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.

Abstract
In the last years, the electric power systems have been restructured, moving from a vertical integrated model to a market oriented environment. The new paradigms associated with the restructuring of the electricity sector made it critical to develop new efficient and reliable methodologies to study and analyze the security of the power networks. In this paper it is proposed a method to evaluate the impact of external elements on the responsibility area of a Transmission System Operator (TSO) using the influence factor method. This approach offers a concrete support in the determination of the observability area, which at the end remains in the responsibility of the single TSO. The influence factor is a numerical value used to quantify the greatest effect of the outage of an external network component on any internal network branch. The developed methodology was applied to study the IEEE 118 bus test power network. All simulations of the transmission systems of the IEEE 118 bus were performed using the PSS®E software package from Siemens PTI, making the division of the network in two countries (areas). From the simulation results, some conclusions that provide a valuable contribution to understanding the influence factor method are pointed out. © 2012 IEEE.