Study on Fault Line Detection Based on Genetic Artificial Neural Network in Compensated Distribution System

The faulty line detection of single phase to earth fault in power system with neutral grounding via arc suppression coil has not been well solved. The commonly used single faulty line detection methods, such as wavelet transform method, the fifth harmonic current method and zero sequence current active components method, etc., can only process partial fault information, so their reliability of faulty line detection is not satisfied. By means of constructing both relative fault measurement function and confirmable fault measurement function the fault measurement function of each faulty line detection method is determined, then using genetic neural network the intelligent fusion of practical fault measurements of those faulty line detection methods is conducted, thereby the faulty line detection result with higher reliability can be obtained. Simulation results by EMTP show that the faulty line detection result by the proposed method is more precise and possesses stronger robustness