a horizontal super hydrophobic surface and its self-cleaning application

Moisture is a significant factor that affects the insulation performance of outdoor high-voltage insulators in power systems. Accumulation of water droplets on insulators causes severe problems such as flashover of insulators and power outage. In this study, we develop a method to fabricate a micro/nano hierarchical super hydrophobic surface. The as-prepared super hydrophobic surface exhibits a water contact angle (WCA) of 160.4±2°, slide angle (SA) less than 1° and surface free energy (SFE) of 5.99mJ/m2. We investigated the electrohydropdynamic behavior of water droplet on a horizontal super hydrophobic surface compared with hydrophobic RTV silicone rubber surface which was widely used as anti-pollution coating or shed material of composite insulator. Results show that water droplet tended to a self-propelled motion on the super hydrophobic surface while it tended to elongate and break up on the RTV surface. The micro/nano hierarchical surface structure and chemical components with low surface free energy of the super hydrophobic surface jointly contributed to the reduction of skin fraction drag and subsequently made it possible for the motion of water droplet driven by electric field. Furthermore, the self-propelled motion of water droplets could also sweep away contaminations along its moving trace, which provides super hydrophobic surface a promising anti-pollution prospect in power systems.

Aggregating Deep Convolutional Feature Maps for Insulator Detection in Infrared Images

Insulator detection using an infrared image is challenged by variance of temperature, orientations, and a cluttered background. A robust and discriminative representation of insulators in electric power systems is needed. This paper proposes a novel method for generating this type of representation in infrared images by taking advantage of high-level discriminative Convolutional Neural Networks (CNNs) to feature the extraction framework and the deformation invariant nature of the Vector of Locally Aggregated Descriptors (VLAD) aggregator. Different from existing methods, we delve deep into the convolutional feature maps. We first extract deep activation maps from convolutional layers of a pretrained deep model and replace the last three fully-connected layers with a VLAD pooling layer to generate the representation of an insulator. Then, we train a Support Vector Machine (SVM) for binary classification. To further verify the effectiveness and robustness of our proposed feature, an insulator detection pipeline based on an object proposal is introduced. The experimental results show that our proposed method can achieve an accuracy of 93%. Meanwhile, the detection results demonstrate that our insulator detection pipeline has satisfied performance goals.

Determination of Hydrophobic Contact Angle of Epoxy Resin Compound Silicon Rubber and Silica

Epoxy resin is a thermosetting polymeric material which is very good for application of high voltage outdoor insulator in electrical power system. This material has several advantages, i.e. high dielectric strength, light weight, high mechanical strength, easy to blend with additive, and easy maintenance if compared to that of porcelain and glass outdoor insulators which are commonly used. However, this material also has several disadvantages, i.e. hydrophilic property, very sensitive to aging and easily degraded when there is a flow of contaminants on its surface. The research towards improving the performance of epoxy resin insulation materials were carried out to obtain epoxy resin insulating material with high water repellent properties and high surface tracking to aging. In this work, insulating material was made at room temperature vulcanization, with material composition: Diglycidyl Ether Bisphenol A (DGEBA), Metaphenylene Diamine (MPDA) as hardener with stoichiometric value of unity, and nanosilica mixed with Silicon Rubber (SiR) with 10% (RTV21), 20% (RTV22), 30% (RTV23), 40% (RTV24) and 50% (RTV25) variation. The usage of nanosilica and Silicon Rubber (SIR) as filler was expected to provide hydrophobic properties and was able to increase the value of surface tracking of materials. The performance of the insulator observed were contact angle of hydrophobic surface materials. Tests carried out using Inclined Plane Tracking procedure according to IEC 60-587: 1984 with Ammonium Chloride (NH4Cl) as contaminants flowed using peristaltic pumps. The results show that hydrophobic contact angle can be determined from each sample, and RTV25 has maximum contact angle among others.

Bayesian Inference of Power System Insulation Reliability in the Presence of Voltage Harmonics

This article illustrates a Bayesian inference methodology for the parametric evaluation of the reliability of power system components in the presence of voltage harmonics. The methodology starts from an experimentally-based life model for solid insulation under distorted voltage, which belongs to the class of the popular Inverse Power Model. Thereafter, a novel approach is developed for building the prior distribution of the unknown life model parameters, described by a joint Normal distribution, that implies a Lognormal model for the hazard rate and the Mean Time To Failure. The applicability and efficiency of the proposed Bayesian methodology is checked by means of a broad amount of Monte Carlo simulations performed for the insulation of power capacitors and cables subjected to harmonic voltages. The results prove the satisfactory behavior of the Bayesian methodology especially for quite small samples; this is an important outcome, since – as well known in the case of real power systems - small samples are a common practical case.