Abstract
The renewable energy-based distributed generation (DG) implementation in power systems has been an active research area during the last few decades due to several environmental, economic and political factors. Although the integration of DG offers many advantages, several concerns, including protection schemes in systems with the possibility of bi-directional power flow, are raised. Thus, new protection schemes are strongly required in power systems with a significant presence of DG. In this study, an adaptive protection strategy for a distribution system with DG integration is proposed. The proposed strategy considers both grid-connected and islanded operating modes, while the adaptive operation of the protection is dynamically realized considering the availability of DG power production (related to faults or meteorological conditions) in each time step. Besides, the modular structure and fast response of the proposed strategy is validated via simulations conducted on the IEEE 13-node test system.

Abstract

Abstract
Heterogeneous Multi-core Processors (HMPs) have the potential to outperform homogeneous multi-core processors in terms of raw performance and/or energy as both their Instruction-Set Architectures (ISA) and cache configurations (size and set associativity) can be tailored to the specific needs of a computation. In this paper we describe algorithm for the generation of custom HMP and a dynamic run-time core-mapping and scheduling policy that exploits the heterogeneity of such systems customized with respect to the number of cores and L1 cache memory sizes. Experimental results targeting custom HMPs implemented on a contemporary Field-Programmable Gate Array (FPGA) with LEON3 cores as their base for a set of 50 application codes reveal that the proposed core-mapping and scheduling algorithms achieves an average execution time improvement of 18.3% and a 12% energy reduction over a static core-mapping and list-scheduling algorithms. © 2015 IEEE.

Abstract
This paper investigates the effects of Demand Response Programs (DRPs) on the behavior of electricity market players in the day-ahead energy market. To this end, an electricity market environment is proposed based on the multi-agent systems in order to model the strategic self-scheduling of each market player as an individual agent. In such oligopolistic environment, market interactions are considered by using a game theoretic model and the market transactions are cleared by means of a security constrained unit commitment problem. Different types of DRPs are also considered consisting of Time Of Use (TOU), Real Time Pricing (RTP), Critical Peak Pricing (CPP), and Emergency Demand Response Program (EDRP). The proposed model is applied on a modified IEEE six-bus test system. The numerical results indicate that different types of DRPs differently affect the oligopolistic behavior of market players that should be studied by the system operators before their implementation.

Abstract
Wind power probabilistic forecast is a key input in decision-making problems under risk, such as stochastic unit commitment, operating reserve setting and electricity market bidding. While the majority of the probabilistic forecasting methods are based on quantile regression, the associated limitations call for new approaches. This paper described a new quantile regression model based on the Reproducing Kernel Hilbert Space (RKHS) framework. In particular, two versions of the model, off-line and on-line, were implemented and tested for a real wind farm. Results showed the superiority of the on-line approach in terms of performance, robustness and computational cost. Additionally, it was observed that, in the presence of correlated data, the optimal on-line learning may cause unreliable modelling. Potential solutions to this effect are also described and implemented in the paper.

Abstract
Universities and polytechnics are educational institutions that make decisions within the university management, taking into account various factors such as the number of vacancies to offer ( not only the university, as each course itself), the courses setting strategy and his regime, the type of the course and publication. This paper presents a study on the evolution of vacancies and students placed in higher education in Portugal, taking into account an analysis of data from the page of the Ministry of Education and Higher Education from 2004 until 2015. The results show that vacancies available experienced a positive increase. However, since 2010 until the last year, there has been a progressive decrease. In relation to the number of students placed, this has been subject to fluctuations and some turning points, but in the last two years showed an increase. The most popular courses were Management and Medicine, and those who had more students were Nursing and Management.