Abstract
This text presents an overview of the basic concepts of a Neuro-Fuzzy inference system for spatial Offer-and-Demand forecasting of electric power on a geographical basis, over GIS (Geographical Information Systems).

Abstract

Abstract
In distribution networks, the problem of finding the radial configuration that minimizes losses is usually solved for the peak load scenario, since this is the worst case situation regarding both losses and network loading. In general, the solution will remain optimal for other load levels, provided that there is an homothetic load variation. However, in some situations, the load pattern in the entire network may change during the day, or in seasonal periods, leading to situations where the solution is not optimal outside the peak period, or outside a specific period. On the other hand, the presence of dispersed generation directly connected to the distribution network may also contribute to these situations. This paper addresses this issue by considering a set of load scenarios and finding single or multiple configuration solutions that minimize both energy losses and switching actions, in a bicriteria framework. The optimization engine uses a Simulated Annealing algorithm previously reported to give good results in this class of problem |1]|2|. The methodology is illustrated with an example. © 2001 IEEE.

Abstract
In this paper, preliminary results from MORE CARE, a European R&D project financed within the Energy Program are described. This project has as main objective the development of an advanced control software system, aiming to optimize the overall performance of isolated and weakly interconnected systems in liberalized market environments by increasing the share of wind energy and other renewable forms, including advanced on-line security functions. The main features of the control system comprise advanced software modules for load and wind power forecasting, unit commitment and economic dispatch of the conventional and renewable units and on-line security assessment capabilities integrated in a friendly Man-Machine environment. Pilot installations of advanced control functions are foreseen on the islands of Crete, Ireland and Madeira. © 2001 IEEE.

Abstract
Due to their efficiency and their interesting design and implementation features, metaheuristics have been used for a long time with success, in dealing with combinatorial problems. In recent years they have been applied to the Unit Commitment problem with rather interesting results that justify further research in the area. In this paper we present a Simulated Annealing approach to the Unit Commitment problem. Two coding schemes are compared, new neighbourhood structures are presented and some searching strategies are discussed. Preliminary computational experience, performed on some test instances, shows that this approach is flexible, effective and able to handle variations on the problem structure. © 2001 IEEE.

Abstract
Very often, in dependability evaluation, the systems under study are assumed to have a Markovian behavior. This assumption highly simplifies the calculations, but introduces significant errors when the systems contain deterministic or quasi-deterministic processes, as it often happens with industrial systems. Existing methodologies for non-Markovian systems, such as device stage method [1], the supplementary variables method or the imbedded Markov chain method [2] do not provide an effective solution to deal with this class of systems, since their usage is restricted to relatively simple and small systems. This paper presents an analytical methodology for the dependability evaluation of non-Markovian discrete state systems, containing both stochastic and deterministic processes, along with an associated systematic resolution procedure suitable for numerical processing. The methodology was initially developed in the context of a research work [3] addressing the dependability modeling, analysis and evaluation of large industrial information systems. This paper, extends the application domain to the evaluation of reliability oriented indexes and to the assessment of multiple components systems. Examples will be provided throughout the paper, in order to illustrate the fundamental concepts of the methodology, and to demonstrate its practical usefulness.