Abstract
In this paper the main parameters to assess the power quality of grid embedded wind farms are presented. International standards to assess and quantify the power quality of grid connected wind turbines exist for some years now, and are here extrapolated to wind farms. aggregates when possible being the correspondent methodologies identified in the document. Recently, the grid code requirements posed a novel challenge to this technologic area, particularly since they were issued with national or local objectives and without particular normalized global concerns. The form how the international standards are evolving in order to cope both with the power systems industry local requirements, but also with the global wind turbine manufacturers principles is addressed in the paper.

Abstract
In this paper the existing technical barriers that prevent the accomplishment of a very high wind generation penetration in a power system are presented. Since several countries and regions in Europe are already experiencing such high wind penetration or, as a minimum, planning their grids and operation strategies to cope with wind penetration from a high to a very high level, the solutions already identified for the most common constraints are also identified.

Abstract
This paper presents a formulation for an Optimal Power Flow problem that includes the DFIG wind generator reactive power characteristics in order to obtain set points that consider wind turbines loading capabilities. This approach can be adopted at the wind park control level to define the active and reactive set points following requests from the wind park dispatch centers.

Abstract
This paper addresses the problem of large wind power integration and its impact on damping of the electromechnnical modes of oscillation. The viability of the doubly fed induction generator (DFIG) supplying additional damping is discussed and power system stabilizers (PSS) installed in DFIG wind power generators are simultaneously tuned to increase damping levels of a multimachine system.

Abstract
MicroGrids comprise low voltage distribution systems with distributed energy sources, storage devices and controllable loads, operated interconnected with the main power grid or autonomously, in a controlled coordinated way. Storage devices are absolutely essential for MicroGrid autonomous operation. However, depending on the operating conditions, their limited storage capacity is a major drawback and might compromise successful MicroGrid islanded operation. In this paper is proposed an index to evaluate MicroGrids security regarding an unplanned transition to islanded operation due to disturbances in the upstream Medium Voltage network. An Artificial Neural Network tool is proposed to forecast the security index for a credible range of operating scenarios. The usage of Artificial Neural Networks is emphasized due to its computational speed for on-line performance and its flexibility for providing corrective actions for insecure operating conditions in order to achieve a seamless transition from interconnected to islanded operation. © 2007 IEEE.

Abstract
Wind energy experiences in Portugal an increasing interest. Slightly more than 1700 MW were operating by the end of 2006, in a system with a global capacity of about 12 GW (8,5 GW peak demand). Several new wind farms are under construction and a considerable amount of connection points are or will be granted in the coming years. More than 5000 MW are expected to be connected to the grid around 2012, the global generating capacity being then about 16 GW. Clearly, a wind power forecasting system must be implemented that will help to deal with the significant penetration of the technology in the electrical system. A group of wind farm promoters, owning the majority of the capacity installed so far, ordered to a consortium of universities and research institutes the development of a forecasting tool, giving rise of the EPREV project, wholly financed by them. The system will have the following main characteristics: Wind speed and active power forecasting up to 72 hours; Evaluation of the forecasting uncertainty; Possibility of using the predictions of physical models and the information from the wind farm Supervisory Control And Data Acquisition (SCADA); Capacity of predicting only with SCADA information for very short term. The main components of the system are: A human-machine-interface, allowing the control of the system, the selection and aggregation of forecasting models and the visualization of results; A power forecasting model for individual wind turbines and for wind farms. A cascade of models is used, starting in the mesoscale simulation, with up to 2 km resolution. The outputs of the mesoscale models are corrected and statistically adapted to the fine scale conditions. Two models and different boundary conditions are run, in three nested domains (54x54, 18x18 and 6x6 km). The advantage of using a 2x2 km resolution is also tested. The statistical models are fed with recent information from the wind farms, after a learning process that made use of the historical information of its operation. Three different types of statistical models are employed: Power Curve Model (PCM), Auto Regressive (AR) and Neural Network Assembling Model (NNAM). The wind simulation at the wind farm scale is done both by linearized physical models and Computational Fluid Dynamics (CFD) models, namely using VENTOS®, a code developed at the University of Porto. The duration of the project is planned to be 1 year, including off-line tests of the complete system for 3 wind farms, for performance evaluation purposes.