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. 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.

Abstract
In this paper it is studied the influence of the transient stability performance indices on a contingency screening and ranking algorithm. The proposed methodology consists of three modules, with different complexity levels. Due to the large number of contingencies scenarios and calculations required, the application of a hybrid method to assess the system stability reduces drastically the computing time. The single dynamic security indices are obtained as a sub product of the hybrid method with a very reduce computing effort. The composed security indices are evaluated combining the single dynamic indices using weights. These indices are used to select, classify and rank the contingencies in accordance with the system security level. The developed methodology was applied to study the transient stability of the IEEE 17 machines test power system.

Abstract
This article covers a rather innovative and powerful technology that enables the creation of a 3D interactive laboratory for WEB applications based on open standard VRML format for 3D multimedia and the subsequent distribution of this virtual laboratory on the Internet. The project develops an environment, called "interactive technology of a 3D Internet Laboratory" to create various types of 3D laboratory experiments as well as their application via the Internet. The application produced is the creation of a 3D virtual laboratory for measurements and instrumentation. The description of the laboratory, fonts and data are also provided. The various steps for creating a 3D virtual laboratory are presented. Lastly, the application of the "interactive technology laboratory 3D" is displayed and can be considered as a step forward in the development of innovative technologies for distance learning. © 2011 University of Maribor.

Abstract
Electrical utilities are confronted daily with unpredictable events in their grids, which may lead to severe security level repercussions in the system, far exceeding all the security principles used for operation and consequently jeopardizing the essential service to the consumers. Incidents are unpredictable disturbances and recent experiences prove that severe contingencies happen. Given these facts, the need to evaluate harsher contingencies arose and such analysis must be rigorous and exhaustive. The security principles used for planning and system operation determine that, given an incident in the Electrical Power System (EPS) which involves the breakdown of any grid element or the simultaneous failure of a double circuit overhead line or the failure of the largest generator in service the supply interruption shall never take place (excluding single-feeding points without alternative) or permanent overloads. To analyse the steady-state security of an EPS it is required too, accurately and efficiently identify the critical contingencies set, i.e., those that when occur may endanger the system's security. The steady-state simulations of the Portuguese Transmission System (PTS) were made in PSS/E software from Siemens PTI using snapshots that represent pictures of the real system. All these security studies produce a large amount of data and information. Recently, the Rough Sets Theory (RST) has been used successfully to handle efficiently problems where large amounts of data are produced. RST constitute a framework for inducing minimal decision rules. These rules in turn can be used to perform a classification task. The main goal of the rough set analysis is to search large databases for meaningful decision rules and finally acquire new knowledge. This approach is based on four main topics: Indiscernibility, Approximation, Reducts and Decision rules. A reduct is a minimal set of attributes from the whole attributes set that preserves the partitioning of the finite set of objects and therefore the original classes. It means that if the redundant attributes are eliminated the reducts are found. Decision rules extracted knowledge, can be used when classifying new objects not in the original information system. In this paper it is proposed an efficient study and contingency analysis in the PTS using the RST. The developed methodology produces a system operation classification, distinguishing in four possible states: normal, alert, emergency I and emergency II. These different operating states correspond to a four levels of security. The four states can be classified horizontally as secure, in normal state and insecure for the remaining ones. The computer programs SecurMining2.0 developed, were applied to the Portuguese test power network.

Abstract
Wind energy is the renewable energy source considered a hope in future as a clean and sustainable energy, as can be seen by the growing number of wind farms all over the world. With the huge proliferation of wind farms, as an alternative to the traditional fossil power generation, the economic issues dictate the necessity of monitoring systems to optimize the availability and profits. The relatively high cost of operation and maintenance associated to wind power is a major issue. Wind turbines are most of the time located in remote areas or located offshore and these factors increase the referred operation and maintenance cost. Good maintenance strategies are needed to increase the health management of wind turbines. The objective of this paper is to show the application of neural networks to analyze all the wind turbine information to identify possible future failures, based on previous information of the turbine. © 2011 Institute of Electrical Power.

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.