Abstract
In this paper it is applied a Rough Setapproach that takes into account an incomplete information system to study the steady-state security of an electric power system. The Rough Set Theory has been conceived as a tool to conceptualize, organize and analyze various types of data, in particular, to deal with inexact, uncertainor vague knowledge. The knowledge acquisition process is a complex task, since the experts have difficulty to explain how to solve a specified problem. So, an incomplete set of relevant information may arise. The study presents a systematicapproach to transform examples in a reduced set of rules. These rules can be used successfully to avoid security problems and provides a deeper insight into the influence of parameters on the steady-state system performance. © Springer Science+Business Media Dordrecht 2014.

Abstract
Renewable energy is essential for global sustainability. Wind power gave a great contribution to this energy paradigm. The paper describes a maintenance management system for inshore and offshore wind farms, as well as a method to schedule maintenance using genetic algorithms. Under this subject there exists a sub-problem that concerns with the determination of the cheapest path between two points. The paper compares the performance of three methods: genetic algorithms, Dijkstra's algorithm and ant optimization algorithm to the determination of the cheapest path between different wind parks for maintenance.

Abstract
This paper proposes a novel method to characterize the availability of household loads to participate in demand response programmes, as well as detailed mathematical models to characterize households loads. The availability of the households results from the flexibility of their controllable loads to increase/reduce consumption. This flexibility is calculated taking into account the comfort levels predefined by the customers and the technical restrictions of the controllable loads. The proposed method was evaluated through a management algorithm developed to perform demand control actions in quasi-real-time, according to the objectives of the distribution system operator or energy aggregator and the availability of the household loads. A scenario with a single household located in a semi-urban area is used to illustrate the application of the algorithm and validate the proposed method.

Abstract
This paper proposes a novel Energy Aggregator model responsible for managing the flexibility of low voltage customers in order to reduce electricity costs. The flexibility of the customers is represented by the availability of their controllable loads to reduce/ increase power consumption. The flexible loads are managed according to the customers' preferences and the technical limitations of the flexible loads. The Energy Aggregator model developed includes an algorithm designed to manage customers' flexibility in quasi-real-time, with the objective of minimizing the deviations from the energy bought by the aggregator in the market. A scenario with 30 households located in a semi-urban area is used to illustrate the application of the algorithm and validate the proposed approach.

Abstract
This paper describes a novel Electric Vehicle (EV) charging management system which was designed to control the EV load considering simultaneously the EV owners requirements and the electrical network technical limitations. The system was developed to be integrated with existing commercial equipment for smart grids, such as distribution transformer controllers, SCADA systems and Electrical Vehicles Charging Stations. The performance of the smart charging system was evaluated using a typical Portuguese low voltage network as test case, where several EV were assumed to exist. The results obtained prove the effectiveness of the system, as it allowed charging all the EV according to their owners' preferences without increasing the network peak load or creating voltages or overload problems.

Abstract
Many applications of Fuzzy Power Flow have been proposed not only for operational purposes considering uncertainties, but also for planning exercises with high level of intermittent sources, interconnection presence and, more recently, electric vehicles load. However, their use in real systems is not usual, mainly where the uncertainty level can be significant. This is due to the low accuracy of the results related to the classical methods, and the computational burden needed to achieve a high level of accuracy in the symmetric approaches. This paper aims to present a linearization of the Symmetric Fuzzy Power Flow in order to reduce the computational effort and make it possible for it to achieve high levels of accuracy when applied to real systems. With the purposes of demonstrating the applicability of the proposed approach, several IEEE test systems and a planning configuration of the Portuguese Transmission System will be studied.