Abstract
The uncertainties related to when and where Plug-in Electric Vehicles (PEVs) will charge in the future requires the development of stochastic based approaches to identify the corresponding load scenarios. Such tools can be used to enhance existing system operators planning techniques, allowing them to obtain additional knowledge on the impacts of a new type of load, so far unknown or negligible to the power systems, the PEVs battery charging. This chapter presents a tool developed to evaluate the steady state impacts of integrating PEVs in distribution networks. It incorporates several PEV models, allowing estimating their charging impacts in a given network, during a predefined period, when different charging strategies are adopted (non-controlled charging, multiple tariff policies and controlled charging). It uses a stochastic model to simulate PEVs movement in a geographic region and a Monte Carlo method to create different scenarios of PEVs charging. It allows calculating the maximum number of PEVs that can be safely integrated in a given network and the changes provoked by PEVs in the load diagrams, voltage profiles, lines loading and energy losses. Additionally, the tool can also be used to quantify the critical mass (percentage) of PEV owners that need to adhere to controlled charging schemes in order to enable the safe operation of distribution networks. © Springer Science+Business Media Singapore 2015.

Abstract
The feasibility of the MicroGrid (MG) concept, as the pathway for integrating Electric Vehicles (EV) and other Distributed energy Resources (DER), has been the focus of several research projects around the world. However, developments have been mainly demonstrated through numerical simulation. Regarding effective smart grid deployment, strong effort is required in demonstration activities, addressing the feasibility of innovative control solutions and the need of specific communication requirements. Therefore, the main objective of this paper is to provide an integrated overview of the laboratorial infrastructure under development at INESC Porto, where it will be possible to conceptualize, implement and test the performance of new control and management concepts for Smart Grid cells. The laboratorial infrastructure integrates two experimental MG, including advanced prototypes for power conditioning units to be used in micro generation applications, batteries for energy storage and a fully controlled bidirectional power converter. Preliminary experimental results and organization of the infrastructure are presented.

Abstract
Large scale integration of micro-generation, together with active loads and energy storage devices, under micro-grid and multi micro-grid concepts, requires the adoption of advanced control strategies at different distribution network levels. This paper presents advanced control functionality to be housed at high voltage (HV)/medium voltage (MV) substations and to be used to manage micro-generation, active loads and energy storage, subject to different constraints. Some of these constraints involve inter-temporal relations, such as the ones related with energy storage levels in consecutive time moments. This functionality is specially oriented to deal with stressed MV network operation involving overload and excessive voltage drops situations.

Abstract
A distinctive characteristic of a Microgrid (MG) system is related to the ability of operating autonomously. However, the stability of the system relies in storage and generation availability, providing frequency and voltage regulation. Considering the deployment of distributed storage units in the Low Voltage network and of smart metering infrastructures, this paper presents an online tool for promoting an effective coordination of MG flexible resources in order ensure a secure autonomous operation and maximize the time that the MG is able to operate islanded from the main grid. The tool determines a priori an emergency operation plan for the next hours, based on load and microgeneration forecasting. The limited energy capacity of the distributed storage units participating in MG control is also considered.

Abstract
The development of the microgrid (MG) concept endows distribution networks with increased reliability and resilience and offers an adequate management and control solution for massive deployment of microgeneration and electric vehicles (EVs). Within an MG, local generation can be exploited to launch a local restoration procedure following a blackout. EVs are flexible resources that can also be actively included in the restoration procedure, thus contributing to the improvement of MG operating conditions. The feasibility of MG service restoration, including the active participation of EVs, is demonstrated in this article through extensive numerical simulation and experimentation in a laboratorial setup. © 2007-2011 IEEE.

Abstract
Within the Smart Grid paradigm, the MicroGrid concept (MG) presents an adequate framework to monitor and manage the low voltage network and coordinate the resources connected to it, including the smart grid new players, namely the consumers, prosumers and the Electric Vehicles (EV). The coordinated management and control of the MG resources, enables the operation both connected to the main power network or autonomously, due to planned or unplanned outages. In order to operate autonomously, the MG relies in its storage capacity to provide some form of energy buffering capabilities to balance load and generation. This paper presents innovative methodology to coordinate the microgrid storage capacity with EV smart charging strategies and demand response schemes, in order to improve microgrid resilience in the moments subsequent to islanding and reduce the non-served load. The effectiveness of the proposed algorithms are validated though extensive numerical simulations.