A neural network based protection technique for combined 275kV/400kV double circuit transmission lines
The work described in this paper addresses the problems encountered by conventional distance relays when protecting double-circuit transmission lines comprising different voltage levels. The problems arise principally as a result of the mutual coupling between the two circuits under different fault conditions; this mutual coupling is highly nonlinear in nature. An adaptive protection scheme is proposed for such lines based on employing a neural network (NN). A NN has the ability to classify the nonlinear relationship between measured signals and the faulted zone by identifying different patterns of the associated voltages and currents. One of the key points of this paper is data preprocessing of the measured signals essentially to extract the most significant features from the signals. The adaptive protection scheme is tested under a specific fault type, but varying fault location, fault resistance, fault inception angle and different source capacities. All the test results clearly show that the proposed adaptive protection technique is well suited for double circuits with different voltage levels.
neural networks adaptive protection double circuit lines