Abstract

Abstract
Large-scale integration of variable Renewable Energy Sources (RES) brings significant challenges to grid operation that require new approaches and tools for distribution system management, particularly concerning voltage control. Therefore, an innovative approach for voltage control at the MV level is presented. It is based on a preventive day-ahead analysis that uses data from load/RES forecasting tools to establish a plan for operation of the different Distributed Energy Resources (DER) for the next day. The approach is formulated as a multi-temporal Optimal Power Flow (OPF) solved by a meta-heuristic, used to tackle complex multi-dimensional problems. The tuning of the meta-heuristic parameters was performed to ensure the robustness of the proposed approach and enhance the performance of the algorithm. It was tested through simulation in a large scale test network with good results.

Abstract
The strong growth that is felt at the level of photovoltaic (PV) power generation craves for more sophisticated and accurate forecasting methods that could be able to support its proper integration into the energy distribution network. Through the combination of the vector autoregression model (VAR) with the least absolute shrinkage and selection operator (LASSO) framework, a set of sparse VAR structures can be obtained in order to capture the dynamic of the underlying system. The robust and efficient alternating direction method of multipliers (ADMM), well known for its great ability dealing with high-dimensional data (scalability and fast convergence), is applied to fit the resulting LASSO-VAR variants. This spatial-temporal forecasting methodology has been tested, using 1-hour and 15-minutes resolution, for 44 microgeneration units time-series located in a city in Portugal. A comparison with the conventional autoregressive (AR) model is performed leading to an improvement up to 11%.

Abstract
Vast increase of renewable energy resources' (RER) share in total electricity production have led to evolving studies regarding different aspects of renewables integration. Other than their effects on network, the electricity markets are also affected by uncertain behavior of RERs in the market place. Hence, new approaches for market clearing are investigated. One of the possible solutions is the deployment of stochastic market clearing. However, the adaption of new market models should consider different market characteristics. As a result, this paper assesses the adaption of stochastic market in a hydro-penetrated system. The co-optimized energy and reserve schedule in the day-ahead time frame is derived using the mixed integer linear programming (MILP). The model is tested with Portuguese electricity market data as a real-case of hydro-penetrated system.

Abstract
Introduction: The study of eating behaviour should consider the presence of potential sources of bias, including social desirability. This is particularly relevant among students of Nutrition Sciences, since they have a higher risk of eating disorders. Objective: To analyse the effect of social desirability in the assessment of eating behaviour dimensions among nutrition students. Methods: In this cross-sectional study, we analysed data from 149 students of Nutrition Sciences. Participants completed a questionnaire assessing social desirability and eating behaviour dimensions (emotional, external and binge eating, flexible and rigid control, and eating self-efficacy). Results: Among males, social desirability had a negative association with binge eating, while among women it had a negative association with emotional, external and binge eating and a positive association with eating self-efficacy. In both subsamples, social desirability showed no significant association with any of the two types of dietary restraint (rigid and flexible control). Discussion: Overall, the association between social desirability and eating behaviour dimensions among students of Nutrition Sciences occurs in the same direction as found in students from other areas. However, alongside these similarities, there is a stronger association between social desirability and binge eating among male students of Nutrition Sciences. We hypothesize that this may be related with the different knowledge of students from different areas, and the way they perceive and face the treatment of eating disorders. Conclusion: Our study shows that social desirability should be considered while assessing eating behaviour among nutrition students, particularly when studying external eating, binge eating and eating self-efficacy. Moreover, when tailoring interventions to reduce the possible effects of eating behaviour on nutritionists and dieticians' practice, we should consider the influence of social desirability.

Abstract
The present work addresses the design of an electronic system for powering autonomous underwater vehicles (AUVs). We report the study and implementation of a system developed for transmitting and receiving wireless power in water from a docking station to an AUV. A simplified analysis is presented regarding the operation of a class-D power driver in a series-series inductive resonant coupling topology. We further investigate the compromise between link efficiency and power delivery of the system to circumvent the reduced power output capability. Simulation results are provided as well as measurement data validated using circuit prototypes in an experimental setup with a structure similar to the docking station of the AUV filled with salt water.