Abstract
The idea behind the first proposal of the Fuzzy Power Flow (FPF) was to analyze the impact of the uncertainties in load and generation at the power flow level, when no statistical information is available. Further development of the field addressed the optimal power flow problem and the use of fuzzy methodologies to help planners of the composite generation-transmission system. In a market environment, transmission system adequacy may be defined as the ability of the system to meet reasonable demands for the transmission of electricity. The starting point of this paper is that FPF can be used as a tool to quantify this adequacy, without the need of making too many assumptions about load and generation uncertainties. However, some changes in the basic concept of the FPF are needed in order to accomplish this task - part of the paper is devoted to the description of the adequate formulation. We'll also show that this formulation can be used both in the normal operation situation and in the reliability evaluation of the transmission system. An illustrative example completes the paper.

Abstract
The emergence of micro-generation as a technically sound alternative has lead, in recent times, to the concept of microgrid, a network of LV consumers and producers able to export electric energy in some circumstances and also to work in a isolated way in emergency situations. Research work about the organization of microgrids, control devices, functionalities and other technical and economic aspects is presently being carried out, in order to establish a consistent technical framework to support the concept. Among other aspects, the effect of microgrids in the reliability of the distribution network has been pointed out as an important advantage, due to the ability of isolated operation in emergency situations. In order to address this topic, the present paper identifies the situations where the existence of a microgrid may reduce the interruption rate and time and thus improve the reliability indices of the distribution network. The relevant expressions necessary to quantify the reliability are also presented. An illustrative example is included, where the global influence of the microgrid in reliability is commented.

Abstract
Classifying consumers, namely LV consumers, in order to assign them typical load diagrams, was always a concern of the electric utilities, which used this kind of information to better manage their distribution networks. Now, with the transition to a completely open market, the need for settlement between distribution operators and traders requires hourly consumption records that are not generally available, so deriving load diagrams for LV consumers is a mandatory task. This paper presents a new methodology for this purpose that uses typical diagrams obtained in measurement campaigns to create classes defined in the commercial information space that maximize the compactness of the diagrams in each class. The methodology was developed in a project with EDP (the Portuguese distribution operator) and the result will probably be adopted by the regulatory authority. © 2005 ISAP.

Abstract
The application of artificial neural networks or other techniques in load forecasting usually outputs quality results in normal conditions. However, in real-world practice, a remarkable number of abnormalities may arise. Among them, the most common are the historical data bugs (due to SCADA or recording failure), anomalous behavior (like holidays or atypical days), sudden scale or shape changes following switching operations, and consumption habits modifications in the face of energy price amendments. Each of these items is a potential factor of forecasting performance degradation. This paper describes the procedures implemented to avoid the performance degradation under such conditions. The proposed techniques are illustrated with real data examples of current, active, and reactive power forecasting at the primary substation level.

Abstract
Pitch control has so far been the dominating method for power control in modern variable speed wind turbines. This paper proposes an improved control technique for pitching the blades of a variable speed wind turbine, using Artificial Neural Networks (ANN). The control objective is decided according the two states of operation: below rated operation and above rated operation. In the below rated power state, the aim of control is to extract maximum energy from the wind. In the above rated power, the control design problem is to limit and smooth the output electrical power. A model has been constructed and evaluated with experimental data obtained from Vestas V-47 660 kW wind turbine.

Abstract
This paper describes a model to perform transmission expansion planning studies together with the computation of Long Term Marginal Prices along the planning horizon. The model includes four criteria and adopts a Simulated Annealing based algorithm to solve the problem. The algorithm also provides Long Term Marginal Prices reflecting both investment and operation costs, thus being able to conveniently address the Revenue Reconciliation Problem that would arise if short-term approaches were used. The paper includes a case study based on the 400/220/150 kV Portuguese transmission system to illustrate the application of the proposed algorithm and highlight its potential.