Abstract
Due to the high penetration of renewable energy into the energy matrix of today's power networks, the design of generating systems based only on static reserve assessment does not seem to be enough to guarantee the security of power system operation. From the wind power integration perspective, this energy source imposes additional requirements, mainly due to the inherent unpredictable characteristic of the wind. Besides the uncertainties in load and generating unit availabilities, the operating reserve needs also to deal with the fluctuation characteristic of the wind power. Therefore, more flexibility of the conventional generators (hydro and thermal) is required to provide system support services. This paper discusses a new methodology based on chronological Monte Carlo simulation to evaluate the operating reserve requirements of generating systems with large amounts of renewable energy sources, in particular, wind power.

Abstract
Coordination in Reo emerges from the composition of the behavioural constraints of primitives, such as channels, in a component connector. Understanding and implementing Reo, however, has been challenging due to the interaction of the channel metaphor, which is an inherently local notion, and the non-local nature of the constraints imposed by composition. In this paper, the channel metaphor takes a back seat. We focus on the behavioural constraints imposed by the composition of primitives and phrase the semantics of Reo as a constraint satisfaction problem. Not only does this provide a clear description of the behaviour of Reo connectors in terms of synchronisation and data flow constraints, it also paves the way for new implementation techniques based on constraint satisfaction. We also demonstrate that this approach is more efficient than the existing techniques based on connector colouring.

Abstract
In the last years we have witnessed a growing interest, by the academic community and the automotive industry, in the multi-motor electric vehicles. The electrical nature of the propulsion is going to stress even more an increasing insertion of electronic devices in the vehicles. Furthermore, carmakers are performing research and already presented some vehicles based on the concept of X-By-Wire. Consequently, the growing complexity of the actuators and their control, as well as the need of increasing the safety and reliability of the vehicles obliges to the study and development of intelligent computational systems dedicated to the detection and diagnosis of failures in the electric propulsion. Hence, it is fundamental to start advanced studies leading to the development of innovative solutions that embed fault-tolerant electric propulsion in the electric vehicles. Accordingly, the main objective of this work consists on the bibliographic revision and study of fault-tolerant diagnosis and control systems dedicated to multi-motor electric vehicles.

Abstract
Business organizations must pay attention to interesting changes in customer behavior in order to anticipate their needs and act accordingly with appropriated business actions. Tracking customer's commercial paths through the products they are interested in is an essential technique to improve business and increase customer satisfaction. Data warehousing (DW) allows us to do so, giving the basic means to record every customer transaction based on the different business strategies established. Although managing such huge amounts of records may imply business advantage, its exploration, especially in a multi-dimensional space (MDS), is a nontrivial task. The more dimensions we want to explore, the more are the computational costs involved in multi-dimensional data analysis (MDA). To make MDA practical in real world business problems, DW researchers have been working on combining data cubing and mining techniques to detect interesting changes in MDS. Such changes can also be detected through gradient queries. While those studies have provided the basis for future research in MDA, just few of them points to preference query selection in MDS. Thus, not only the exploration of changes in MDS is an essential task, but also even more important is ranking most interesting gradients. In this chapter, the authors investigate how to mine and rank the most interesting changes in a MDS applying a TOP-K gradient strategy. Additionally, the authors also propose a gradient-based cubing method to evaluate interesting gradient regions in MDS. So, the challenge is to find maximum gradient regions (MGRs) that maximize the task of raking gradients in a MDS. The authors' evaluation study demonstrates that the proposed method presents a promising strategy for ranking gradients in MDS. © 2010, IGI Global.

Abstract

Abstract
This study is on variable-speed wind turbines with permanent magnet synchronous generator. Three different drive train mass models and three different topologies for the power-electronic converters are considered. The three different topologies considered are, respectively, a matrix, a two-level and a multilevel converter. A novel control strategy, based on fractional-order controllers, is proposed for the wind turbines. The influence of a converter control malfunction on the harmonic current emissions is studied. The performance of disturbance attenuation and system robustness is ascertained. Simulation results are presented, and conclusions are duly drawn.