Abstract
In this paper a combined Monte Carlo-Hybrid Transient Stability approach for the dynamic security analysis of a multimachine power system is proposed. This approach evaluates a probabilistic measure of the transient stability, instead of just a particular response to a specified disturbance. Due to the large number of simulations required, the application of a hybrid method to assess transient stability reduces drastically the computing time. A probabilistic version of the software package TRANsySTEM, developed by the authors to study the transient security of a multimachine system, was applied to a test power network. During the simulation time, the occurrence of disturbances and the subsequent protective actions are assumed as a stochastic process. Finally, the obtained results are discussed and some conclusions that provide a valuable contribution to the understanding of the system dynamics are pointed out. © 2001 IEEE.

Abstract
In this paper it is presented a study were the Rough Set Theory is applied to evaluated a set of the new severity index. The developed methodology produces a classification of the system operation in four possible states: normal, alert, emergency (emergency I and emergency II). The states can be classified as secure, that correspond to the normal state and insecure for the remaining ones. Severity indices are used to represent the impact of the reliable contingencies in electric power system Security studies. In this study the severity index are used to classify and ranked the contingencies. This methodology was applied to the 118IEEE busbar test power network, and the results obtained are analyzed. Finally, some conclusions that provide a valuable contribution to the understanding of the power system security analysis are pointed out. © 2010 IEEE.

Abstract
The maintenance costs associated with wind turbines assumes an important weight in the operation of wind parks. The main objective of wind farms operators is to run their parks most economically, to increase their profits. An adequate maintenance planning is essential to an effective operating costs reduction, compared with traditional maintenance techniques. Tools to detect the onset of mechanical and electrical faults in wind turbines at a sufficiently early stage are very important for well planned maintenance actions, because these actions can reduce the outage time and can prevent bigger faults that can lead to machine outage. The amount of information obtained from SCADA systems of wind farms is huge. The use of neural networks to deal with all the information and try to detect faults in some equipment in a early stage is a promising technique. © 2012 IEEE.

Abstract
All over the world, energy companies are investing in technologies to make better use of renewable energy to generate electric power. Wind energy is the renewable energy source that had a higher growing in the last decades and can be considered a hope in future based on clean and sustainable energy. The development of tools that allows operators and maintenance personnel to correlate machinery related information with other operational information such as machine speed, electrical load, and wind speed, are needed.

Abstract
Taking into account that the non renewable recourses are less and less available worldwide we need to use renewable energies to produce electricity. The wind energy is nowadays the most attractive renewable energy, after hydropower, to produce electricity. Wind energy is the renewable energy source that had a higher growing in the last decades and can be considered a hope in future based on clean and sustainable energy. All over the world, energy companies are investing in technologies to make better use of renewable energy to generate electric power. Wind energy is the renewable energy source that had a higher growing in the last decades and can be considered a hope in future based on clean and sustainable energy. Unlike conventional fuels, wind energy is a massive indigenous power source permanently available in virtually every nation in the world. Wind power delivers the energy security benefits of fuel costs, no long term fuel price risk, and avoids the economic and supply risks that can arise with reliance on imported fuels and political dependence on other countries. The problems resulting by the production of electricity using wind power and by the interconnection of wind parks to the grid are discussed in this paper.

Abstract
In a world with a global market that is continually increasing, the productivity management plays an important key role to keep the competitiveness. The productivity can be achieved through the availability that can be increased through the adoption of efficient maintenance practices, by focusing the organisations on adequate type of maintenance strategy. Condition Based Maintenance (CBM) uses primarily non destructive testing techniques, as environmental indicators, visual inspection, monitoring functioning variables and performance data. This kind of maintenance replaces tasks of scheduled maintenance by warranted interventions predicted by on-condition limits previously defined. The interventions occur only when the equipments presents abnormal symptoms. The intervals of CBM are determined based on the expected delay to fail and are managed through the frequency by which the predictive interventions have to be done. The technological advances are accepted and applied on CBM systems, which includes improved knowledge of failure mechanisms, advancements in, failure forecasting techniques, monitoring and sensor devices, diagnostic and prognostic software, communication protocols, and computer networking technologies. The measurement precision and sensitivity of the Condition Monitoring (CM) techniques are used because they affect the reaction time available to reduce or eliminate the consequences of the functional failure. CBM maintenance tasks must be applicable under the situation of cost effective improvement, including external costs. The base of development of this paper is supported by an integrated system called SMIT (Terology Integrated Modular System), that permits to manage the maintenance itself, including on-condition maintenance, but it is modular enough to permit to associate new features, namely this last approach, in order to maintain the system up-to-date and, always possible, to anticipate the future.