Abstract
This paper presents a new approach to perform on-line dynamic security assessment and monitoring of electric power systems exploiting a statistical hybrid learning technique - the Kernel Regression Trees This technique, besides producing fast;security classification, can still quantify, hi real-time, the security degree of the system, by emulating continuos security indices that translate the power system dynamic behavior. Moreover it can provide interpretable security structures. The feasibility of this approach was demonstrated in the dynamic security assessment of isolated systems with large amounts of wind power production, like In the Crete island electric network (Greece) Comparative results regarding performances of Decision Trees and Neural Networks are also presented and discussed. From the obtained results, the proposed approach showed to provide good predicting structures whose performance stands up to the performance of the two other existent methods.

Abstract
The State Estimation is nowadays considered the fundamental element of modern electrical power networks control centers. In this paper we develop a theoretically robust and computationally efficient state estimator algorithm, to solve the WLS problem by using parallel processing, The computational aspects of the parallel processing, was analyzed and tested using the IEEE 14, 57 and 118 bus systems. Computational experiments are compared with standard WLS methods, in the integral and distributed version. An evaluation of the degree of natural decoupling in the state estimation problem is rise performed. The results indicate that a distributed processing for state estimation, is the better way to adopt the parallel computing in power systems energy.

Abstract
Today, the State Estimation is considered as the heart of nearly all modern network control centers. Among other factors, the technical developments in fast data communication network technology opens up the possibility of parallel and distributed implementations of the state estimation function. This paper provides an overview of the state of the art in Power Systems State Estimation.

Abstract
The software package TRANsySTEM developed for teaching and research purposes of the transient security assessment of a multimachine power system is presented. This package run in Windows environment.

Abstract
In this paper it is presented a combined on-line hybrid transient stability formulation with a parallel processing state estimator. The transient stability assessment uses a time domain integration scheme to compute the initial system trajectory and the equal area criteria to obtain the transient stability margins and the critical clearing times. The state estimator that provides the pre-fault operating conditions uses a parallel processing approach. In this technique the power system is split into K areas, and each subsystem is supervised by a local control centre. The measurements in each area are collected in the individual local control centre that has at least one computer system for data acquisition, data processing and computation. The computer programs developed by the authors were applied to a multimachine power network. The results obtained with the proposed formulation were compared with the solutions produced by other methods. Finally, some conclusions that provide a valuable contribution to the understanding of the multimachine power system preventive control are pointed out.

Abstract
A robust feedback control of an induction motor is proposed. The theoretical basis is a continuous-time machine model defined by a pair of simultaneous complex-coefficients differential equations. The parameter uncertainties and load perturbations are considered in the controller design. The control methodology is based on sliding mode control techniques. The design of a sliding mode controller for tracking the torque and the rotor flux of an induction motor drive is also given. The design includes the hardware structure, control laws for torque control and rotor flux control. The modulation is defined as part of the variable structure control algorithm which enables an optimum choice of the output voltage of the static converter. The validity and robustness of the proposed control system were verified by simulation. The simulation results are presented to demonstrate their agreement with the theoretical predictions of the proposed controller. Copyright (C) 2000 John Wiley & Sons, Ltd.