Abstract
In order to avoid voltage problems derived from the connection of large amounts of renewable-based energy generation to distribution networks, new advanced tools need to be developed that are able to exploit the presence of Distributed Energy Resources (DER). This paper describes the approach proposed for a predictive voltage control algorithm to be used in LV distribution networks in order to make use of available flexibilities from domestic consumers via their Home Energy Management System (HEMS) and more traditional Distribution System Operator's (DSO's) resources, such as transformers with On-Load Tap Changer (OLTC) and storage devices. The proposed algorithm for the Low Voltage Control (LVC) is detailed in this paper. The algorithm was then tested through simulation using a representative Portuguese Low Voltage (LV) network in order to assess its performance in several future scenarios with different operating conditions. The future prospects for field-trial validation in a Portuguese smart grids pilot are also discussed.

Abstract
In order to avoid voltage problems derived from the connection of large amounts of renewable-based generation to the electrical distribution system, new advanced tools need to be developed that are able to exploit the presence of Distributed Energy Resources (DER). This paper describes the approach proposed for a predictive voltage control algorithm to be used in Low Voltage (LV) distribution networks in order to make use of available flexibilities from domestic consumers via their Home Energy Management System (HEMS) and more traditional resources from the Distribution System Operator (DSO), such as transformers with On-Load Tap Changer (OLTC) and storage devices. The proposed algorithm-the Low Voltage Control (LVC)-is detailed in this paper. The algorithm was tested through simulation using a real Portuguese LV network and real consumption and generation data, in order to evaluate its performance in preparation for a field-trial validation in a Portuguese smart grids pilot.

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
This study presents Integrid’s project framework to manage low voltage (LV) electrical networks, aiming to avoid both technical and quality constraints, induced by the ever-increasing amount of flexible resources spread all over the grid. These assets cover a large amount of renewable-based energy generation to electrical vehicles and energy storage units. For this to be possible, new advanced tools were developed to exploit the benefits of the so-called distributed energy resources, while overcoming limitations on the metering and communication infrastructures. Hence, this study describes the approach taken to perform the active management of LV networks, without a perfect level of observability, exploiting the flexibility provided by the distribution system operator’s resources combined with the one offered by private consumers through the home energy management systems. Additionally, some results followed by a brief discussion are presented, enforcing the success of the developed tools. The algorithms within these tools allow to forecast both microgeneration, available flexibility and load profiles, as well as to estimate the network’s state, at different time frames.

Abstract
Energy communities have been designed to empower consumers while maximizing the self-consumption of local renewable energy sources (RESs). Their presence in distribution systems can result in strong modifications in the operation and management of such systems, moving from a centralized operation to a distributed one. In this scope, this work proposes a distributed community-based local energy market that aims at minimizing the costs of each community member, accounting for the technical network constraints. The alternating direction method of multipliers (ADMM) is adopted to distribute the market, and preserve, as much as possible, the privacy of the prosumers' assets, production, and demand. The proposed method is tested on a 10-bus medium voltage radial distribution network, in which each node contains a large prosumer, and the relaxed branch flow model is adopted to model the optimization problem. The market framework is proposed and modeled in a centralized and distributed fashion. Market clearing on a day-ahead basis is carried out taking into account actual energy exchanges, as generation from renewable sources is uncertain. The comparison between the centralized and distributed ADMM approach shows an 0.098% error for the nodes' voltages. The integrated OPF in the community-based market is a computational burden that increases the resolution of the market dispatch problem by about eight times the computation time, from 200.7 s (without OPF) to 1670.2 s. An important conclusion is that the proposed market structure guarantees that P2P exchanges avoid the violation of the network constraints, and ensures that community agents' can still benefit from the community-based architecture advantages.

Abstract
Electric power systems are currently experiencing a profound change, as increasing amounts of Renewable Energy Sources (RESs) displace conventional forms of generation. This development has gone hand-in-hand with an increasing share of distributed power generation being connected directly to the Distribution Network (DN), and the widespread of other types of Distributed Energy Resources (DERs), such as Energy Storage Sytems (ESSs), Electric Vehicles (EVs), and active (flexible) consumers. As these trends are expected to continue, this will require a profound revision of the way Transmission System Operators (TSOs) and Distribution System Operators (DSOs) interact with each other to fully benefit from the growing flexibility that is available at the DN level. In this work we propose a new tool for the coordinated operational planning of transmission and distribution systems, considering the existence of shared resources that can be simultaneously used by TSO and DSOs for the optimal operation of their networks. The tool uses advanced distributed optimization techniques, namely the Alternating Direction Method of Multipliers (ADMM) in order to maintain data privacy of the several agents involved in the optimization problem, and keep the tractability of the problem. The proposed tool is applied to modified IEEE test systems, and the results obtained highlight the benefits of the proposed coordination mechanism to solve problems occurring simultaneously at the transmission and DN-levels.