This paper presents an effective technique based on an artificial neural network algorithm utilized for circuit parameter identification in lightning impulse generation for low inductance loads such as low voltage windings of a power transformer, a large distribution transformer and an air core reactor. The limitation of the combination between Glaninger’s circuit and the circuit parameter selection from Feser’s suggestions in term of producing an impulse waveform to be compliant with standard requirements when working with a low inductance load is discussed. In Feser’s approach, the circuit parameters of the generation circuit need to be further adjusted to obtain the waveform compliant with the standard requirement. In this process, trial and error approaches based on test engineers’ experience are employed in the circuit parameter selection. To avoid the unintentional damage from electrical field stress during the voltage waveform adjustment process, circuit simulators, such as Pspice and EMTP/ATP, are very useful to examine the generated voltage waveform before the experiments on the test object are carried out. In this paper, a system parameter identification based on an artificial neural network algorithm is applied to determine the appropriate circuit parameters in the test circuit. This impulse voltage generation with the selected circuit parameters was verified by simulations and an experiment. It was found that the generation circuit gives satisfactory impulse voltage waveforms in accordance with the standard requirement for the maximum charging capacitance of 10 µF and the load inductance from 400 µH to 4 mH. From the simulation and experimental results of all cases, the approach proposed in this paper is useful for test engineers in selection of appropriate circuit components for impulse voltage tests with low inductance loads instead of employing conventional trial and error in circuit component selection.
This paper presents internal failure analysis of transformer windings based on the characteristic of winding impedance in the frequency domain. Two winding samples are selected to test. The simple equivalent circuit of the transformer winding is investigated and proposed. The two windings under test have 76 turns with different length. An iron core is either inserted or not inserted inside a winding in the test to investigate the effect of the iron core. Turn to turn short circuit on the windings is considered as internal failure in this paper. The simulated turn to turn short on the model is carried out in the experiment to observe impedance characteristic in the frequency domain. A number and position of short turns are varied to observe characteristics of impedances The impedance of the models of the transformer windings are measured by a spectrum analyzer in a wide frequency range upto 2 MHz. From the test results, it is investigated that a resonance frequency of the transformer model is depended on a number and position of short turns. From the investigation, it has high possibility that the characteristic can be used for analysis of internal failures occurring in a transformer.
This paper presents the studies of breakdown characteristics of a 12-kVarcing horn under a lighting impulse superimposed on an AC power frequency voltage at various angles. The lightning impulse is superimposed on the AC power frequency voltage at a phase angle varied from 0° to 360. The 12-kV arcing horn under test has dimension and configuration according to DIN 42531 standard. The critical breakdown voltages (U b50% ) with and without superposition of an impulse voltage on the AC voltage are investigated and made comparison. It is found that the statistical breakdown voltages are depended on the phase angle of the AC voltage superposed by the lightning impulse voltage. From the test results, the AC voltage affects the insulation level and it should be taken into account in an insulation design and insulation coordination.
In this paper, an effective simulation method for lightning impulse voltage tests of reactor and transformer windings is presented. The method is started from the determination of the realized equivalent circuit of the considered winding in the wide frequency range from 10 Hz to 10 MHz. From the determined equivalent circuit and with the use of the circuit simulator, the circuit parameters in the impulse generator circuit are adjusted to obtain the waveform parameters according to the standard requirement. The realized equivalent circuits of windings for impulse voltage tests have been identified. The identification approach starts from equivalent circuit determination based on a vector fitting algorithm. However, the vector fitting algorithm with the equivalent circuit extraction is not guaranteed to obtain the realized equivalent circuit. From the equivalent circuit, it is possible that there are some negative parameters of resistance, inductance, and capacitance. Using such circuit parameters from the vector fitting approach as the beginning circuit parameters, a genetic algorithm is employed for searching equivalent circuit parameters with the constraints of positive values. The realized equivalent circuits of the windings can be determined. The validity of the combined algorithm is confirmed by comparison of the simulated results by the determined circuit model and the experimental results, and good agreement is observed. The proposed approach is very useful in lightning impulse tests on the reactor and transformer windings.
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