## 3 Fault Localization Methods
### Related Work  
It is evident that each group of methods has its specifics in terms of complexity and accuracy, but it is vital to notice that the applicability of the methods also relies on the used measurement equipment. Given that PMUs already represent the backbone of the WAMS and the WAMPAC in TNs and have recently also become widely adopted in DNs in the context of smart grids, we investigated the methods that incorporate PMUs more thoroughly. Several algorithms exploiting synchronized PMU data have already been proposed and are briefly summarized in the following paragraphs.  
The research in [29] presents fault detection and faulted line identification with PMU devices installed in each bus of a network. The proposed solution is suitable for both passive and active networks, with a solid-earthed or unearthed neutral, and for low and high impedance faults of any kind. Furthermore, the process was validated with a real-time simulation platform showing the identification of the faulted line, but not also the exact location.  
Another approach using a real-time simulator as a means for validating results is presented in [30]. This approach combines several algorithms, depending on the type of occurring fault and network grounding. Additionally, the phasor data concentrator and geographic information system environment are introduced.  
The detection of anomalies in grids using optimally placed PMUs was carried out by [PERSON] et al. [31]. This approach combines data-driven methods as well as criteria resulting from analysing the underlying physical model of a system. Exiting the quasi steady-state regime is exploited to design a key part of the proposed metrics. The optimal placement of PMUs with a limited number of sensors is also discussed in this work.  
The generalized fault location algorithm with optimally placed PMUs, suitable for both ring and radial feeders, is presented in [32]. The integration of information available from PMU measurements with the information contained in the distribution feeder database is performed with the aim of fault location identification. The solution is based on the assumption that the network topology, line parameters and load models are all known.  
In [33], multiple fault locations are first obtained using the synchro-phasors measured at one terminal. The exact location is determined after by comparing the voltage phasors in the junction nodes of terminals measured from two terminals.  
A short circuit theory-based approach is presented in [34] for locating permanent and temporary faults. The refinement scheme allows finding faults not only on buses, but also on branches. In addition to the synchronised phasor approach and the approach using only magnitude measurements, unsynchronized phasors are being used for the first time for fault location purposes.  
A study on a fault localization technique applicable to both legacy and modern networks with different distributed generator types is carried out in [35]. A linear least-squares estimator is utilized or a non-linear least-squares problem is solved by the trust-region-reflective algorithm if data is acquired from PMUs or smart meters (SMs), respectively.  
Last but not least, the compensation theorem from circuit theory is used for the purposes of localizing events such as faults and power quality events in DNs [11]. The solution is based on measurement differences making its performance robust against constant errors in instrumentation channels, such as errors from voltage and current transformers.  
It is important to emphasize that despite the extensive work that had already been undertaken in the field of fault localization, none of the papers (to the best of the authors' knowledge) deals with the corresponding method's data acquisition and its reliability. One of the contributions of this paper is ensuring that the premise of the methods, that the required data to perform the localization is reliable and always readily available for use, is actually met in the real environment as well.