## 5 Proposed Edge-Cloud Framework for Automated Fault Detection and Localization
### Building Blocks  
#### 5.2.1 Measurement Locations (Edge Nodes)  
Two types of measurement device were deployed in the pilot, as already explained in Section 4. Furthermore, the PMU deployment for the primary and secondary substation differed in the sense that only the ePC of the primary substation was complemented with the _Event detector_ module. The reason behind this decision was that the data from the primary substation are sufficient for detecting events that are narrowed down to only faults (similar to the protection scheme of the feeder, which is only implemented in the primary substation). The features of each edge node deployment are presented hereinafter. * PQMs  
One PQM is installed in each load bus, fulfilling the FLA requirements for active and reactive power measurements of loads. Each PQM is complemented with a gateway with an LTE communication interface for the transmission of data. Measurements from PQMs are pushed once a second via the message queuing telemetry transport (MQTT) protocol to the _MQTT broker_, which is part of the cloud-based _Data historian_ application. Since PQMs do not require any additional edge computing capability for this particular FLA application, their measurements are not pre-processed and are pushed from the edge to the cloud side of the framework in raw format. * PMU--secondary substation  
The PMU in the secondary substation is complemented by a co-located ePC that contains a local phasor data concentrator (_PDC_) with a _Time series database_ and a gateway with an LTE communication interface for the transmission of data. The gateway part is also responsible for the adaptation of the data exchange protocol from IEEE C37.118 to MQTT. Note that since the PMU and the ePC are co-located and physically connected by Ethernet cable, the entirety of the PMU data (200 Hz report rate) is transferred to the local database, whereas only 1 sample is pushed each second over the LTE gateway for the purposes of grid observability. The _Time series database_ with a retention policy has a capacity of storing up to one week of PMU data and is accessed automatically by the _Hosted application_ via the _HTTP REST API_ in case of an event. On the other hand, the _Control center_ can also request the data from this database manually in case the DSO wants more granular measurements of a particular time window. In order not to overload the figure and since this additional functionality is not required for the functioning of the FLA framework anyway, this connection is not shown in Figure 5.  
PMU--primary substation  
Similarly to the PMU in the secondary substation, the PMU in the primary substation is accompanied by an ePC containing a PDC, a local short-term storage database and a gateway. However, an additional functionality of this ePC is a local application execution environment supporting a simple fault detection algorithm (_Event detector_ in Figure 5), which is responsible for the activation of the _Hosted application_ in the cloud. There are currently two independent triggers of the _Event detector_ application. The first one compares the amplitude of the phase currents to a predefined threshold (acts similar to overcurrent protection), whereas the second trigger is activated when the magnitudes of the zero-sequence current and zero-sequence voltage phasors simultaneously exceed the corresponding thresholds and the phase angle between the phasors lies in the predefined interval (acts similar to differential protection). The _Event detector_ runs continuously, in real-time, on the entirety of the PMU data (200 Hz report rate). Once either of the triggers  
Figure 5: Edge-cloud computing framework for automated fault localization. is activated, a notification about the event and its timestamp are pushed via the MQTT to the _Event handler_ component in the cloud and the _Hosted application_ is initialized.