Abstract
This paper presents the performed steps to design an Artificial Neural Network (ANN) tool, able to evaluate, within the framework of on-line security assessment, the dynamic security of interconnected power systems having an increased penetration of wind power production. This approach exploits functional knowledge generated off-line, the Linear Regression (LR) variable selection stepwise method to perform automatic Feature Subset Selection (FSS) and ANN to provide a way for fast evaluation of the system security degree. In order to choose the best input/output set of variables for the ANN tool, a comparative analysis is performed, regarding the obtained predicting error, by performing a statistical hypothesis test. The reduced error results confirm the feasibility and quality of the derived security structures.

Abstract
Microgrids comprise Low Voltage distribution systems with distributed energy sources, such as micro-turbines, fuel cells, PVs, etc., together with storage devices, i.e. flywheels, energy capacitors and batteries, and controllable loads, offering considerable control capabilities over the network operation. These systems are interconnected to the Medium Voltage Distribution network, but they can be also operated isolated from the main grid, in case of faults in the upstream network. From the customer point of view, Microgrids provide both thermal and electricity needs, and in addition enhance local reliability, reduce emissions, improve power quality by supporting voltage and reducing voltage dips, and potentially lower costs of energy supply. This paper outlines selected research findings of the EU funded MICROGRIDS project (Contract ENK-CT-2002-00610). These include: • Development and enhancement of Microsource controllers to support frequency and voltage based on droops. Application of software agents for secondary control. • Development of the Microgrid Central Controller (MGCC). Economic Scheduling functions have been developed and integrated in a software package able to simulate the capabilities of the MGCC to place bids to the market operator under various policies and to evaluate the resulting environmental benefits. • Analysis of the communication requirements of the Microgrids control architecture • Investigation of alternative market designs for trading energy and ancillary services within a Microgrid. Development of methods for the quantification of reliability and loss reduction. • Initial measurements from an actual LV installation.

Abstract
The use of wind energy has developed significantly worldwide. Wind power is the strongest growing form of renewable energy, ideal for a future with pollution-free electric power. But the integration of wind farms in power networks has become an important problem for the unit commitment and control of power plants in electric power systems. The intermittent nature of wind makes it difficult to forecast wind-produced electric energy in a wind farm even in the next hours. This paper compares the results obtained with a set of selected models for hourly electric power production forecasting in a real-life wind farm. The results show a significant improvement if previous numerical weather forecasts are used as input in hourly power forecasting models.

Abstract
The objective of this paper is to analyse the steady state and dynamic behaviour of a MicroGrid system containing one microturbine generating Combined Heat and Power feeding some small local loads in islanded mode of operation. Future operating scenarios were also analysed and simulated, namely considering the installation of photovoltaic panels near consumers.

Abstract
In this paper it is proposed a probabilistic stead-state security assessment of an electric power system using a Monte Carlo method. This approach evaluates a probabilistic measure of the system security, instead of just a particular response to a specified contingency. Performance indices are used to assess the impact of the contingencies in the power system security. These indices allow to accurately evaluate the influence of the overloads, voltage limit violations and voltage stability problems in the power network. A probabilistic version the SECURsySTEM software package developed by the authors was applied to the IEEE 118 busbars test power system. During the simulation time, the occurrence of contingencies and the subsequent protective actions are assumed as a stochastic process. Finally, some conclusions that provide a valuable contribution to the understanding of the power system security analysis are pointed out.

Abstract
With the development of electric power systems and their increase of complexity, basically due to the interconnection to other production centres, impose the necessity of introduction of new control system techniques. The efficiency of these control centres is only possible if data received from network arrives quickly and with accuracy. The basic task of a system operation is to get a reliable and accurate real time network model. In the past and even in the present, the real time network model is obtained by the use of System Control and Data Acquisition (SCADA) and processing of the SCADA data via state estimator algorithms. Today's reality is different, intelligent electronic devices (IEDs), digital fault recorders (DFRs), phase measurement units (PMUs) and relays, collects an enormous amount of data that arrives to control centres through SCADA system. So, other ways to validate and utilize this data are needed.