Abstract

Abstract
This paper describes the methodology developed to build estimates of electricity prices having the horizon of one week. This approach uses artificial neural networks and includes a particular treatment of weekends and national holidays as a way to improve the quality of the results. The developed approach was tested using data obtained from the Spanish market operator for the time period of 2006 to 2008. The obtained value of MAPE - Mean Absolute Percentage Error - was 12,62% for workdays and 10,73% for holidays and weekends. The obtained results show that this study has interest to the market agents in question, since realistic forecasting was achieved.

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 addresses the generation expansion-planning problem describing a model that generation companies and regulators can use to get insight to this problem and to more completely study and characterize different investment decisions. The simulation model considers a number of possible generation technologies and aims at characterizing the corresponding investment plans from an economic point of view having in mind that market prices, the demand growth, investment and operation costs, as well as other factors, are affected by uncertainties. With the objective of helping generation companies and regulators to carry out this planning, we adopted an approach based on System Dynamics. This methodology allows simulating the long-term behavior of electricity markets, namely to help getting insight into the way new generation capacity enters in the market in a liberalized framework. Finally, the paper presents results from a case study illustrating the use of this approach.

Abstract
In this paper it is presented a formulation for the DC Optimal Power Flow problem considering load and generation cost uncertainties and the corresponding solution algorithms. The paper also details the algorithms implemented to allow the integration of losses on the results as well the algorithm developed to compute the nodal marginal price in the presence of such uncertainties. Since loads and generation costs are represented by fuzzy numbers, nodal marginal prices are no longer represented by deterministic values, but instead, by membership functions. To illustrate the application of the proposed algorithms, this paper also includes results based on a small 3 bus system and on the IEEE 24 bus/38 branch test system.

Abstract
One of the challenges that generation companies having hydro stations are facing corresponds to build the most adequate bids to send to day-ahead markets, maximizing their profit and taking into account the expect inflows, market prices and the interdependency between hydro plants in cascades. As a contribution to address this problem, this paper describes a short-term optimization model to build one-week schedules for a set of hydro power plants so that the outputs can be used to bid in the day-ahead market. This model is coordinated with a medium-scale (one year) model that inputs the value of using the water in the short-term problem. The developed model considers the non-linear relationship between the electric power, the net head and the turbine discharge and it takes in consideration pumping as well. The solution approach is based on an under-relaxed iterative procedure based on the algorithm described in [1] and the players are considered as price-takers, so that market prices are input variables. To solve the medium-term problem we propose a similar model that sends information about the final week volumes of each power plant to the short-term problem. On the other hand, we conducted a scenario analysis regarding market prices and inflows to internalize uncertainty. Finally, the model was successfully applied to a real size Portuguese cascade and the paper includes several results to illustrate the application of the developed models.