Mechanism of saline deposition and surface flashover on high-voltage insulators near shoreline:mathematical models and experimental validations

This paper deals with sea salt transportation and deposition mechanisms and discusses the serious issue of degradation of outdoor insulators resulting from various environmental stresses and severe saline contaminant accumulation near the shoreline. The deterioration rate of outdoor insulators near the shoreline depends on the concentration of saline in the atmosphere, the influence of wind speed on the production of saline water droplets, moisture diffusion and saline penetration on the insulator surface. This paper consists of three parts: first a model of saline transportation and deposition, as well as saline penetration and moisture diffusion on outdoor insulators, is presented; second, dry-band initiation and formation modelling and characterization under various types of contamination distribution are proposed; finally, modelling of dry-band arcing validated by experimental investigation was carried out. The tests were performed on a rectangular surface of silicone rubber specimens (12 cm × 4 cm × 8 cm). The visualization of the dry-band formation and arcing was performed by an infrared camera. The experimental results show that the surface strength and arc length mainly depend upon the leakage distance and contamination distribution. Therefore, the model can be used to investigate insulator flashover near coastal areas and for mitigating saline flashover incidents.</p

Novel technique for estimating pollution-associated leakage current in high voltage insulators based on adaptive filtering in long-term recording

[EN] Moist polluting substances on high-voltage insulator surfaces can cause power-line failures by triggering electric arcs. There are at present no effective methods of measuring insulator pollution levels during normal operations. In this work, we attempt to estimate insulator pollution leakage current (PLC) as an indirect method of measuring deposits in a 30 month period of simultaneously recording leakage current and related environmental variables in substation insulators. We analyzed the relationship between raw leakage current and environmental variables. We canceled out the influence of relative humidity on leakage current by adaptive filtering and then obtained the PLC by filtering out the anomalous peaks in the recording. The proposed method considerably reduces the correlation between leakage current and relative humidity (0.826 vs 0.019). The resulting signal was only slightly correlated with other environmental variables (<0.03), suggesting that the relationships between leakage current and temperature, wind direction and speed are mainly attributable to their influence on relative humidity. The PLC presents a quasi-annual smooth fluctuation over time with a magnitude similar to those obtained in laboratory tests. This novel technique could be used to monitor insulator PLC in real time and thus improve power supply continuity and reduce maintenance costs.Bueno-Barrachina, J.; Cañas Peñuelas, CS.; Ye Lin, Y.; Fuster Roig, VL. (2021). Novel technique for estimating pollution-associated leakage current in high voltage insulators based on adaptive filtering in long-term recording. Measurement Science and Technology. 32(5):1-10. https://doi.org/10.1088/1361-6501/abea3dS11032

Comparative laboratory performance characterisation of silicone rubber textured insulators

Silicone rubber (SiR) outdoor insulators are increasingly being deployed in new AC and DC high voltage transmission systems thanks to their superior performance in wet-polluted conditions compared to traditional porcelain and glass insulators. However, in severely polluted environments, sustained discharge activities and dry band arcing due to surface contamination cause tracking, erosion, and the loss of hydrophobicity on the SiR insulator surface. This degradation can accelerate damage to the insulator surfaces, increasing the probability of a flashover and enduring insulator failure. This thesis presents an experimental study on the electric performance of polluted and aged outdoor SiR polymeric insulators using AC and DC voltages. The research involved an extensive review of the published literature and an investigation of the performance of SiR insulators subjected to different ambient conditions and identifies the modes where most failure and degradation occurred on SiR surfaces. Experimental investigations were carried out to compare the aging performance of two 11kV SiR insulator designs using a rotating wheel dip test under AC and positive DC excitations. A standard polymeric insulator design was used and compared with insulators that had a textured surface. Both insulator designs were fabricated in-house using a vacuum casting machine. Several electrical parameters were measured during the test to characterise the performance of each insulator. Dry band arcing activities were mainly observed on the trunk surface of the conventional profile. A decrease in hydrophobicity was measured on the tested surfaces, and tracking and erosion defects were also observed on both insulator designs. Leakage current measurements showed that drying and discharge activity was greater for a conventional insulator compared with the textured insulator, and more severe degradation appeared under positive DC tests than under AC. These studies showed that insulators with a textured design can improve the performance of SiR insulators against tracking and erosion under AC and positive DC excitations. The electric field and potential distributions along the leakage surface of the 11 kV SiR insulators under dry clean and wet polluted conditions were studied using finite element method COMSOL Multiphysics. The critical of high field regions on SiR surfaces were identified and the power dissipated in the pollution layer along insulator surface was calculated. This study showed useful information about surface heating, which could be used to predict of the formation of dry bands. An investigation of the pollution layer characterisation on conventional and textured pattern designs is described. Several tests were conducted to evaluate the behaviour of the insulator surfaces under different conditions. ESDD and NSDD parameters were measured for different materials, and evaluations for each design were also performed. Leakage conductance measurements on surface designs were determined, and the distribution trends of surface conductance were also characterised. Different rectangular SiR samples were assessed, and an improvement for reducing the pollutant deposition on textured surfaces was observed. In 4-shed insulators, the textured design showed comparable ESDD value with conventional profile. Textured designs also showed slower growth of the leakage current than the conventional design. Clean fog tests (based on a high voltage ramp test) were carried out to investigate the flashover performance of conventional and textured insulator designs. For different ranges of wetting and pollution severity conditions, the textured design showed an improvement in the flashover performance that could reach 16 % compared to the conventional surface. This indicates that the textured surface seems to be more effective under severe ambient conditions. It was also observed that the textured insulator design can improve the electrical performance of SiR insulators under AC and DC voltages

