Time domain single-phase reclosure scheme for transmission lines based on dual-Gaussian mixture models

The basic principle of new adaptive reclosures are to first identify whether a fault is transient or permanent and consequently to determine the reclosing moment. In this paper a novel method to enhance self-adaptive single phase autoreclosure of transmission lines is presented. Using Gaussian Mixture Models (GMM) the redundancy of setting the threshold is omitted. The proposed algorithm could prevent closing command in permanent faults and adapt dead time in temporary events. The method is derived by processing line terminal voltage around the period of dead time. The proposed scheme uses two sampled windows from the inception of the fault and two groups of GMM. Simulations performed in EMTP/ATP environment advocate the validity of the proposed algorithm convergence speed as well as fast and accurate protection scheme for reclosing relaying. The design of GMM is easy and the relative factors of the structure elements can be regulated due to the desirable effects. Since the discrimination method is done with stochastic characteristics of signals in time domain without application of any deterministic index, more reliable and accurate classification is achieved.

► A novel single phase autoreclosure scheme for transmission lines is presented.
► Method identifies transient or permanent faults and determines the reclosing moment.
► This scheme uses two GMM models with different window lengths.
► Transmission line terminal voltage around the period of dead time is sampled.
► The method is self-adaptive, with no threshold, so fast, and very accurate.