Abstract
Back in 1999, the Power Systems Unit of INESC Porto concluded a consultancy study to estimate the remuneration that could be obtained by the Portuguese transmission provider using Short Term Marginal Prices. By that time the Regulatory Agency decided not to include a marginal based term on the Transmission Network Tariffs. However, that study was updated using information about the operation of the network in 2001 and recently it was concluded a new version of this study using information from 2004. This paper describes the models used in these studies, the assumptions that were adopted and the evolution of the marginal based remuneration that the Portuguese transmission provider could obtain if a marginal based tariff term existed. This evolution is important in order to get insight on the congestion level of the transmission network and on how neutral the transmission network is behaving in being able to physically implement the dispatches prepared by the Market Operator or related with bilateral contracts.

Abstract
This paper analyses and discusses the current situation in Portugal and in Spain regarding the procurement and the supply of the ancillary services considered in the Codes for the Operation of these two power systems. This is relevant because Portugal and Spain share a common day ahead and bilateral contract electricity market since 2007. However, several technical activities as the procurement and the provision of Ancillary Services are not yet entirely harmonized and fully integrated and continue to be provided within the control area of each country. Accordingly, this paper discusses three possible approaches that the two TSO's can adopt to further enlarge this integration. Then, tertiary reserve is taken as an example to illustrate the advantages that can be obtained if it is used a common list of bids from the two countries. The Case Study analyses four situations including the present mechanisms used to procure tertiary reserve, as well as the use of a common bid list admitting different values for the capacity of the interconnection lines between the two countries. Based on these results, the paper provides a discussion on the mentioned three integration models addressing their advantages and practical difficulties. © 2011 IEEE.

Abstract
This paper describes a set of mathematical formulations designed to include uncertainties modeled by fuzzy numbers in DC OPF studies. These approaches enhance and generalize an initial formulation and solution algorithm described in several papers co-authored by the second author. The approaches described in this paper adopt multiparametric optimization techniques in order to translate to the results the uncertainties affecting loads, for one side, the generation costs, for another, and also both of them in a simultaneous way. These approaches can be very useful nowadays given the uncertainties and volatility affecting data required to run several studies. They can also be the basis for the computation of nodal short time marginal prices reflecting these uncertainties. This paper also includes results obtained from a Case Study based on the IEEE 24 bus test system.

Abstract
This paper reviews the concepts and the solution algorithm of the Fuzzy DC OPF problem admitting generation costs and load values modeled by fuzzy numbers and details the integration of this problem in the Monte Carlo simulation model. In this sense, the paper describes an hybrid approach in which generation cost and demand uncertainties are represented by fuzzy numbers and the life cycle of the system components is modeled by probabilistic approaches. On this topic, the paper addresses the sampling procedure, the analysis of sampled states, the convergence testing and the computation of the expected values of the system Power Not Supplied and system risk indices. Finally, the paper includes results based on the IEEE 24 bus/38 branch test system to illustrate the proposed approach. © 2011 IEEE.

Abstract
This paper describes an approach to address the generation expansion-planning problem in order to help generation companies to decide whether to invest on new assets. This approach was developed in the scope of the implementation of electricity markets that eliminated the traditional centralized planning and lead to the creation of several generation companies competing for the delivery of power. As a result, this activity is more risky than in the past and so it is important to develop decision support tools to help generation companies to adequately analyse the available investment options in view of the possible behavior of other competitors. The developed model aims at maximizing the expected revenues of a generation company while ensuring the safe operation of the power system and incorporating uncertainties related with price volatility, with the reliability of generation units, with the demand evolution and with investment and operation costs. These uncertainties are modeled by pdf functions and the solution approach is based on Genetic Algorithms. Finally, the paper includes a Case Study to illustrate the application and interest of the developed approach.

Abstract
Generation expansion planning gained a new dimension with the advent of electricity markets. It is now an activity decoupled from transmission and there are several agents competing to generate electricity and aiming at maximizing their individual profits. In view of this, it becomes more important to develop tools to help generation agents to build their expansion plans, internalizing several uncertainties in the model, an being able to simulate different possible reactions of the other competitors, given their impact in the profits of the agent being modelled. In this paper, we present a long-term decision aid tool that uses System Dynamics to model the long run of electricity markets together with Genetic Algorithms to solve the individual expansion problem of generation agents given their mixed-integer nature. Apart from the detailed description of the developed approach, the paper also includes a Case Study based on a four generation agent system to illustrate its application.