Study on fast early detecting and rapid accurate fault parameters estimation method for short-circuit fault

With the intelligentization of distribution network, a large scale of power electronic devices are applied in energy conversion. And the system flow of distribution network becomes random and varies greatly, which puts forward higher requirements for measurement and protection. Therefore, it's necessary to detect and identify short-circuit fault rapidly and effectively. In this paper, an early detecting method based on Wavelet Transform and a zero prediction method based on recursive least square (RLS) algorithm are proposed and implemented. The fault detection is based on the quadratic spline wavelet transform and the detail component of the wavelet transform is taken as fault eigenvalue. The parameters estimation is based recursive least square algorithm. The factors which affect the convergence speed of RSL and accuracy of zero-crossings prediction are studied. Conduct simulation and verification are carried out by using the short-circuit fault current data from PSCAD simulation, and results show that those methods can quickly determine fault inception in 1ms with error of zero-crossings less mall 1ms.