Abstrait

Application based on feedback neural network fault current detection method

Yang Zhao, PengGao, Yun-xia Jiang, Rui Zhang

For some traditional current detection methods which are slow, poor reliability, and can notmeet the large grid interconnection and flexibleAC transmission requirements, a fault line detection method based on neural network is proposed. By BP neural network, Elman neural network, the method is used for fault signal detection error training, can detect fault signal in a short time. The effect and speed of the Elman neural network is better, and have a certain anti-jamming capability, that can quickly detect failure lines of the electric power. It has a very important significance in improving the speed and service life of the grid circuit breaker, fast switching applications power systemand ensuring the safety of the power grid.