Abstract
Power systems with high wind penetration experience increased variability and uncertainty, such that determination of the required additional operating reserve is attracting a significant amount of attention and research. This paper presents methods used in recent wind integration analyses and operating practice, with key results that compare different methods or data. Wind integration analysis over the past several years has shown that wind variability need not be seen as a contingency event. The impact of wind will be seen in the reserves for nonevent operation ( normal operation dealing with deviations from schedules). Wind power will also result in some events of larger variability and large forecast errors that could be categorized as slow events. The level of operating reserve that is induced by wind is not constant during all hours of the year, so that dynamic allocation of reserves will reduce the amount of reserves needed in the system for most hours. The paper concludes with recent emerging trends.

Abstract
In this paper the contributions of the ELLEIEC project for the international dimension of Life Long Learning (LLL) are described. In the framework of the Thematic Networks Programme, tools such as Recognition of Prior Learning (RPL), the Tuning Methodology were used in the implementation of an International Curricula Network with accreditation by two European institutions at least. Benchmarks were proposed, in order to show various tools that can be used for the establishment of dual degree programmes

Abstract
With the development of synchronized phasor measurement technology in recent years, it gains great interest the use of PMU measurements to improve state estimation performances. In this paper, a mixed measurement (SCADA and PMU measurements) state estimator is proposed. Several measures useful for evaluating various aspects of the performance of the mixed measurement state estimator are proposed and explained. State Estimator validity, performance and characteristics of the results on IEEE 14 bus test system are presented. © 2012 IEEE.

Abstract
Nowadays, the large penetration of wind power generation poses new challenges for the dynamic voltage stability analysis of an electric power system. In this paper is studied the influence of the reactive power management for wind power plants in the dynamic voltage stability of an electric power network under a fault condition, considering two different Doubly-Fed Induction Generators (DFIG) models. The simulation results were obtained using the EUROSTAG software package.

Abstract
In this paper it is proposed a technique to identify the relevant neighbouring electric power systems using the Horizontal Network scheme. The developed methodology was applied to study the IEEE 118 test power network and the Iberian systems. All simulations were performed using the computational software package PSS®E developed by the Siemens/PTI. From the simulation results, some conclusions that provide a valuable contribution to the understanding of the impact of the cross-border interconnections between the countries will be pointed out.

Abstract
The huge proliferation of wind farms across the world has arisen as an alternative to the traditional power generation and as a result of economic issues which necessitate monitoring systems in order to optimize availability and profits too. Equipments inside a wind turbine are subject to failures which, most of times lead to long downtime periods. When wind turbine is not running due to a failure, no profits are added and operation and maintenance costs increases. The development of advanced techniques to detect the onset of mechanical and electrical faults in wind turbines at a sufficiently early stage is very important for maintenance actions. Neural networks can be used to detect failures in some equipments of wind turbines, but to use them is necessary to create a model to the equipment under surveillance. The training of the neural network represents the big handicap of the developed method that will be presented here. However, after solving this problem, results are very interesting, and failures can be detected with several months in advance. © 2012 IEEE.