Abstract
In this paper we develop a theoretically robust and computationally efficient state estimator algorithm, to solve the WLS problem by using parallel processing. Technical developments in distributed Energy Management Systems (EMS), based on fast data communication networks, open up the possibility of Parallel Processing in the state estimation algorithms. We have analysed the computational aspects of the parallel processing. Moreover, we have simulated this state estimator parallel algorithm in the IEEE 30, 57 and 118 bus systems. The numerical accuracy of the simulation demonstrates the excellent computational performance of the parallel algorithm. Results of 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 also performed. The results of computational experiments indicate that a distributed processing for state estimation, is the better way to adopt the parallel computing in power systems energy.

Abstract
Simulation is a useful tool which can significantly reduce resources invested during product development. The present paper describes the development of the Vector Control Signal Processing (VCSP) blockset for use with MATLAB/Simuhnk(R). The originality of this blockset consists on the extension of Simulink for design, simulation and prototyping of signal processing algorithms in power conversion systems. The VCSP blockset, consists on a number of newly developed blocks. Together with Real-Time WorkshopTM and a number of other generally available blocks, it takes advantage of the inherent visual programming techniques of Simulink to reach the above goals. Due to its open and flexible nature, this approach is also very useful as a tool for teaching. The work is focused on modelling and simulation for power conversion systems use in the drive of rotating AC machines with vector control methods. By concept, a simulation environment can be examined at different abstraction or hierarchy levels. The approach in this paper is so the formulation of a simulation task at different levels: component level, electric circuit level, functional description and implementation description. The basic blockset functions are presented and some examples of modelling techniques for both simple and complex drive structures are included. Simulation results are presented and discussed as well.

Abstract
Electrical distribution utilities have been dealing with the problem of estimation of distribution network load diagrams, either for operation studies or in forecasting models for planning purposes. Load curve assessment is essential for an efficient management of electric distribution systems. However, the only information available for most of the loads (namely LV loads) is related to monthly energy consumption. The general procedure uses measurements in consumers to construct inference engines that predict load curves using commercial information. This paper presents a new approach for this problem, based on Kohonen maps and Artificial Neural Networks (ANN) to estimate load diagrams for the Portuguese distribution utilities. A method for estimating error bars is also proposed in order to provide a high order information about the performance of load curve estimation process. Performance attained is discussed as well as the method to achieve confidence intervals of the main predicted diagrams. © Springer-Verlag Berlin Heidelberg 1997.

Abstract
This paper shows the conceptual differences between adopting a probabilistic weighting of the futures and a risk averse strategy, in power system planning under uncertain scenarios. It is illustrated with a distribution planning problem, where optimal solutions in both cases are determined by a genetic algorithm. It shows that the probabilistic approach is less safe and cannot detect some interesting solutions.

Abstract
The classical long range distribution network planning problem consists on deciding network investments to meet future demands at a minimum cost, while attending technical constraints. The decisions whether to construct or reinforce substations and branches lead to a mixed integer programming problem with a great number of decision variables. Besides, the network injections have a fuzzy nature on account of the non availability of statistical data in what concerns future loads (namely in new areas and due to the presence of independent producers. Moreover several objectives must be taken into account. This leads to a fuzzy multiobjective, mixed integer problem. This paper presents a case study, adapted from a real network, that illustrates the application of an integrated methodology to deal with the planning problem. This case study aims into illustrating the proposed methodology and to point out its flexibility to adapt to the planner's needs.

Abstract
An advanced control system for the optimal operation and management of autonomous wind-diesel systems is presented. This system minimises the production costs through an on-line optimal scheduling of the power units, which takes into account the technical constraints of the diesel units, as well as short-term forecasts of the load and renewable resources. The power system security is maximised through on-line security assessment modules, which enable the power system to withstand sudden changes in the production of the renewable sources. The control system was evaluated using data from the island of Lemnos, where it has been installed and operated since January 1995. © 1997 Elsevier Science Ltd.