Abstract
Large-scale deployment of renewables in island power systems is attracting local attention of grid operators as a way of reducing fuel fossil consumption. Planning a grid based on renewable power plants poses serious challenges to the normal operation of a power system, namely on frequency and voltage stability. Regardless of its inherent problems, there is a consensus that in a future not far away, the green energy could supply most of local needs with less production based on fuel burning. In past grid code compliance, wind turbines did not require services for supporting grid operation. To shift to large-scale integration of renewables, the island grid code should incorporate a new set of requirements in order to regulate the inclusion of these services. Hence, this paper focuses on grid code requirements for large renewable energy integration based distributed generation in island power systems. The paper also discusses additional requirements such as "virtual" wind inertia for improving regulation capability of wind farms and electric energy storage applications for better renewable generation performance. Moreover, a comparative analysis of insular grid code compliance to these requirements in European context is presented.

Abstract

Abstract
The success of neurosurgery strongly depends on the pre-neurosurgical evaluation phase, in which the delineation of the areas to be removed or to be stimulated must be very accurate. For patients undergoing Deep Brain Stimulation (DBS) it is vital the delineation of the target area prior to surgery, and after the implantation of the DBS lead to confirm the electrodes positioning. In this paper we present a system to accurately determine the 3D position of DBS electrodes implanted within the brain of Parkinson and Dystonia patients. The system was tested using a multimodal dataset from 16 patients (8 with Parkinson's disease and 8 with dystonia) and, on average, the differences between the detected electrodes positions and the ones estimated manually by an experienced physician were less than a voxel in all cases. Copyright

Abstract
The Electric Vehicle (EV) is one source of flexibility to the electric power system. When aggregated by a market agent, it can offer its flexibility in the balancing reserve market. In order to meet this goal, a framework of optimization and forecasting algorithms must designed to cover the different time horizons of the decision process. This paper describes a full framework for EV aggregators participating in different electricity market sessions. This framework is illustrated for the balancing reserve market and the impact of forecasts of different quality for the balancing reserve direction is evaluated. The test case consists in synthetic time series generated from real data for 3000 EV participating in the Iberian electricity market.

Abstract
Combining conventional and unconventional generations with hard forecasting properties and consumption variability has made the task of fitting large amounts of wind generation into unit commitment procedures very challenging. In this context, massive integration of electric vehicles in the electric systems, is expected. This paper aims at evaluating the adequacy of a generating system taking into account the electric vehicles and high wind power integration level in its energy mix. This study was conducted on the European project MERGE framework, and the results have shown that the generating system evaluated is reliable. Nevertheless, the simulations carried out for scenarios with adverse weather conditions (dry years) have revealed specific circumstances that might jeopardize the system adequacy.

Abstract
This paper presents an innovative and flexible approach for recommending the number, size and composition of purchasing groups, for a set of hospitals willing to cooperate, while minimising their shared supply chain costs. This approach makes the financial impact of the various cooperation alternatives transparent to the group and the individual participants, opening way to a negotiation process concerning the allocation of the cooperation costs and gains. The approach was developed around a hybrid Variable Neighbourhood Search (VNS)/Tabu Search metaheuristic, resulting in a flexible tool that can be applied to purchasing groups with different characteristics, namely different operative and market circumstances, and to supply chains with different topologies and atypical cost characteristics. Preliminary computational results show the potential of the approach in solving a broad range of problems.