Efficient Smart Grid Fault-Identification Approach with PhotovoltaicDistributed Generators Based on Monitoring of Current/Voltage Signals

Abstract

A Smart grid fault-identification is a critical aspect of the protection relaying system with the integration of renewable energy based on photovoltaic-distributed generators. With increasing the distributed generators usage in smart grids, the conventional relaying techniques suffer from maloperation owing to the risk of changing fault current levels. Therefore, in this paper, a discrete wavelet transform (DWT) and the statistical cross-alienation coefficients-based method is proposed to detect and classify different types of faults considering the dynamic response of photovoltaic. The proposed protection scheme does not require any extra-measuring systems as it relied on the one-ended measurements that are installed at PV-feeder over a moving window, which are available due to the use of advanced measuring facilities in smart grids. This opens the doors to transferring real-time data from / to protective relays, and then these datasets are processed for discriminating among various internal fault classes and external and healthy conditions. Intensive simulation studies are executed using PSCAD/EMTDC platform along with the validation of the proposed scheme. The 300 kW PV panel is connected to grid though a boost converter and Voltage Source Inverter. Results unveil that the application of alienation concept and differential faulty energy method for approximation coefficients-based DWT for voltage and current signals show a better performance in terms of accuracy and computational burden.