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.

The objective of this paper is to present an approach to behavioral modeling that can be applied to predict the nonlinear response of power amplifiers with memory. Starting with the discrete-time, complex-baseband full Volterra model, we define a novel methodology that retains only radial branches that can be implemented with one-dimensional finite impulse response filters. This model is subsequently simplified by selecting a subset of directions using an ad hoc procedure. Both models are evaluated in terms of accuracy in the time and frequency domains and complexity, and are compared with other models described in the literature. The evaluation is conducted using a low-voltage silicon RF driver amplifier and a 5-W PA, which are characterized at different levels with diverse modulation formats, including wideband code-division multiple-access (WCDMA) and orthogonal frequency-division multiplexed (OFDM) signals. In all cases, comparison of the measured and simulated responses confirms the effectiveness of the proposed approach.

The ongoing energy transition has changed the architecture of electricity networks in ways that conventional power transformers are not able to cope with the new required functionalities. For this purpose, the solid state transformer (SST), which comprises state of the art power electronics with galvanic isolation to interconnect two separate alternating current (AC) or direct current (DC) power grids, is considered to be the dominant solution. The purpose of this paper is to provide a practical, application-oriented review of the SST. In this context, the main functionalities and possible applications of the SST are presented, including smart grids (SGs), data centres, railways, offshore wind farms, etc. Furthermore, the main developed SST prototypes are analysed with special focus on the related projects, demonstrators, stakeholders and rated values, e.g., voltage, switching frequency and power. The analysis is concluded with the future trends and challenges regarding the wider implementation of SST technology in the electrical grid.

Newly installed renewable power capacity has been increasing incredibly in recent years. For example, in 2018, 181 GW were installed worldwide. In this scenario, in which photovoltaic (PV) energy plays a leading role, it is essential for main players involved in PV plants to be able to identify the failure modes in PV modules in order to reduce investment risk, to focus their maintenance efforts on preventing those failures and to improve longevity and performance of PV plants. Among the different systems for defects detection, conventional infrared thermography (IRT) is the fastest and least expensive technique. It can be applied in illumination and in dark conditions, both indoor and outdoor. These two methods can provide complementary results for the same kind of defects, which is analyzed and characterized in this research. Novel investigation in PV systems propose the use of a power inverter with bidirectional power flow capability for PV plants maintenance, which extremely facilitates the electroluminescence (EL) inspections, as well as the outdoor IRT in the fourth quadrant.

A new active Q-f droop anti-islanding (AI) algorithm is proposed. The method is based on frequency and reactive power cross-correlation measures. The proposed control technique is intended to fulfill recent and future grid code requirements. The algorithm looks for a zero nondetection zone, adding low disturbances, working with long frequency excursions and nondependence of the power factor setpoint. The method was verified using a set of simulation models developed in PSCAD environment. The tests show results for several quality factors and different active power levels. In addition, a comparative analysis against other AI methods is presented. Experimental and simulation tests provide further insight on the controllers performance under different working conditions, considering several quality factors and active power levels. Moreover, its performance is assessed comparing the proposed controller behavior against state-of-the-art AI methods.

Nowadays, photovoltaic (PV) silicon plants dominate the growth in renewable energies generation. Utility-scale photovoltaic plants (USPVPs) have increased exponentially in size and power in the last decade and, therefore, it is crucial to develop optimum maintenance techniques. One of the most promising maintenance techniques is the study of electroluminescence (EL) images as a complement of infrared thermography (IRT) analysis. However, its high cost has prevented its use regularly up to date. This paper proposes a maintenance methodology to perform on-site EL inspections as efficiently as possible. First, current USPVP characteristics and the requirements to apply EL on them are studied. Next, an increase over the automation level by means of adding automatic elements in the current PV plant design is studied. The new elements and their configuration are explained, and a control strategy for applying this technique on large photovoltaic plants is developed. With the aim of getting on-site EL images on a real plant, a PV inverter has been developed to validate the proposed methodology on a small-scale solar plant. Both the electrical parameters measured during the tests and the images taken have been analysed. Finally, the implementation cost of the solution has been calculated and optimised. The results conclude the technical viability to perform on-site EL inspections on PV plants without the need to measure and analyse the panel defects out of the PV installation.