Information Literacy developments and issues in Spain

The adoption of the information literacy (IL) agenda in Spain has been comparatively slow and fragmented due to cultural setbacks during the twentieth century. Since the late 1980s, however, developments in library services and staffing policies, reforms in education, and wide availability of ICTs, among other factors, have led to a brighter picture, with academic and public librarians all over the country engaged in IL activities for all types of users ± though school libraries still lag far behind. The main problems still to be addressed seem to be much the same as in most comparable countries: IL as a responsibility for all learning facilitators, social awareness of lifelong learning needs, training of IL trainers, assessing the individual achievements and the institutional outcomes of IL training programmes, and a clear understanding of the remit and rationale for different literacies within the information societ

Overload screening of transmission systems using neural networks

The process of determining whether a power system is in a secure or insecure state is a crucial task which must be addressed on-line in any Energy Management System. In this paper, an Artificial Neural Network, capable of accurately identifying the set of harmful contingencies, is presented, along with several results obtained from a real-size power network. The proposed approach makes use of classical numerical techniques to compensate the ANN'S inputs so that it can deal with topological changes in the power system

Time-Series Prediction: Application to the Short-Term Electric Energy Demand

This paper describes a time-series prediction method based on the kNN technique. The proposed methodology is applied to the 24-hour load forecasting problem. Also, based on recorded data, an alternative model is developed by means of a conventional dynamic regression technique, where the parameters are estimated by solving a least squares problem. Finally, results obtained from the application of both techniques to the Spanish transmission system are compared in terms of maximum, average and minimum forecasting errors

Application of Evolutionary Computation Techniques to the Optimal Short-Term Scheduling of the Electrical Energy Production

In this paper, an evolutionary technique applied to the optimal short-term scheduling (24 hours) of the electric energy production is presented. The equations that define the problem lead to a nonlinear mixed-integer programming problem with a high number of real and integer variables. Consequently, the resolution of the problem based on combinatorial methods is rather complex. The required heuristics, introduced to assure the feasibility of the constraints, are analyzed, along with a brief description of the proposed genetic algorithm. Finally, results from realistic cases based on the Spanish power system are reported, revealing the good performance of the proposed algorithm, taking into account the complexity and dimension of the problem

A Comparison of Two Techniques for Next- Day Electricity Price Forecasting

In the framework of competitive markets, the market’s participants need energy price forecasts in order to determine their optimal bidding strategies and maximize their benefits. Therefore, if generation companies have a good accuracy in forecasting hourly prices they can reduce the risk of over/underestimating the income obtained by selling energy. This paper presents and compares two energy price forecasting tools for day-ahead electricity market: a k Weighted Nearest Neighbours (kWNN) the weights being estimated by a genetic algorithm and a Dynamic Regression (DR). Results from realistic cases based on Spanish electricity market energy price forecasting are reported