Smart grid fault detection and classification with multi‐distributed generation based on current signals approach

Abstract

Smart grid (SG) containing clean distributed generation (DG) has gained intensive research for reliable digital protection against fault conditions. The main objective of this study is to develop and validate a fast and efficient fault detection and classification algorithm taking into account the dynamic behaviour of DG units. The proposed algorithm does not require additional measurements as it based only on the synchronised measured three-phase currents through the communication facilities available in SG. The advanced communication technologies in SG are currently utilised for efficient and real-time data transfer from the protective relays to the monitoring and protection centre. The transferred data are processed for fault diagnosing before taking the necessary trip actions. In the proposed algorithm, the statistical cross-alienation coefficients are calculated for the measured current signals at sending and receiving ends of each feeder. Fault detection and classification process will be achieved taking into account the changes in the synchronised and discretised waveform of current signals within a movable window of (1/4 cycle). The proposed algorithm is tested on real system to detect and classify the different fault condition. The results indicated that the proposed technique is fast and reliable for SG digital protection schemes.