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 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
The letter describes a new economic dispatch algorithm for systems with uncertain wind generation prediction, similar to the classical thermal dispatch model with load on a single bus. The optimization is achieved in a compromise between fuzzy constraints in the magnitude of wind penetration and the variation of running costs. The model includes also the attitudes of the dispatcher toward risk (security) and cost.

Abstract
This paper presents a new multicriteria decision aid system (DAS) to obtain acceptable power line paths integrating the diverse socioeconomic interests of the different groups involved in the planning process, such as utilities, environmental agents, or local and regional authorities. The DAS is based on the intensive use of geographic information systems, as well as multicriteria weighting techniques reflecting all group interests. This new DAS can be used to overcome the problems raised by initially opposing positions among different groups stemming from diverse technological, economic, environmental, and/or social interests. The technique is illustrated by an intensive simulation example from a case study reproducing some of the phases of a negotiation process.

Abstract
The paper describes how mapping a neural network into a rule-based fuzzy inference system leads to knowledge extraction. This mapping makes explicit the knowledge implicitly captured by the neural network during the learning stage, by transforming it into a set of rules. By applying the method to transformer fault diagnosis using dissolved gas-in-oil analysis, one could not only develop intelligent diagnosis systems, providing better results than the application of the IIEC 60599 Table, but also generate a new rule table whose application also leads to better diagnosis results.