At present, the energy transition is leading to the replacement of large thermal power plants by distributed renewable generation and the introduction of different assets. Consequently, a massive deployment of power electronics is expected. A particular case will be the devices destined for urban environments and smart grids. Indeed, such applications have some features that make wide bandgap (WBG) materials particularly relevant. This paper analyzes the most important features expected by future smart applications from which the characteristics that their power semiconductors must perform can be deduced. Following, not only the characteristics and theoretical limits of wide bandgap materials already available on the market (SiC and GaN) have been analyzed, but also those currently being researched as promising future alternatives (Ga${}_2$O${}_3$, AlN, etc.). Finally, wide bandgap materials are compared under the needs determined by the smart applications, determining the best suited to them. We conclude that, although SiC and GaN are currently the only WBG materials available on the semiconductor portfolio, they may be displaced by others such as Ga${}_2$O${}_3$ in the near future.

Background: Alterations in heart rate (HR) may provide new information about physiological signatures of depression severity. This 2-year study in individuals with a history of recurrent major depressive disorder (MDD) explored the intra-individual variations in HR parameters and their relationship with depression severity.Methods: Data from 510 participants (Number of observations of the HR parameters = 6666) were collected from three centres in the Netherlands, Spain, and the UK, as a part of the remote assessment of disease and relapse-MDD study. We analysed the relationship between depression severity, assessed every 2 weeks with the Patient Health Questionnaire-8, with HR parameters in the week before the assessment, such as HR features during all day, resting periods during the day and at night, and activity periods during the day evaluated with a wrist-worn Fitbit device. Linear mixed models were used with random intercepts for participants and countries. Covariates included in the models were age, sex, BMI, smoking and alcohol consumption, antidepressant use and co-morbidities with other medical health conditions.Results: Decreases in HR variation during resting periods during the day were related with an increased severity of depression both in univariate and multivariate analyses. Mean HR during resting at night was higher in participants with more severe depressive symptoms.Conclusions: Our findings demonstrate that alterations in resting HR during all day and night are associated with depression severity. These findings may provide an early warning of worsening depression symptoms which could allow clinicians to take responsive treatment measures promptly.

The fast deployment of distributed energy resources (DERs) is creating a series of challenges that should be addressed in the coming years. In particular, distribution grids are playing an increasingly important role in the electricity system. Moreover, the three-phase four-wire structure of this network contribute to the appearance of imbalances and a series of problems derived from them. In this context, distribution system operators (DSOs), as the main responsible for the distribution grid, must ensure the quality of supply to consumers. This paper takes advantage of a four-legs D-STATCOM to remove current imbalances in low-voltage power lines. A 35-kVA prototype has been developed and installed in an urban distribution grid. The effect of the D-STATCOM has been analyzed during its first month of operation, studying and measuring the advantages of providing DERs the ability to perform active balancing to the utility grid. The results show a reduction in current imbalances from 21 % to 0 % and neutral current from 10.3 A to 0.4 A. In addition, a 13 % decrease in cable losses has been estimated and a slight improvement in voltage unbalance factor can be noted.

The on-site assessment of the efficiency of a charging station is not a trivial process and is a topic of discussion for professionals. The efficiency of electric Vehicle Supply Equipment (EVSE), is an important parameter for both the user and the EVSE operator. This paper deals with a particular type of EVSE, using static wireless power transfer (WPT). This paper proposes a clear method to account for the parameters which can affect the correct determination of efficiency, such as in particular the accuracy of the meters and the effect of temperature. This work proposes a method to define the accuracy of the power and efficiency on-site assessment, and is aimed at clarifying that despite distorted waveforms at the charging stations, it is possible to reach a good accuracy in a wide temperature span (expanded uncertainty <0.5% between 5 °C and 40 °C). Analysis initiated from the measurement conditions and the actual waveforms recorded at two WPT EVSEs with differently rated power. This paper paves the way for the possibility of verifying class 0.5 m on-site, desirable for this type of application. The paper also clarifies that despite the evident presence of voltage and current ripple at the batteries, the weight of the ripple power on the total power is nevertheless lower than 0.1%. Finally, the paper highlights how, for the correct measurement of the ripple, it would be advisable to calibrate the instrumentation in DC and in AC, at a frequency double that of the working frequency of the EVSE coils.