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
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.

Abstract
This paper describes a Load Allocation model to be used in a DMS environment. A process of rough allocation is initiated, based on information on actual measurements and on data about installed capacity and power and energy consumption at LV substations. This process generates a fuzzy load allocation, which is then corrected by a fuzzy state estimator procedure in order to generate a crisp power flow compatible set of load allocations, coherent with available real time measurements recorded in the SCADA.

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
In this paper, an advanced control system for the optimal operation and management of isolated power systems with increased renewable power integration is presented. The control system minimises the production costs through on-line optimal scheduling of the power units, taking into account short-term forecasts of the load and the renewable resources. The power system security is supervised via on-line security assessment modules, which emulate the power system frequency changes caused by pre-selected disturbances. For each of the above functions, a number of techniques have been applied, both conventional and AI based. The system has been installed in the dispatch center of Crete since June 1999, and is under evaluation. © 2000 IEEE.

Abstract
This paper presents an approach for including nonstatistical uncertainties in engineering economic analysis, particularly utility economic analysis, by modeling uncertain variables with fuzzy numbers. In this case, the mathematical operations are defined by the extension principle and the results obtained are also in a form of fuzzy numbers. This approach can be seen as an extension of a previously proposed one that uses interval numbers and interval analysis for including such uncertainties. However, this paper considers also the dependence which may exist between the fuzzy variables and shows the impact this dependence may have on the results. In this context, a way of modeling partial correlation between the variables of the same kind is proposed.