Abstract: The increasing penetration of Distributed Generation (DG) from Renewable Energy Resources (RESs) is heavily affecting the design and operation of modern power grids. The growing diffusion of dispersed generators installed at end users’ premises is calling for the adoption of advanced control and protection mechanisms, to comply with the increasing complexity of grid codes. New functions are being introduced, year over year, by national regulatory frameworks, thus often requiring the implementation of intelligent devices. This is the case, for instance, of Interface Protection Systems (IPSs), which are used to prevent the undesired islanding of distributed generators in smart and micro grids. In particular, the coordination of distributed IPSs in modern smart grid scenarios is becoming a crucial task for the safe operation of modern power grids. However, the adoption of newer and smarter units is only half of the story, and the overall costs following the deployment of proper communication infrastructures may become critical. To cope with this issue, the use of low-cost communication systems must be investigated, and their applicability must be properly addressed. In this speech, the use of the Long-Range Wide Area Network (LoRaWAN) technology is suggested as a viable approach to implement the coordination of IPSs, and its applicability evaluated by providing sensitivity analyses. A proper communication architecture based on the LoRaWAN Class B technology was proposed by following the definition of the required IPS monitoring and control functions. A specific data model structure was also defined to allow the computation of the payload of the communication. The scalability analysis was carried out by computing the number of devices that can be handled by a single LoRaWAN gateway (GW) and the maximum expected time of response between a triggering event and the arrival of the related coordination command. The results of the study showed that up to 312 devices can be managed by a single GW, by assuring a maximum response time of 22.95 s. A faster maximum response time of 6.2 s is also possible by reducing the number of managed devices to 12.