Abstract
This paper valuates generation assets within deregulated electricity markets. A new framework for modeling electricity markets with a Markov chain model is proposed. The Markov chain model captures the fundamental economic forces underlying the electricity markets such as demand on electricity and supplied online generation capacity. Based on this new model, a real option analysis is adopted to valuate generation assets. The Markov chain model is combined with a binomial tree to approximate the stochastic movement of prices on both electric energy and ancillary services, which are driven by the market forces. A detailed example is presented. This method is shown to provide optimal operation policies and market values of generation assets. This method also provides means to analyze the impacts of demand growth patterns, competition strategies of competitors, and other key economic forces.

Abstract
This paper provides a description of a new approach for steady state security evaluation, using fuzzy nearest prototype classifiers, The basic method has an off-line training phase, used to design the fast classifiers for on-line purposes, allowing more than the two traditional security classes. A battery of these fuzzy classifiers, valid for a specific configuration of the network, is adopted to produce a global evaluation for all relevant single Contingencies. An important feature of this approach is that it selects automatically the most appropriate number of security clusters for each selected contingency. Natural language-labeling is also used to produce standardized sentences about the security level of the system, improving in this way the communication process between the system and the operator. The paper is completed by an example on a realistic model of the Hellenic interconnected power system, where seven contingencies were simulated.

Abstract
The idea behind the first proposal of the Fuzzy Power Flow (FPF) was to analyze the impact of the uncertainties in load and generation at the power flow level, when no statistical information is available. Further development of the field addressed the optimal power flow problem and the use of fuzzy methodologies to help planners of the composite generation-transmission system. In a market environment, transmission system adequacy may be defined as the ability of the system to meet reasonable demands for the transmission of electricity. The starting point of this paper is that FPF can be used as a tool to quantify this adequacy, without the need of making too many assumptions about load and generation uncertainties. However, some changes in the basic concept of the FPF are needed in order to accomplish this task - part of the paper is devoted to the description of the adequate formulation. We'll also show that this formulation can be used both in the normal operation situation and in the reliability evaluation of the transmission system. An illustrative example completes the paper.

Abstract
The idea behind the first proposal of the fuzzy power flow (FPF) was to analyze the impact of the uncertainties in load and generation at the power flow level, when no statistical information is available. Further development of the field addressed the optimal power flow problem and the use of fuzzy methodologies to help planners of the composite generation-transmission system. In a market environment, transmission system adequacy may be defined as the ability of the system to meet reasonable demands for the transmission of electricity. The starting point of this paper is that FPF can be used as a tool to quantify this adequacy, without the need of making too many assumptions about load and generation uncertainties. However, some changes in the basic concept of the FPF are needed in order to accomplish this task-part of this paper is devoted to the description of the adequate formulation. We will also show that this formulation can be used both in the normal operation situation and in the reliability evaluation of the transmission system. An illustrative example completes this paper.

Abstract
One of the important decision problems for a power system operator is to choose the appropriate operation point when possible contingencies must be considered. The operator may decide to do nothing or to take some actions that change the operating point and decrease the negative impact (cost) of some or all the contingencies. The purpose of this paper is to investigate the applicability of utility and value functions to this decision problem, since the large range of consequences raises some doubts about the fulfillment of the theoretical conditions imposed by Decision Theory. Although not essential to this discussion, some alternatives to prescriptive methodologies are presented and discussed, mostly regarding the definition of risk attributes and other determinist equivalents, suitable for multicriteria analysis.

Abstract
Preliminary filtering of a large decision set can be an important issue in multicriteria problems. Besides eliminating dominated solutions, it is usual to define aspiration levels in some or all the attributes, and then eliminate all the solutions that do not respect the imposed limits. This procedure may lead to the undesired elimination of possibly interesting solutions, due to the irrelevant violation of a specified limit. In this paper, a new method is presented that overcomes this problem by defining the concept of accepted solution as a fuzzy set and calculating a degree of acceptance for each solution that takes values in the interval [0, 1] instead of having only the crisp {0, 1} values. The method also deals with fuzzy attributes, and has an additional feature of advising the decision maker regarding the definition of the acceptance level that leads to selection or exclusion of an alternative. To illustrate the application of the fuzzy filtering method (FFM), a planning problem in the area of power distribution systems is used. The example shows how FFM can be used to reduce an initial set of 48 plans, according to the expressed aspiration levels.