Abstract
This paper describes an integrated wind farm maintenance system, including software, hardware and some algorithms. The approach will imply the optimization of the maintenance planning among different wind towers owned by a company, considering the management of situations where the distances among them have a considerable weight in the maintenance costs. This reason, associated to the generators accessibility and the on-line maintenance variables acquisition, are very important to justify the necessity of improvement of the maintenance planning. This objective is achieved through the application of integrated maintenance management systems to which are associated new functionalities, in parallel with the usual ones in these systems that fit within the on-condition predictive maintenance, including on-line data acquisition modules. Usually, the manufactures construct, deploy and give the means to the suppliers to perform the wind system's maintenance. In some cases, the owners of wind farms can choose the maintenance company. This is a very competitive area, where companies hide the development details and implementations. Another important factor is that, by the first time in last ten years, the three countries with the largest installed power, together, have fallen to a minimum historic, below 40% of the market for wind power in the EU. Definitively, the other European countries encouraged the appearing of programs for installing wind power, with prominence for Italy, Portugal and Netherlands. Within this scenario, the development of maintenance management models for multiple wind equipments is important, and will allow countries to be more competitive in a growth market.

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.