## 2 Literature Review
Through electromagnetic transient program (EMTP) simulations, a transient-based protection system is presented and evaluated [39]. The angle between the zero-sequence voltage and current phasors is estimated by the fault-detection technique. The estimation is performed at the dominating transient frequency of the network response within the initial milliseconds after the failure. The protection system's performance is assessed for a distribution network in both unearthed and compensated neutral scenarios using a Monte Carlo method in which fault resistance, incidence angle, and fault location variations are treated as random variables in Emitter simulations. The application of IEC 61850-9-2 LE-sampled values in transients-based protection by implementing a line-protection intelligent electronic device (IED) that can distinguish between internal and external faults by comparing the polarities of wavelet coefficients of the line currents at either end of the line is discussed in [43]. A real-time digital simulator is used to implement the power system portion. In IED implementations, special attention is paid to simulating the restrictions experienced by a real relay. The findings show that IEC 61850-sampled data can be employed effectively in a transients-based protection mechanism that can withstand extreme conditions. Fault diagnosis by a wavelet transform has been investigated in many research papers [47; 48; 49; 50; 51; 52; 53]. [PERSON] et al. [30; 38] introduce an implementation of d-q axis components and wavelet-packet-transform-based hybrid technique. It is based on high-frequency sub-band contents in the d-q axis components. Then, it required one level of the wavelet packet transform (WPT) for the synchronously rotating of frame components to discriminate inrush currents from all types of internal fault currents. The WPT based on the differential protective relay in paper [49] used Butterworth passive (BP) filters to distinguish the magnetizing inrush current and restrain the relay from the operation. The BP filters are designed to extract the second-level details consisting of high-frequency components of the three-phase differential current. In previous studies [50; 51; 52; 53], the coefficients of the first scale from the discrete wavelet transform were compared to distinguish between external and internal defects in power transformers (DWT). To give comparison indicators to discern between external and internal faults, the maximum coefficient of distinct current phases (A, B, C) was divided by the zero-sequence differential current. The decision algorithm suggested in this paper can help distinguish between internal and exterior errors and provide better outcomes. DWT, on the other hand, may not be sufficient for a thorough characterization. To improve its effectiveness in power transformer protection, DWT's performance should be improved. Furthermore, to increase power transformer protection, artificial neural network techniques have been proposed in several of the approaches in the literature [7; 8; 9]. The comparison between different methodology and application that has been previously research can be summarize as shown in the literature survey in Table 1.