Abstract
Transmission system operators have to consider multiple contingencies in the security analysis whenever lightning or active forest fires exist or are expected, in order to be prepared and prevent harmful situations. This paper presents a method to integrate multiple contingencies in the security analysis. ©2010 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
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
Nowadays most of the transmission systems' operating conditions are more stressed due to the introduction of a competitive environment in the power system industry and the regulatory changes causing the unbundling of generation, transmission and distribution, the environmental concerns, which limit the construction of new transmission lines and generation capacity, and the strong incentives to the generation through renewable energy sources. The use of methodologies that take advantage of the actual real-time conditions in combination with past knowledge is extremely interesting in the system operation's environment, because it gives a more accurate overview to the control room operators allowing them to prevent harmful situations. Obviously, this type of methodologies has received even more interest after the large disturbances which occurred in recent years, because they increase the awareness about the risk of unpredictable disturbances. Recent international data show that the frequency of large blackouts has increased and also that simple initiating faults can have very severe consequences. References [1-4] present a few examples of severe disturbances, which occurred in the recent past. Despite all the efforts being done regarding supervisory practices, operation strategies and protection and control systems' improvements, it is technically and economically impossible to eradicate major disturbances and blackouts. They will be a permanent threat to the electrical power systems, making incident analysis a crucial activity. The risk assessment methodology that is being developed is composed of two parts: probability of occurrence and severity for all contingencies under analysis. This paper aims to present the complete probabilistic model used to calculate the probability of occurrence of contingencies, including overhead lines, transformers and busbars. N-2 common cause contingencies are also considered for faults caused by lightning and forest fires.

Abstract
Wind energy is the renewable energy source with a higher growing rate in the last decades and can be considered a hope in the future as a clean and sustainable energy. 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 availability and profits. Tools to detect the onset of mechanical faults in wind turbines at a sufficiently early stage are very important for maintenance actions to be well planned, because these actions can reduce the outage time and can prevent bigger faults that may lead to machine stoppage.

Abstract
Trajectory sensitivity analysis can provide valuable insights into the security of an electric power system. There is a strong correlation relating the system stability and the corresponding trajectory sensitivity. In this paper it is analyzed the influence of load shedding in the voltage stability of an electric power system using trajectory sensitivity analysis. It is recognized that voltage instability and collapse have led to major system failures. The emergency load shedding is one of the most important methods to preserve the system stability. In this study different values of load shedding were used to avoid voltage collapse. The automatic voltage regulators of the generating units and the turbine speed governors were modelled. Different load models were used and the under load tap changers were also taken into account. The simulation results were obtained using EUROSTAG program and post-processing module developed using the Matlab software package.