Abstract
The development of techniques under geographical information system (GIS) platforms, such as geocomputational modeling, which increase the capabilities of GIS, allowing the systems to adapt to optimal distributed generation (DG) planning studies, is discussed. Using adequate software under the GIS platform, users can obtain useful information on the economic or technical viability of any distributed power generation facilities. GIS offers a variety of structured data models suitable for the storage, manipulation, and analysis of the information needed in DG planning. GIS can also be used in DG planning to study negotiation processes among different energy actors to look for geographical planning solutions.

Abstract
This paper presents an overview of a simulation platform for studying the behavior of energy retail markets where multiple energies enter in competition. This platform is based on autonomous agent techniques. The simulations include agents representing Residential, Commercial and Industrial Consumer Groups, Electricity, Gas, Heat Retail Suppliers and Energy Deliverers, Regulators, Market Operators, Economy and Information Environment. Each pursues its own interests and from their interaction a complex collective behavior emerges. Agents formulate their strategies namely by inner complex simulation process that try to guess other agent move s and define optimum decisions in energy purchasing, price fixing, market share wining, investing and capturing new consumers, among other. The process works on a FIPA complying platform being able to run in a parallel cluster machines.

Abstract
This paper presents the structure of a negotiation aid system (NAS) to select the best locations for new DG facilities, using sophisticated spatial techniques [based on geographical information systems (GISs)] and decision aid methodologies for negotiation, based on consensus among groups that may have conflicting interests. This system helps to overcome the problems posed by initially opposing positions stemming from diverse technological, economic, environmental and/or social interests. The NAS use is illustrated with results from a negotiation process between two groups to select locations for new wind farms in the region of La Rioja, Spain.

Abstract
The power flow is the fundamental tool for the study of power systems. The data for this problem are subject to uncertainty. This paper uses interval arithmetic to solve the power flow problem. Interval arithmetic takes into consideration the uncertainty of the nodal information, and is able to provide strict bounds for the solutions to the problem: all possible solutions are included within the bounds given by interval arithmetic. Results are compared with those obtainable by Monte Carlo simulations and by the use of stochastic power flows. Object oriented programming techniques make it possible to use interval arithmetic with minimal modifications to existing software. However, to reduce the conservatism inherent in all interval curtest computations, the paper describes an iterative method used to obtain the "hull" of the solution set.

Abstract
The paper describes a new methodology for mapping a neural network into a rule-based fuzzy inference system. This mapping makes explicit the knowledge implicitly captured by the neural network during the learning stage, by transforming it into a set of rules. The method is applied in transformer fault diagnosis using dissolved gas-in-oil analysis. Studies on transformer failure diagnosis are reported, illustrating the good results obtained and the knowledge discovery made possible.

Abstract