Abstract
In this paper we describe a new approach to identify the combination of tap transformer positions, capacitor bank steps together with the minimum amount of toad to be shed that assures one to obtain a specified security degree of a power system. The basic approach is designed to identify the most adequate actions to be taken for a given contingency. This identification procedure uses Genetic Algorithms given their adequacy to model discrete actions. However, Genetic Algorithms are known for their usually large computation time. In order to address this issue and having in mind the objective of developing a real time tool, we incorporated a classification procedure based on Neural Networks. The paper includes results obtained using the developed approach both to evaluate the quality of the solutions for a number of contingencies and the quality of the overall performance when using the Neural Network tool. Results obtained for a reduced version of the Brazilian Mate Grosso transmission system are presented and discussed.

Abstract
In this paper we describe an application corresponding to a DMS system - Distribution Management System - that is organized in terms of a distributed multitask client-server architecture. The system is implemented according to the Object Oriented paradigm leading to a number of objects related with electric devices and specific algorithms. At this level of development, these algorithms correspond to topology processor, state estimation, power flow and short circuit analysis. They correspond to main coordinator objects that can be achieved by clients of the system in terms of Java applets running within a WEB browser. fn the paper we detail the structure of the system and describe some objects and applications.

Abstract
In this paper several concepts related to the application of Monte Carlo simulation to evaluate reliability indices of composite power systems are reviewed. In the sequence of previous papers, one integrates in the Monte Carlo simulation a DC Fuzzy Optimal Power Flow model to cope with uncertainties in peak loads. This general framework is now enhanced as one can specify fuzzy load duration curves, uncertainties in repair and failure rates and can adopt either non-chronological or chronological sampling strategies. This package can thus be used to evaluate the impact in the expected values of Power and Energy Not Supplied of uncertainties affecting several variables and parameters.

Abstract
The deregulation of the electricity industry places a number of complex questions related namely with planning and operating activities. In this paper one will enumerate some of these issues and give an overview about the way this process is being handled in several countries. In the paper one will also describe a methodology to identify the most adequate components to be reinforced considering that one aims at reducing the risk felt by the planner if loads are modeled by fuzzy numbers. At the end, fuzzy concepts are integrated in a model to validate from a technical point of view a set of trades established between electricity buyers and sellers in a competitive environment.

Abstract
In this paper one reviews some concepts related to fuzzy load modeling namely dealing with correlated and uncorrelated models. After briefly describing DC and AC fuzzy power flow models, one addresses the problem of integrating information about correlations between node consumptions or injections in these models. This information will lead to a correction phase performed after running the previous models. This correction phase is organized as a linear programming problem solved in a very efficient way as one takes advantage of the special structure of the problem. The methodology will be illustrated using a case study based on the IEEE 24 bus/38 branch Test System.

Abstract
This paper describes the methodology developed to build estimates of electricity prices having the horizon of one week. This approach uses artificial neural networks and includes a particular treatment of weekends and national holidays as a way to improve the quality of the results. The developed approach was tested using data obtained from the Spanish market operator for the time period of 2006 to 2008. The obtained value of MAPE - Mean Absolute Percentage Error - was 12,62% for workdays and 10,73% for holidays and weekends. The obtained results show that this study has interest to the market agents in question, since realistic forecasting was achieved.