Abstract
This paper presents a new two-step algorithm to compute a conjectured supply function electricity market equilibrium with DC transmission network constraints. This approach generalizes a previous authors' model developed for the single-bus case. Unlike other approaches, its main contribution is that the parameters of the first order approximation of the conjectured supply functions (intercept and slope) are endogenously determined, coherently with the network lines status. Nodal prices are used to split the market into single prices areas. Each area is treated as a single-bus market from the transmission constraints point of view, and the authors' single-bus algorithm is applied to compute the generators supply functions for each area. These new generators strategies are then cleared to determine new nodal prices and areas for the next iteration. Convergence is achieved when the network lines status and strategies of the generators do not change significantly in two consecutive iterations. The algorithm has been tested with some illustrative case examples, and with a simplified version of the MIBEL market (Spain-Portugal). © 2011 IEEE.

Abstract
Electricity physical and financial contracts are common instruments used by generators to reallocate their risk among other market participants. Likewise, from the regulator point of view, contracts are understood and promoted as a way to mitigate the generators market power exercise. Therefore the analysis of the impact of these derivatives on the electricity market prices and on the agents' strategic behavior is of interest for both regulator and market participants. This paper focuses on how physical and financial electricity contracts affect the generators' strategies, but does not deal with determining contracts' quantities or prices, that are assumed to be fixed and known. Strategies are computed for selected agents and different physical or financial contracted quantities, assuming inelastic demand. A CSFE methodology for endogenous conjectures computation, developed by the authors in previous works, has been applied. The examples highlight the importance of computing the conjectures when the contracted quantities vary, since the variable agents' position can significantly change the market results. The main conclusion is that the common understanding that contracts can decrease the market prices may be called into question. © 2012 IEEE.

Abstract
Knowledge of the health of power transformers is important to prevent high costs caused by failures and to maintain the quality of the service. On-line monitoring and diagnosis seem to be the right way to reach this objective. In this paper a set of experiences related to the installation of vibration and temperature sensors inside a test transformer will be described. Different types of sensors have been tested, and some of them discarded because of induced electromagnetical noise. Some of the main results and conclusions are shown in this paper. These experiences are included in a more general project called TRAFES, whose main objective is the continuous monitoring and diagnosis of large power transformers.

Abstract
When inference is performed with the compositional rule of inference (CRI), fuzzy rules can be mathematically modelled by a pair of operators, the implication function and the modus ponens generating function, each pair being a possible model for the rule. Analyzing the firing condition of fuzzy rules, that is the condition the hypothesis and the observation must verify to infer a non trivial conclusion, it is possible to get a deeper understanding of the behaviour of the different models that can be used, and valuable semantical criteria can be obtained to select the best suitable model. The firing condition of any model can be expressed by means of a generalized possibility or necessity measure generated by its implication and modus ponens generating functions, measures that quantify the amount of uncertainty or possibilistic uncertainty of the conclusion. Two different types of possibility distributions can be identified as those concluded from different types of models, that is necessary and possible possibility distributions, corresponding to necessary and possible conclusions.

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.