Partial Discharge Classification Using Acoustic Signals and Artificial Neural Networks and its Application in detection of Defects in Ceramic Insulators

Online condition monitoring of critical assets constitutes one method whereby the electrical insulation industry can help safeguard grids through the avoidance of system outages due to insulation failure. This thesis introduces a novel approach for monitoring the condition of outdoor ceramic insulators based on partial discharge (PD) measurements. The presence of physical defects such as punctures, broken porcelain, and cracks will ultimately lead to the initiation of PD activity in outdoor ceramic insulators. In addition to defects, surface discharges such as that caused by corona and dry band arcing are also very common, particularly in wet and polluted outdoor insulators. Such a discharge activity that originates in these kinds of conditions can cause flashover or insulator failure, resulting in power outages. Measuring early-stage discharge activity is thus very important as a means of avoiding catastrophic situations in power networks. The work presented in this thesis involved initial tests conducted to distinguish between different types of controlled discharges generated in the laboratory. The next step was the implementation of an artificial neural network (ANN) for classifying the type of discharge based on selected features extracted from the measured acoustic signals. First, relatively high-frequency acoustic signals are transformed into low-frequency signals using an envelope detection algorithm imbedded in the commercial acoustic sensor. A fast Fourier transform (FFT) is then applied to each low-frequency signal, and finally, 60 Hz, 120 Hz, and 180 Hz are used as input feature vectors for the developed ANN. This initial research was then extended to include testing of the proposed diagnostic tool on a practical insulation system, and outdoor ceramic insulators were selected for this purpose. Three types of defects were tested under laboratory conditions: a cracked ceramic insulator, a healthy insulator contaminated by wetting with salt water, and a corona generated from a thin wire wound to the ceramic insulator. Both a single disc, and three discs connected in an insulator string were tested with respect to these defects. For both controlled samples and full insulators, a recognition rate of more than 85 % was achieved

Partial Discharge Classification Using Acoustic Signals and Artificial Neural Networks and its Application in detection of Defects in Ceramic Insulators

Online condition monitoring of critical assets constitutes one method whereby the electrical insulation industry can help safeguard grids through the avoidance of system outages due to insulation failure. This thesis introduces a novel approach for monitoring the condition of outdoor ceramic insulators based on partial discharge (PD) measurements. The presence of physical defects such as punctures, broken porcelain, and cracks will ultimately lead to the initiation of PD activity in outdoor ceramic insulators. In addition to defects, surface discharges such as that caused by corona and dry band arcing are also very common, particularly in wet and polluted outdoor insulators. Such a discharge activity that originates in these kinds of conditions can cause flashover or insulator failure, resulting in power outages. Measuring early-stage discharge activity is thus very important as a means of avoiding catastrophic situations in power networks. The work presented in this thesis involved initial tests conducted to distinguish between different types of controlled discharges generated in the laboratory. The next step was the implementation of an artificial neural network (ANN) for classifying the type of discharge based on selected features extracted from the measured acoustic signals. First, relatively high-frequency acoustic signals are transformed into low-frequency signals using an envelope detection algorithm imbedded in the commercial acoustic sensor. A fast Fourier transform (FFT) is then applied to each low-frequency signal, and finally, 60 Hz, 120 Hz, and 180 Hz are used as input feature vectors for the developed ANN. This initial research was then extended to include testing of the proposed diagnostic tool on a practical insulation system, and outdoor ceramic insulators were selected for this purpose. Three types of defects were tested under laboratory conditions: a cracked ceramic insulator, a healthy insulator contaminated by wetting with salt water, and a corona generated from a thin wire wound to the ceramic insulator. Both a single disc, and three discs connected in an insulator string were tested with respect to these defects. For both controlled samples and full insulators, a recognition rate of more than 85 % was achieved

Calibration of the OSU Psychrometric Chamber and First Experiments

Complete the construction of a new psychrometric chamber at OSU and demonstrate that the chamber is capable of performing accurate and precise experiments on thermal systems with and without a live thermal load. Completion of the chamber involved the development and fabrication of the control system. The control system included both the hardware and software needed to adjust and maintain the conditions in both the indoor and outdoor rooms. After completing the control system the chamber was ran in order to produce conditions needed to perform two experiments. These two experiments include the testing of an 11-ton (39 kW) rooftop air-conditioning unit and the establishment of thermal conductivity for different cold pipe insulation systems exposed to both moist air condensing and non-condensing conditions. Not only was these experiments performed but, the required experimental setup was also design and construct for both. An uncertainty analysis was performed on these setups and it shows to produce excellent theoretical uncertainty. The actual experiments results and accuracies confirm these finding as well as the experimental setups designs, fabrications, and abilities. Furthermore, the validation of the chamber and chamber control system was proven proficient at performing these two different experiments. These two experiments were different in nature; in both experiments a range of conditions were used, further validating the chamber and control system's capabilities.Mechanical & Aerospace Engineerin