This paper analyses two different approaches of fault distance location in a double circuit transmission lines, using artificial neural networks. The single and modular artificial neural networks were developed for determining the fault distance location under varying types of faults in both the circuits. The proposed method uses the voltages and currents signals available at only the local end of the line. The model of the example power system is developed using Matlab/Simulink software. Effects of variations in power system parameters, for example, fault inception angle, CT saturation, source strength, its X/R ratios, fault resistance, fault type and distance to fault have been investigated extensively on the performance of the neural network based protection scheme (for all ten faults in both the circuits). Additionally, the effects of network changes: namely, double circuit operation and single circuit operation, have also been considered. Thus, the present work considers the entire range of possible operating conditions, which has not been reported earlier. The comparative results of single and modular neural network indicate that the modular approach gives correct fault location with better accuracy. It is adaptive to variation in power system parameters, network changes and works successfully under a variety of operating conditions. 1. Introduction Protection of double-circuit transmission lines poses additional problems due to zero sequence mutual coupling between faulted and healthy circuits during earth faults . The nature of mutual coupling is highly variable; and it is affected by network changes such as switching in/out of one of the parallel lines, thus causing underreach/overreach of conventional distance relaying . Artificial neural network has emerged as a relaying tool for protection of power system equipments . ANN has pattern recognition, classification, generalization, and fault tolerance capability. ANN has been widely used for developing protective relaying schemes for transmission lines protection. Most of the research on ANN-based protection schemes has been carried out for single-circuit transmission lines [4–16]. An adaptive distance protection of double-circuit line using zero sequence thevenin equivalent impedance and compensation factor for mutual coupling to increase the reach and selectivity of relay has been developed in . Fault classification using ANN for one circuit of parallel double-circuit line has been reported in . A neural network based protection technique for combined 275？kV/400？kV
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