Study of Hydrophobicity Effect on 220kV Double Tension Insulator String Surface Using Finite Element Method

Insulators are one of the most significant equipment in power system. The insulators’ operation may affect the power flow, line loss and reliability. The electrical parameters that influence the performance of insulator are surface leakage current, corona and dry band arcing. Electric field stresses on the insulator surface will degrade the insulating properties and lead to puncture. Electric filed stresses can be analyzed by numerical methods and experimental evaluation. As per economic aspects, evaluation by numerical methods are best. In outdoor insulation, a hydrophobic surface can facilitate to prevent water film formation on the insulation surface, which is decisive for diminishing leakage currents and partial discharge (PD) under heavy polluted environments and harsh weather conditions. Polymer materials like silicone rubber have an outstanding hydrophobic property among general insulation materials. In this paper, electrical field intensity of 220 kV porcelain and polymer double tension insulator strings at critical regions are analyzed and compared by using Finite Element Method. Hydrophobic conditions of polymer insulator with equal and unequal water molecule conditions are verified by using finite element method.

Power Transformers Insulation Material Investigations: Partial Discharge

There is a great problem in testing and investigations the reliability of different type of transformers insulation materials. It summarized in how to create and simulate the real conditions of working transformer and testing its insulation materials for Partial Discharge PD, typically as in the working mode. A lot of tests may give untrue results as the physical behavior of the insulation material differs under tests from its working condition. In this work, the real working conditions were simulated, and a large number of specimens have been tested. The investigations first stage, begin with choosing samples of different types of insulation materials (papers, pressboards, etc.). The second stage, the samples were dried in ovens at 105 C0and 0.01bar for 48 hours, and then impregnated with dried and gasless oil (the water content less than 6 ppm.) at 105 C0and 0.01bar for 48 hours, after so specimen cooling at room pressure and temperature for 24 hours. The third stage is investigating PD for the samples using ICM PD measuring device. After that, a continuous test on oil-impregnated insulation materials (paper, pressboards) was developed, and the phase resolved partial discharge pattern of PD signals was measured. The important of this work in providing the industrial sector with trusted high accurate measuring results based on real simulated working conditions. All the PD patterns (results) associated with a discharge produced in well-controlled laboratory condition. They compared with other previous and other laboratory results. In addition, the influence of different temperatures condition on the partial discharge activities was studied.

The Comprehensive Study Based on Ultrasonic and X-ray Visual Technology for GIS Equipment Detection

For lack of the visualization of the ultrasonic detection method of partial discharge (PD), the ultrasonic detection technology combined with the X-ray visual detection method (UXV) is proposed. The method can conduct qualitative analysis accurately and conduct reliable positioning diagnosis to the internal insulation defects of GIS, and while it could make up the blindness of the X-ray visual detection method and improve the detection rate. In this paper, an experimental model of GIS is used as the trial platform, a variety of insulation defects are set inside the GIS cavity. With the proposed method, the ultrasonic method is used to conduct the preliminary detection, and then the X-ray visual detection is used to locate and diagnose precisely. Therefore, the proposed UXV technology is feasible and practical.

Pattern Recognition of Partial Discharge by Using Simplified Fuzzy ARTMAP

This paper presents the effectiveness of artificial intelligent technique to apply for pattern recognition and classification of Partial Discharge (PD). Characteristics of PD signal for pattern recognition and classification are computed from the relation of the voltage phase angle, the discharge magnitude and the repeated existing of partial discharges by using statistical and fractal methods. The simplified fuzzy ARTMAP (SFAM) is used for pattern recognition and classification as artificial intelligent technique. PDs quantities, 13 parameters from statistical method and fractal method results, are inputted to Simplified Fuzzy ARTMAP to train system for pattern recognition and classification. The results confirm the effectiveness of purpose technique.

Measurement of Small PD-S in Compressed SF6(10%) - N2(90%) Gas Mixture

Partial Discharge measurement is a very important means of assessing the integrity of insulation systems in a High Voltage apparatus. In compressed gas insulation systems, floating particles can initiate partial discharge activities which adversely affect the working of insulation. Partial Discharges below the inception voltage also plays a crucial in damaging the integrity of insulation over a period of time. This paper discusses the effect of loose and fixed Copper and Nichrome wire particles on the PD characteristics in SF6-N2 (10:90) gas mixtures at a pressure of 0.4MPa. The Partial Discharge statistical parameters and their correlation to the observed results are discussed.

Online Partial Discharge Source Localization and Characterization Using Non-Conventional Method

Power cables are vulnerable to failure due to aging or defects that occur with the passage of time under continuous operation and loading stresses. PD detection and characterization provide information on the location, nature, form and extent of the degradation. As a result, PD monitoring has become an important part of condition based maintenance (CBM) program among power utilities. Online partial discharge (PD) localization of defect sources in power cable system is possible using the time of flight method. The information regarding the time difference between the main and reflected pulses and cable length can help in locating the partial discharge source along the cable length. However, if the length of the cable is not known and the defect source is located at the extreme ends of the cable or in the middle of the cable, then double ended measurement is required to indicate the location of PD source. Use of multiple sensors can also help in discriminating the cable PD or local/ external PD. This paper presents the experience and results from online partial discharge measurements conducted in the laboratory and the challenges in partial discharge source localization.

An Advanced Time-Frequency Domain Method for PD Extraction with Non-Intrusive Measurement

Partial discharge (PD) detection is an important method to evaluate the insulation condition of metal-clad apparatus. Non-intrusive sensors which are easy to install and have no interruptions on operation are preferred in onsite PD detection. However, it often lacks of accuracy due to the interferences in PD signals. In this paper a novel PD extraction method that uses frequency analysis and entropy based time-frequency (TF) analysis is introduced. The repetitive pulses from convertor are first removed via frequency analysis. Then, the relative entropy and relative peak-frequency of each pulse (i.e. time-indexed vector TF spectrum) are calculated and all pulses with similar parameters are grouped. According to the characteristics of non-intrusive sensor and the frequency distribution of PDs, the pulses of PD and interferences are separated. Finally the PD signal and interferences are recovered via inverse TF transform. The de-noised result of noisy PD data demonstrates that the combination of frequency and time-frequency techniques can discriminate PDs from interferences with various frequency distributions.

Ageing and Partial Discharge Patterns in Oil-Impregnated Paper and Pressboard Insulation at High Temperature

The power transformer is the most expensive, indispensable and arguably the most important equipment item in a power system Insulation failure in transformers can cause long term interruption to supply and loss of revenue and the condition assessment of the insulation is thus an important maintenance procedure. Oil-impregnated transformer insulation consists of mainly organic materials including mineral oil and cellulose-base paper and pressboard. The operating life of cellulose-based insulation, as with most organic insulation, depends heavily on its operating temperature rise above ambient. This paper reports results of a laboratory-based experimental investigation of partial discharge (PD) activity at high temperature in oil-impregnated insulation. The experiments reported here are part an on-going programme aimed at investigating the way in which insulation deterioration can be monitored and quantified by use of partial discharge diagnostics. Partial discharge patterns were recorded and analysed during increasing and decreasing phases of the temperature. The effect of ageing of the insulation on the PD patterns in oil and oil-impregnated insulation are also considered.