This thesis describes an investigation into the influences of arcing and conductor deflection due to magnetic forces on the accuracy of fault locator algorithms in electrical distribution networks. The work also explores the possibilities of using the properties of an arc to identify two specific types of faults that may occur on an overhead distribution line.A new technique using the convolution operator is introduced for deriving differential equation algorithms. The first algorithm was derived by estimating the voltage as an array of impulse functions while the second algorithm was derivedusing a piecewise linear voltage signal. These algorithms were tested on a simulated single-phase circuit using a PI-model line. It was shown that the second algorithm gave identical results as the existing dynamic integration operator type algorithm.The first algorithm used a transformation to a three-phase circuit that did not requireany matrix calculations as an equivalent sequence component circuit is utilised for a single-phase to ground fault. A simulated arc was used to test the influence of the non-linearity of an arc on the accuracy of this algorithm. The simulations showed that the variation in the resistance due to arcing causes large oscillations of thealgorithm output and a 40th order mean filter was used to increase the accuracy and stability of the algorithm. The same tests were performed on a previously developed fault locator algorithm that includes a square-wave power frequency proximation of the fault arc. This algorithm gave more accurate and stable results even with largearc length variations. During phase-to-phase fault conditions, two opposing magnetic fields force the conductors outwards away from each other and this movement causes a change in thetotal inductance of the line. A three dimensional finite element line model based on standard wave equations but incorporating magnetic forces was used to evaluate this phenomenon. The results show that appreciable errors in the distance estimations can be expected especially on poorly tensioned di stribution lines.New techniques were also explored that are based on identification of the fault arc. Two methods were successfully tested on simulated networks to identify a breakingconductor. The methods are based on the rate of increase in arc length during the breaking of the conductor. The first method uses arc voltage increase as the basis of the detection while the second method make use of the increase in the non-linearity of the network resistance to identify a breaking conductor. An unsuccessful attempt was made to identifying conductor clashing caused by high winds: it was found that too many parameters influence the separation speed of the two conductors. Nounique characteristic could be found to identify the conductor clashing using the speed of conductor separation. The existing algorithm was also used to estimate the voltage in a distribution network during a fault for power quality monitoring purposes.
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