## 1 Introduction  
The penetration of DG (Distributed Generation) based on renewables, EV (Electric Vehicles), and distributed storage in the low voltage power distribution networks entails many benefits. As a matter of fact, it will definitely contribute to achieving the main goals of the so-called Smart Grids, such as minimizing both costs and environmental impacts while maintaining system reliability,resilience, and stability [1]. However, it also entails great challenges especially to the grid management, which cannot keep \"swimming\" at the primary substation level anymore, but needs to \"dive\" down to the secondary substations, smart meters, and even beyond. As a token of the increase in complexity that this change of paradigm entails, assuming 100 SS (Secondary Substations) per primary substation and 100 smart meters per SS, which sounds quite reasonable in European power distribution networks [2; 3], the number of elements that need to be considered increases four orders of magnitude. There are different ways of approaching the new scenario sketched in previous paragraph, but all them rely on the same common idea: the solution is all about communications. In this regard, AMI (Advanced Metering Infrastructures) are being widely deployed worldwide [4; 5; 6] to provide bidirectional communications which allow delivering sophisticated services such as DR (Demand Response) [7]. In the case of the EU (European Union), for instance, most of its members have decided to undertake massive AMI deployments involving an estimated accumulated investment of \(\boldsymbol{\upepsilon}\) 35,000 million for the installation of 195 million smart meters by 2020 [8]. Although wireless communications of course play an important role in the Smart Grid, in general, and AMI, in particular [9], PLC (Power Line Communications) specially stand out in this field [10; 11; 12] due to the great trade-off between economic and technical requirements they present [13]. However, the power lines were designed to transmit power and not data. Hence, they represent a harsh communications media which suffers from frequency selectivity, continuous altered loads, EMI (ElectroMagnetic Interference), and, above all, noise. DG, EV, and storage indeed represent sources of noise themselves, since they are equipped with power electronics that introduce unwanted emissions in the frequency bands where PLC works (so-called supraharmonics when such emissions are between 2 and 150 kHz). During the last decades, theoretical models for the PLC channel [14; 15; 16; 17] and noise [18; 19; 20; 21; 22] have been developed based on measurements or analysis to mitigate such problems, contributing to take PLC from simulation environments to the field. As a result, from some time now there are singular infrastructures, such as laboratories and in-field deployments, which involves both PLC networks and DG, EV, and storage equipment. Such infrastructures can be used to further improve PLC networks and its coexistence with the ecosystem of devices they have to monitor and control (1) by obtaining measurements that can be used to fine-tune communications networks or be input to theoretical models and simulations [23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36], and (2) by learning through experimentation itself, which is indeed in the very origins of science. This paper contributes to these two approaches to keep improving PLC networks in the aforementioned new scenarios of the Smart Grid with remarkable presence of DG, EV, and storage at the low voltage grids. Thus, Section 2 sets the background of the paper, presenting an overview of PLC technologies in AMI scenarios, with special emphasis on NBPLC (Narrowband PLC) technology PRIME (PoweRline Intelligent Metering Evolution) [37; 38].