Abstract
An increasing implementation of renewable sources and electric vehicles can be of help in reducing the total operational cost of a power system, affecting power system technical operation. To this end, a multi-objective optimisation method using Normalised Normal Constraint (NNC) is applied in this paper by which two competitive objectives are considered: Minimisation of Active Distribution System (ADS) operational cost and minimisation of ADS power losses. Meanwhile, the uncertain behaviour of wind, photovoltaic units, and arrival and departure time of electric vehicles are considered. The proposed model is a multi-objective problem which comprises two stochastic stages and is simulated under GAMS environment on a modified IEEE 18-bus test system. The results clearly represent the trade-off between economic and technical benefits of the considered ADS. Furthermore, the effect of electric vehicles charging and discharging tariffs on the operational cost of the system are shown.

Abstract
This paper proposes an estimation strategy in order to address two arising trends in Power System State Estimation (PSSE). Through a hybrid two-stage estimation architecture, high quality measurements gathered by PMUs can be incorporated into PSSE without excluding the widespread employed SCADA measurements. In the first stage of the proposed estimation architecture, SCADA and PMU measurements are individual processed by Maximum Correntropy-based estimators that replace conventional WLS-based methods. The second stage makes use of fusion methods to optimally combine the estimates provided by the individual estimators in order to enhance the quality of final estimates. This architecture allows the inclusion of the new class of measurement while making the whole process bad data-resilient, due to the outlier-rejection properties of Maximum Correntropy-based algorithms.

Abstract
This study is about leadership and more specifically it focuses on middle management, namely the marketing director. After a literature review, and a section explaining the methodology followed, the results of three separate studies are described. The first study is an autoethnographic essay by the author; the second study involved 14 interviews with specialists; and the third study involved a focus group with functional directors in a multinational with a presence in Portugal. The context is Portugal, a developed country, albeit one of the poorest in the European Union. The profile of a successful marketing director is developed, the role of digital technology is discussed, and the conclusion announced that there will be little loyalty towards the middle manager (the marketing director) as firm collaborators will want a higher salary, which will often mean occupying this leader’s job. On the other hand, the influence of digital technology is undeniable and is associated to a greater transparency and proximity both existent in the workplace today.

Abstract

Abstract
Together with the increasing population and prosperity levels of the growing countries, the economic and technological developments and modernized lifestyles of the end users have increased their electrical, heating and cooling energy demands extraordinarily. These services are generally provided to the end users independently, which leads to considerable reductions in the system efficiencies. For the purpose of providing a decrease in the demands of the end users and to transfer the energy carriers to the end users in an integrated and more efficient way, the concept of multi energy systems (MESs) has emerged. MESs could be developed at a district level, a city level and lastly at a country level. In this paper, a smart neighborhood MES model is proposed with the aim of achieving cost optimization by mixed integer linear programming (MILP) based formulation considering a time-of-use (TOU) tariff. In order to testify the effectiveness of the proposed optimization algorithm, two different case studies are conducted by taking into account flexible energy production capability of different energy carriers.

Abstract
The use of underwater autonomous vehicles has been growing, allowing the performance of tasks that cause inherent risks to Human, namely in inspection processes near to structures. With growth in usage of systems with autonomous navigation, visual acquisition methods have also gotten more developed because, they have appealing cost and they also show interesting results when operate at a short distance. It is possible to improve the quality of navigation through visual SLAM techniques which can map and locate simultaneously and its key aspect is the detection of revisited areas. These techniques are not usually applied to underwater scenarios and, therefore, its performance in environment is unknown. The paper presents a more reliable navigation system for underwater vehicles, resorting to some visual SLAM techniques from literature. The results, conducted in a realistic scenario, demonstrated the ability of the system to be applied to underwater environment.