الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
The sudden increase in power demand leads to manufacture of large number of oil immersed power transformers and other electrical power equipment. Power transformers are the most vital equipment in power system. Any failure in transformer affects the stability and reliability of the whole power system. Reliable operation of transformers largely depends on a lifetime of insulating system. The transformer may fail due to any combination of mechanical, electrical or thermal stresses which can degrade the quality of the insulation in power transformer. As transformers age, their internal condition degrades, which increases the risk of failure. The faults that most frequently arise in practice may be classified broadly as the following; failures in the magnetic circuit, failures in the windings, failures in the dielectric insulation, structural failures.
Transformer insulation deteriorates as the function of temperature, moisture and time. The core and winding losses, stray losses in tank and metal support structures are the principle sources of heat which cause oil and winding temperature rise. There are multiple reasons for overheating such as improper cooling, excessive eddy currents, bad joints, blocked radiators, overloading, improper earthing and harmonic contents in power supply. This leads to accelerated aging of oil and cellulosic solid insulation, which generate the gases within transformer and further leads to permanent failure. To prevent such failures, effective analysis and diagnosis needs to be investigated.
Sweep Frequency Response Analysis (SFRA) is an effective low-voltage, off-line diagnostic techniques. It is used to find out any possible winding displacement or mechanical deterioration inside the transformer, due to large electromechanical forces occurring from the fault currents or due to transformer transportation and relocation based on measuring their electrical transfer functions over a wide frequency range to identify the abnormal areas prior to catastrophic failure. This thesis investigates the impact of electrical parameters variation of a high frequency transformer model on its SFRA signature to help in SFRA classification and interpretation. The simulations have been done using MATLAB, and to compare them with the reference data. The results of SFRA measurements which were made using the swept frequency measurements are repeatable up to and beyond 1MHz. The analysis could be made from several points of view as a virtual inspection; and also, there is three different statistical techniques as a fitting algorithm (such as Chinese Standard DL 911/2004, the proposed CCF technique and the proposed Adjusted R2 technique) are presented and evaluated for interpreting the results of SFRA measurements and compared these techniques with each other.
On the other hand, the type of gases generated and amount of gas concentrations in oil efficiently are usually evaluated using dissolved gas analysis (DGA). This thesis proposes a MATLAB program to help in standardizing DGA interpretation techniques to investigate the accuracy of these methods in interpreting the transformer condition and proposes a proper maintenance action based on DGA results. Then the result of this work is useful for planning an appropriate maintenance strategy to keep the power transformer in acceptable condition. The evaluation is carried out on DGA data obtained from 352 oil samples that have been collected from a 38 different transformers of different rating and different life span. This diagnostic technique uses normalized parts per million values of combustible gases as an input to detect thermal and electrical faults to represent the state of insulation of the transformer. Consequently, strengthening the decision making of fault prediction in transformers can be enhanced through maintaining proper history data and regular monitoring of DGA and SFRA. It is crucial to study the effect of various faults on gas concentrations and gradual escalation in resonance shift.