Abstract
In the last years the importance of the security analysis has been increasing, due to economical and environment constrains. The operation of an electrical power system is a complex task due to the high degree of uncertainty and the large number of parameters involved. This paper is devoted to the presentation of an efficient steady-state contingency classification using the Rough Set Theory. The developed technique produces a classification of the system operating in four possible states. The powerful methodology developed was applied to a test power network in four different scenarios. The numerical results were compared and analysed in order to obtained important conclusions that provide a valuable contribution to the understanding of the power system security problem.

Abstract
Most power systems are nowadays operated very near to their operating limits due to increase in consumption, while economic and environmental constraints have limited construction of new generation facilities and lines. This paper is devoted to the analysis of the ULTC effect in the dynamic voltage stability of an electric power network. Usually substations are provided with transformers with tap-changers facilities. It was long believed that transformers with tap-changers could eliminate or minimize effectively voltage instabilities. In this study it is shown the influence of the ULTC in the voltage instability for some situations in the analysed power network. It was used the BPA test power network. A severe contingency situation was simulated. The automatic voltage regulators of the generating units and the turbine speed governors will be modelled. The simulation results were obtained using the commercial transient software package EUROSTAG. Finally some conclusions that provide a better understanding of the voltage collapse phenomena are pointed out.

Abstract
The increasing loads, the great distances between the production and consumption centers as well as the state of the transport and distribution networks turns the Electrical Power System operating near its stability limit. When the system gets instable a blackout situation may occur, which is critical to the system operator and consumers. We have recent examples in United States and Italy where the system was without power for several hours, causing serious problems in hospitals and public transportations. One of the causes of a blackout may be the Voltage Instability, which turns this subject widely discussed and studied. The speed of evolution of the Voltage Stability phenomenon allows us to analyze the problem as a static problem rather than a transitory one [1]. This article will show one way to "measure" locally the proximity of the system to the Voltage Stability Limit.

Abstract
Simple performance index for detecting and predicting stability problems such as the voltage collapse are useful analysis tools for planning and operating in power system. A new method for the detection of the point of collapse and a new index for the definition of the distance of the voltage collapse point are proposed. Numerical experiments using standard IEEE 14 and 57 bus systems show that the proposed method can compute the voltage collapse point using several different scenery of load increase. The methodology proposed may be easily implemented in any power flow program.

Abstract
In this paper it is proposed an efficient steady-state contingency classification using the Rough Set Theory. The developed methodology produces a classification of the system operating in four possible states: normal, alert, emergency I, and emergency II. The methodology developed by the authors was applied to a test power network and the results obtained were analyzed. Finally, some conclusions that provide a valuable contribution to the understanding of the power system security analysis are pointed out.

Abstract
This paper presents a comparative study between a new approach for robust speed estimation in induction motor sensorless control, using a reduced order Extended Kalman Filter (EKF), and the one performed by the full order EKF. The new EKF algorithm uses a reduced order state-space model that is discretized in a particular and innovative way. In this case only the rotor flux components are estimated, besides the rotor speed, while the full order EKF also estimates stator current components. This new approach strongly reduces the execution time and simplifies the tuning of covariance matrices. The performance of speed estimation using both EKF techniques is compared with respect to computation effort, tuning of the algorithms, speed range including low speeds, load torque conditions and robustness relatively to motor parameter sensitivity.