Abstract
This paper provides a general overview of the initial developments in the REIVE project (Smart Grids with Electric Vehicles). The main focus of the project is on smart grid infrastructures for large scale integration of EV and micro-generation units. It is a natural evolution of the InovGrid project promoted by the EDP Distribuição - the Portuguese Distribution Network Operator - and allows the development of seminal concepts and enabling technological developments within the Smart Grid paradigm. This paper presents the management and control architecture developed to allow electric vehicle integration in smart grid operation. Additionally, it presents the major impacts in distribution grids of the simultaneous deployment of electric vehicles, micro-generation and smart grid technologies.

Abstract
This paper describes the main results of the MERGE project relative to Electric Vehicle (EV) charging strategies and the impacts of EV integration on the steady-state grid operation. MERGE is a €4.5m, collaborative research project supported by the European Commission's Seventh Framework Programme (FP7). The consortium includes utilities, regulators, commercial organisations and universities with interests in the power generation, automotive, electronic commerce and hybrid and electric vehicle sectors across the entire European Union (EU). One of the MERGE project missions is to evaluate the impacts that EV will have on EU electric power systems, exploring EV and SmartGrid/MicroGrid simultaneous deployment, together with renewable energy increase, to achieve CO 2 emission reduction through the identification of enabling technologies and advanced control approaches. The work presented proposes three charging strategies, dumb charging, multiple price tariffs and smart charging, and uses EV integration scenarios of adherence to these charging schemes. The resulting scenarios are tested using an algorithm coded with Python and using PSS/E, created within the MERGE framework to study EU grids steady-state behaviour. Additionally, the critical mass of EV adherence to smart charging schemes that brings positive impacts to the distribution grids operation was also evaluated.

Abstract
Under normal operating conditions, a MicroGrid (MG) is interconnected with the Medium Voltage (MV) network. However, planned or unplanned events like maintenance or faults in the MV network, respectively, may lead to MG islanding. In order to deal with islanded operation and even black start following a general blackout, an emergency operation mode must be envisaged. Two possible control strategies were investigated and are described in this paper in order to operate a MG under emergency mode. A sequence of actions for a well succeeded black start procedure, involving microgeneration units, has also been identified contributing for an increase in distribution network reliability.

Abstract
The decarbonization of the economy and the increasing integration of renewable energy sources into the generation mix are bringing new challenges, requiring novel technological solutions in the topic of smart grids, which include smart transformers and energy storage systems. Additionally, power quality is a vital concern for the future smart grids; therefore, the continuous development of power electronics solutions to overcome power quality problems is of the utmost importance. In this context, this article proposes a novel three-phase multiobjective unified power quality conditioner (MO-UPQC), considering interfaces for solar PV panels and for energy storage in batteries. The MO-UPQC is capable of compensating power quality problems in the voltages (at the load side) and in the currents (at the power grid side), while it enables injecting power into the grid (from the PV panels or batteries) or charging the batteries (from the PV panels or from the grid). Experimental results were obtained with a three-phase four-wire laboratory prototype, demonstrating the feasibility and the large range of applications of the proposed MO-UPQC.

Abstract
In isolated power systems with very high instantaneous shares of renewables, additional inertia should be used as a complementary resource to battery energy storage systems (BESSs) for improving frequency stability, which can be provided by synchronous condensers (SCs) integrated into the system. Therefore, this paper presents a methodology to infer the system dynamic security, with respect to key frequency indicators, following critical disturbances. Of particular interest is the evidence that multiple short-circuit locations should be considered as reference disturbances regarding the frequency stability in isolated power grids with high shares of renewables. Thus, an artificial neural network (ANN) structure was developed, aiming to predict the network frequency nadir and Rate of Change of Frequency (RoCoF), considering a certain operating scenario and disturbances. For the operating conditions where the system frequency indicators are violated, a methodology is proposed based on a gradient descent technique, which quantifies the minimum amount of additional synchronous inertia (SCs which need to be dispatch) that moves the system towards its dynamic security region, exploiting the trained ANN, and computing the sensitivity of its outputs with respect to the input defining the SC inertia.