Adaptive auto reclosing system for HV transmission lines based on ANN

This paper proposes an ANN based adaptive Auto Reclosing AR which integrated of an operation of distance measuring relay in HV Over Head Transmission Line OHTL. This work is brought to enhance stability synchronism, and reliability during the transient faults of OHTL. Thus, it leads to increase the continuity of the electric power system, especially of hydropower plants are connected to utility grid. This work are used Matlab\Simulink environment to design and simulate a single-phase auto-reclosing, which depends on the Artificial Neural Networks ANN integrated with a distance relay DR. In addition, the simulation model consists of Boolean algebra circuits, and timers are utilised to build Auto-reclosure of a circuit breaker in each phase. The ANN is here trained to recognize angle values of actual impedances (in the positive sequence only) in which it can classify which phase exactly is line to ground fault. The simulation results show the ability of this combination to distinguish among various fault types and giving multi pulses-shot of tripping and reclosing for the specific circuit breaker with a successful mechanism. In this paper, a realistic system with real parameters was represented by the important transmission line (Mosul Dam-East Mosul), which currently is only the main and alone line that connects the northern Iraq network with a national grid.