Abstract
This paper aims to describe the main outcomes of the ADMS4LV project which stands for Advanced Distribution Management System for Active Management of LV Grids. ADMS4LV targets the development and demonstration of a framework with adequate tools to optimize the management and operation of Low Voltage (LV) networks towards the effective implementation of Smart Grids. This work details the main functionalities of ADMS4LV and discusses their implementation. The validation of the functionalities is presented from demonstrations in a laboratorial setup, namely regarding the algorithms which using advanced data analytics, accomplish to operate LV networks with low observability, (i.e., with few real-time measurements) and without having full knowledge of the networks' technical characteristics, such as the consumers' phase connection to the grid. The assessment of the results shows the adequacy of the ADMS4LV solutions for deployment in distribution networks with current infrastructures, differing unnecessary investments in sensory devices. © 2019 IEEE.

Abstract
The evolution of the electrical power sector due to the advances in digitalization, decarbonization and decentralization has led to the increase in challenges within the current distribution network. Therefore, there is an increased need to analyze the impact of the smart grid and its implemented solutions in order to address these challenges at the earliest stage, i.e., during the pilot phase and before large-scale deployment and mass adoption. Therefore, this paper presents the scalability and replicability analysis conducted within the European project InteGrid. Within the project, innovative solutions are proposed and tested in real demonstration sites (Portugal, Slovenia, and Sweden) to enable the DSO as a market facilitator and to assess the impact of the scalability and replicability of these solutions when integrated into the network. The analysis presents a total of three clusters where the impact of several integrated smart tools is analyzed alongside future large scale scenarios. These large scale scenarios envision significant penetration of distributed energy resources, increased network dimensions, large pools of flexibility, and prosumers. The replicability is analyzed through different types of networks, locations (country-wise), or time (daily). In addition, a simple replication path based on a step by step approach is proposed as a guideline to replicate the smart functions associated with each of the clusters.

Abstract
Electrification of society and economy is crucial to fight against climate changes assuming simultaneously a large-scale integration of electricity generation exploiting Renewable Energy Sources (RES). The increasing presence of RES and Electric Vehicles (EV) in Low Voltage (LV) networks, and the emergence of the Smart Grid paradigm will require relevant changes in the operational management of both LV and Medium Voltage (MV) networks. In this paper, two different strategies (separated and coordinated management) for the operational management of MV and LV networks are compared regarding their ability to integrate large amounts of RES and to accept increased electrification of consumption, including EV. Each management strategy is modeled through optimization problems, being then applied to an electrical distribution system consisting of MV and LV networks. Results show that a coordinated operational management outperforms the separated strategy, by allowing the integration of much higher volumes of RES and EV.

Abstract
Achieving carbon neutral power systems is pushing for higher penetration of distributed energy resources (DER) in existing distribution systems. Accordingly, sophisticated, yet, practical tools for the optimal operation and management of active distribution systems (ADS) are in high need. In response to this necessity, this paper presents a novel and scalable tool for ancillary services procurement by distribution system operators (DSOs). The developed tool takes into consideration the inter-temporal and variable nature of DER in an uncertainty-aware approach. This tool is also suited for real-world implementation with large ADS, as it adopts a sequential linearization approach. As such, it allows DSOs to procure flexibility optimally from DERs embedded in ADS in the day-ahead operation planning timeframe, where congestion and voltage issues are managed.