# Adaptive Impedance-Based Fault Location Algorithm for Active Distribution Networks
## 1 Introduction  
Fault location (FL) is one of the most important tasks in the supervision and management of electrical networks with self-healing features. This task plays an important role on the fast maintenance and restoration of the electricity supply for the costumers [1, 2]. However, despite technological advancements, the FL process is still based on the calls from customers who provide useful information for identifying the fault region. This procedure proves to be inefficient, since it requires the maintenance team to visually inspect a potentially large region to locate the fault point. Currently, there are several techniques that are based on mathematical formulations proposed for FL estimation. They use information such as the system topology, its electrical parameters, and recorded voltage and currents at the substation [3, 4]. Among them, there are methods based on traveling waves, artificial intelligence, and impedance-based methods. Traveling-wave methods for FL have been presented previously [5, 6]. These techniques present some limitations, such as the requirement of high sampling rate [3]. On theother hand, artificial intelligence-based methods present a high performance. Still, they need large databases to perform their learning process, and their accuracy depends on the database information quality [3; 6; 7; 8]. The impedance-based methods are one of the most successful techniques for FL [3]. These methods are easy to implement in real life applications, have good precision, and a high cost/benefit relationship [9; 10; 11; 12]. However, these techniques present some limitations like the estimation of multiple FL. This problem can be reduced by artificial intelligence-, traveling waves-, or circuital analysis-based strategies [4; 13; 14]. Additionally, with the development of smart grids and the use of renewable energy, distribution grids are being transformed from passive to active networks. With this, including the effect of Distributed Energy Resources (DER) on the formulation of the FL problem becomes necessary; DER comprise Distributed Generation (DG) technologies and energy storage technologies [15]. Most DER require a power electronic based interface--defined in this paper as Inverter-interfaced DER (IIDER)--to connect them and ensure their synchronization with the Power Distribution System (PDS). The remaining DER are connected directly to the network, and are defined as Inverter non-interfaced DER (INIDER). Some strategies to consider the DER effect on FL have been proposed in the technical literature [16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27]. In [16; 17; 25] the DER effect is considered by using a model of the synchronous machine, which is only valid for INIDER [28]. In [26; 27] the DER effect is considered by using a model of the inverter, which is only valid for IIDER. Further, the methods exposed in the literature [18; 19; 20; 21; 22; 23; 24] are formulated using synchronized current and voltage phasors, provided by Intelligent Electronic Devices (IED), in order to consider the DER effect on the FL. These methods are robust, but depend strongly on the availability of measurements given by IED, which are installed in DER. If the IED communication or its synchronization with the Distribution Management System (DMS) is lost; the FL is not possible. In this context, it is most important to create models that allow the FL estimation without relying on the availability of measurements on DER location. Considering such, the main contribution of this work is the development of an adaptive impedance-based FL algorithm for active distribution networks. It combines the information provided by IEDs, located at the substation, and the DER to estimate the FL. Nevertheless, if the information provided by the IED is not available, the DER effect is considered by the use of its equivalent linear analytical models.