Abstract
Sabilizing control for power system stability has been applied to generators equipped with excitation controller and speed governor. Recently, power electronics-based control devices have been the focus of research and development for the improvement of dynamic stability. Power electronics control devices are utilized for control of the power flow on a transmission line or the reactive power in a power system. In this paper it will be presented a thyristor controlled series compensation strategy to improve the dynamic voltage stability of an Electric Power System. In this study it was simulated a significant load demand disturbance in a test power network. The Automatic Voltage Regulator of the generating units, the Under Load Tap Changer and loads were taken into account. The simulation results were obtained using EUROSTAG software package.

Abstract
This paper presents a transient stability preventive control technique based on a hybrid method. In order to maintain the power system security it is evaluated the generators output power that should be shift from the most unstable synchronous machines to the undisturbed units. The reallocation of the generators output power is carried out using an optimal power flow program. The hybrid method is a very important tool for the transient stability analysis, since it allows a fast evaluation of the stability limits and margins. This approach can also easily accommodate detailed models of the network devices and protective schemes. In order to validate the established mathematical models it was studied the transient stability of the New England test power network. The results obtained with the proposed methodology were compared with the solutions produced by another numerical formulation, showing a very close agreement.

Abstract
The significant increase of production of energy from renewable sources led to the necessity of developing new ways of exploration of the power systems. The evaluation of the intermittent of the renewable generation, which characterizes some of the renewable sources, such as wind power, becomes very important to assess its impact on the generation reliability of power systems. This paper studies and analyses the reliability impact of a Portuguese wind farm in the power system using a computer model which represents the Portuguese wind farm by a Markov process. The probabilistic model combines the stochastic characteristics of wind speed with the characteristics of the wind turbines. The transition between the operative and failed states of the wind turbines, characterized by failure and repair rates, are combined with wind behaviour to allow the calculation of some performance indices used on the analysis of the wind power output expectation of the Portuguese wind farm. Some results obtained with the model applied to a Portuguese wind farm are presented. The results show the modelling of the mind form in reliability studies and the use of the model to evaluate the generation states and their probabilities, allied to several reliability indices.

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
In this paper it is proposed an efficient contingency screening and ranking algorithm for assessment and classification of multiple contingencies of an Electric Power System using the Rough Set theory. The developed methodology produces a classification of the system operation in five possible states: normal, alert, emergency, in-extremis and restorative. These different operating states correspond to six levels of security: secure, alert, correctively secure, alert no correctable, emergency and restorative. The states can be classified horizontally as secure, that correspond to the normal state and insecure for the remaining ones. The developed computer programs, the SECURsySTEM were applied to the IEEE 118 busbars test power network and results are presented and analyzed.

Abstract
Maintenance management is a subject that, instead of reducing importance, with the increase of equipment reliability, it increases its role in the companies and obliges the increase of the level of demand of professionals involved because of the new technical and environmental demands. Sometimes, scientific developments anticipate the company's needs while other times it is the company that challenges science. The maintenance area is an example that offers challenges to both science and companies in order to optimize the performance of equipment and facilities. This is also the case of wind generators, because their expansion, evolution, maintenance and reliability guarantee, needs to be adequately articulated in order to maximize production time and, obviously, to optimize maintenance interventions. It is because of this kind of challenge that the authors are developing new methodologies in the area of wind generators that aims to optimize the cycles of production and, consequently, reduce other kinds of energy production. The new features include on-line measures and the corresponding on-time treatment, using algorithms based on time-series forecasting and wireless technology to transmit the signals. The prediction models uses regression techniques based on SVR, ARMA and ARIMA models, modified according to this specific case. The weather, conditions and the technical and construction characteristics of wind generators are only some variables that we have in account in the models that are under development. But, if these conditions are important, it is also very important to collect, read and treat data from sensors placed in wind generators that, because their geographic dispersion, and difficulty of transmission, must be solved adequately and conjugated with the above referred algorithms, in order to implement an adequate system. This is the ambit of the present article that reports a wide approach of a subject that usually is managed separately, this is, the hardware from one side and the prediction algorithms from other side. This is possible because the team has being researching and developing algorithms and an information system, since many years ago, around the terology subject that is a wider vision of maintenance. Then, the new methodologies, above mentioned, will be, later, incorporated through new predictive maintenance modules in an integrated maintenance management system called SMIT (Terology Integrated Modular System). The base of SMIT is accessed through a client-server system and a browser system that includes the main modules of a traditional system, as well as a fault diagnosis module, a non-periodic maintenance planning module and a generic oncondition maintenance module, among other innovations.