Abstract
From the studies developed so far, it is a general consensus that Electric Vehicles (EV), when properly managed, can provide many benefits to the grid operation. In the power systems of islands the potential benefits may be even larger. The case of S. Miguel Island, in the Azorean archipelago, may be one of such cases. This island achieves typically an annual peak power of 75 MW and a valley slightly higher than 30 MW. Currently, around 75% of its installed capacity is formed by fuel units, 22% by geothermal units and the rest by small hydro units. Yet, there are numerous unexplored endogenous resources in this place, especially geothermal and wind power, which cannot be used due to technical restrictions. Geothermal is limited by the valley load as the involved technology is not suited for load following, even with very small ramp rates. Wind power requires sufficient conventional spinning reserve to be safely integrated due to the variability of the wind resource. High EV integration, with an adequate charging management, would then increase base load allowing further geothermal and a reduced need for conventional spinning reserves. This paper evaluates the benefits of the presence of EV as controllable loads performing frequency control in a scenario with abundant wind resource availability, where a sudden loss of wind power production over a short period of time occurs. Ultimately, this work will show that S. Miguel power system would benefit from the presence of EV. A comparison with the conventional approach considering EV as regular loads will also be performed for benchmarking purposes.

Abstract
The massive interconnection of offshore Wind Farms (WF) brings challenges for the operation of electric grids. The predicted amount of offshore wind power will lead to a smaller ratio of conventional units operating in the system. Thus, the power system will have less capability to provide fast dynamic regulation. Despite of offshore WF being able to inject power on the AC grid through High Voltage Direct Current (HVDC) convertors, they cannot participate on frequency support by the intrinsic decoupling that DC adoption brings. This paper proposes a control methodology, based on local controllers, to enable the participation of offshore WF in primary frequency control. Additionally, enhancements were made on the Wind Energy Converters (WEC) controller to make them capable of emulating inertial behaviour. Tests were performed in a multi-terminal DC network with two off shore wind farms to assess the feasibility and effectiveness of the concept in a communication-free framework.

Abstract
The operation and planning of Low Voltage (LV) and Medium Voltage (MV) distribution networks have been changing over the last decade. Due to the presence of Distributed Generation (DG) and microgeneration, an active role has been attributed to these networks in grid operation. For this accomplishment, different conceptual approaches were developed. In [1], a hierarchical control structure was defined, considering that DG units, onload tap changer transformers, static var compensators and loads can be controlled by a hierarchically higher entity, the Central Autonomous Management Unit (CAMC). The CAMC is also responsible for the management of specific LV networks, the MicroGrids (MG), which in turn have autonomy to manage their loads and microgeneration units through an entity called MicroGrid Central Controller (MGCC). A MV grid with these characteristics plus some storage devices would then be called a Multi-MicroGrid (MMG), being, among other functionalities, able to operate isolated from the upstream network. The recent appearance of a new type of load to the system, the Electric Vehicle (EV), expected to be largely integrated in the electricity grids in the upcoming years, has a great potential for adding controllability to the MMG. In this paper, an EV control droop (see [2]) will be introduced to improve the MMG performance when EVs operate as active elements. EV controllers are then able to receive setpoints from the CAMC and also actively update the droop settings in order to deal with different events that may occur on the MMG, for instance when moving from interconnected to islanded mode of operation. The performance of the MMG with controllable EV will be compared with a MMG without the participation of EV. Additionally, multiple philosophies for setting the droops will be tested, considering that EV may inject power into the grid as storage devices or just act as controllable loads. Simulation results were obtained exploiting a dynamic simulation platform developed using the EUROSTAG and MATLAB environments.

Abstract
The scope of this work is to find the best approach to control advanced inverters used to connect electric vehicles to the grid. Phase-locked Loop (PLL) is a grid voltage phase detection that makes use of an orthogonal voltage to lock the grid phase. This method is suitable for both single and three phase systems, although in single-phase, because they have less information, more advanced systems are required. The easiest way to obtain the orthogonal voltage system is using a transport delay block to introduce a phase shift of 90 degrees with respect to the fundamental frequency of the grid voltage. This method is known as Synchronous Reference Frame PLL (SRF-PLL). The use of inverse Park transformation is also possible. To lower the complexity and increasing the filtering of the output signals, methods using adaptive filters are a good alternative. For this approach, the use of a second order generalized integrator (SOGI) or Adaptive Notch filter combined with PLL, Enhanced PLL (EPLL) and Quadrature PLL (QPLL), leads to satisfactory results. © 2011 INESC Coimbra.

Abstract
This paper presents an original forecasting methodology for achieving the spatiotemporal future long-term expansion of small power photovoltaic (PV) systems in a region, taking into account the population density, ground usage and the type of small PV power application adopted. This methodology comprises three stages: a first stage based on a suitable PV technological forecasting method with a group of experts; a second stage consisting of an innovative and iterative process based on elimination of the possible numerical inconsistencies achieved in the first stage; a third stage with a new method for achieving PV power density maps, using a geographical information system (GIS), that provides significant quantitative GIS information and visual and geographically-disaggregated representation of future small power PV systems expansion. The proposed methodology is illustrated with a real example for the region of La Rioja, Spain. In this example, four different combinations of PV systems and geographical zones were considered, and they are referred to as four "PV technologies" in the paper. The forecasted period range was 20 years with steps of 5 years. The results offer very valuable information for electric utilities, PV systems sales and installation agents, investors and regional authorities responsible for energy plans.

Abstract
The uncertainties related to when and where electric vehicles will charge in the future requires the development of stochastic based approaches to identify the corresponding load scenarios. This paper describes a tool based on Monte Carlo techniques to be used for distribution grid planning, providing a characterization of possible grid operation conditions, regarding voltage profiles, branch loading, grid peak power and energy losses. A medium voltage network based on real data is used to illustrate the application of the developed methodology.