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For reliable operation of power transformers, the condition of the insulation system is essential. This paper reports on a detailed study of the effect of ageing, temperature and moisture on frequency and time domain spectroscopic measurements carried out on oil-impregnated pressboard samples as well as on a distribution transformer under controlled laboratory conditions. Because field measurements are generally performed after de-energizing the transformer, extreme care is required in interpreting the results due to inherent temperature instabilities. To avoid large thermal variations that may affect the results, a customized adiabatic room was built around the transformer for measurements above the ambient. Capacitance ratio and direct current conductivity deduced from the spectroscopic measurements, helped to interpret the data. Because, low frequency measurements techniques are time consuming, alternative to a transfer of time domain data into frequency domain data was investigated.

Abstract:A power transformer outage has a dramatic financial consequence not only for electric power systems utilities but also for interconnected customers. The service reliability of this important asset largely depends upon the condition of the oil-paper insulation. Therefore, by keeping the qualities of oil-paper insulation system in pristine condition, the maintenance planners can reduce the decline rate of internal faults. Accurate diagnostic methods for analyzing the condition of transformers are therefore essential. Currently, there are various electrical and physicochemical diagnostic techniques available for insulation condition monitoring of power transformers. This paper is aimed at the description, analysis and interpretation of modern physicochemical diagnostics techniques for assessing insulation condition in aged transformers. Since fields and laboratory experiences have shown that transformer oil contains about 70% of diagnostic information, the physicochemical analyses of oil samples can therefore be extremely useful in monitoring the condition of power transformers.

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Moisture is recognized to be "enemy number one" for transformer insulation.

A self-consistent dynamic model allowing the prediction of ac discharge activities leading to flashover on ice-covered insulator surface is presented. This model takes into account the effects of a number of parameters including insulator geometry and applied water conductivity. The instantaneous variations of major parameters are discussed in order to develop a sequential time-dependent simulation of the flashover. The temporal evolution of arc current and axial arc velocity are determined in a consistent manner. The critical flashover voltage characteristics, as a function of surface conductivity, insulator length, and insulator diameter, calculated by the model are quite satisfactory when compared to the experimental results from empirical models reported in the literature.

Abstract:The condition of the internal cellulosic paper and oil insulation are of concern for the performance of power transformers. Over the years, a number of methods have been developed to diagnose and monitor the degradation/aging of the transformer internal insulation system. Some of this degradation/aging can be assessed from electrical responses. Currently there are a variety of electrical-based diagnostic techniques available for insulation condition monitoring of power transformers. In most cases, the electrical signals being monitored are due to mechanical or electric changes caused by physical changes in resistivity, inductance or capacitance, moisture, contamination or aging by-products in the insulation. This paper presents a description of commonly used and modern electrical-based diagnostic techniques along with their interpretation schemes.

A dynamic model for predicting dc arc behavior and critical flashover voltage of ice-covered insulating surfaces is presented. The model takes into consideration insulating geometry, pre-contamination level, and characteristics of ice layers. Assuming arc behavior as a time dependant impedance, it is possible to determine various arc characteristics such as time histories of leakage currents, potential gradient, channel radius, trajectory, propagation velocity and the energy injected into the zones free of ice (also called air gaps). The simulated results provided by the model are in agreement with those obtained experimentally using a simplified ice-covered cylinder as well as a short string of five IEEE standard porcelain suspension units covered with artificial ice.Index Terms -Dynamic model, dc arc, leakage current, outdoor insulators, flashover voltage, atmospheric icing.1070-9878/1/$17.00 0 2003 IEEE