Abstract
In this paper it is simulated the effect of the circuit breakers reclosure in the transient stability of an electric power system using a new hybrid approach. This efficient and robust formulation combines both a time domain integration scheme to compute the initial system trajectory with the equal area criterion to obtain the transient stability margins and the critical clearing times, In this hybrid approach it is used a stop criterion to provide automatic and early termination of the simulations as soon as post-fault (un)stability are detected. The early termination algorithm assess the transient stability of the multimachine power network based on the concept of the dot products from the potential energy boundary surface method. The computer programs developed by the authors were applied to a multimachine test power network. The results obtained with this new hybrid formulation were compared with the solutions produced by a time domain simulation program. Finally, some conclusions that provide a valuable contribution to the understanding of the auto-reclosing effect in the transient stability problem are pointed out.

Abstract
In this paper, we present and compare two approaches to model supply and demand curves of a sealed-bid auction market. Both the Linear Hinges model and the Sigmo model are able to extract the relevant information from these bidding curves, without losing significant market information. We discuss their main similarities and important differences using an unified framework, to highlight their main strengths and weakness. A practical comparative study based on real supply functions from the Californian electricity market has been included to derive practical conclusions. © 2001 IEEE.

Abstract
This paper describes SGO, a management information system for bidding in deregulated electricity markets, developed for the Spanish case. SGO has a client-server architecture and consists of a set of integrated cooperative and flexible software tools for assisting the users during the whole bidding process: resources identification, bids generation, market performance characterisation, bidding strategy analysis and optimisation, generation of markets results reports and automatic performance monitoring for suggesting on-line corrective actions. © 2001 IEEE.

Abstract
This paper proposes a method to quickly and accurately predict the dynamic response of a power system during an under-frequency load shedding scenario. Emergency actions in a power system due to loss of generation typically calls for under-frequency load shedding measures to avoid potential collapse due to the lack of time in which to correct the imbalance via other means. Due to the slow and repetitious use of dynamic simulators the need for a fast and accurate procedure is evident when calculating optimal bad-shedding strategies A neural network (NN) seems to he an ideal solution for a quick and accurate way to replace standard dynamic simulations. The steps taken to produce a viable NN and corresponding results will he discussed.

Abstract
This text describes a real-world DMS environment in which intelligent tools and techniques such as neural networks, fuzzy sets and meta-heuristics (like evolutionary computing and simulated annealing) have given a strong positive contribution.

Abstract
Forecasting electric demand and its geographical distribution is a prerequisite to generate expansion planning scenarios for distribution planning. This paper presents a comprehensive methodology that uses a fuzzy inference model over a GIS support, to capture the behavior of influence factors on load growth patterns and map the potential for development. The load growth is spread over maps with cellular automate. The interaction with a scenario generator inputs data into a graph generator, which will serve as a basis for more classic network planning tools.