Renewable energy power plants and transport and heating electrification projects are being deployed to enable the replacement of fossil fuels as the primary energy source. This transition encourages distributed generation but makes the grid more weather-dependent, thus reducing its inertia. Simultaneously, electrical network operators face voltage, frequency, and stability challenges at the distribution level. Networks were not designed to manage the stochasticity of renewable energy sources or the congestion caused by the new transport and heating demands. Such challenges are commonly addressed through infrastructure reinforcements. This review studies how energy storage systems with different carriers can provide a collaborative solution involving prosumers as ancillary services providers at the distribution level. We focused on the European urban context; thus, we analyzed renewable energy sources, batteries, supercapacitors, hydrogen fuel cells, thermal energy storage, and electric vehicles. A thorough review of successful implementations proved that including storage in one or more carriers benefits the distribution system operators and the prosumers, from both technical and economic perspectives. We propose a correlation between individual energy storage technologies and the ancillary services they can provide based on their responses to specific grid requirements. Therefore, distribution system operators can address network issues together with the prosumers. Nevertheless, attractive regulatory frameworks and business models are required to motivate prosumers to use their assets to support the grid. Further work is recommended to describe the joint operation of multiple storage technologies as multicarrier systems, focusing on the coupling of electrical and thermal energy storage. Additionally, how ancillary services affect the energy storage system’s aging should be studied.

Fifth-generation energy networks are combined networks of heat and electricity, that have the ability to generate, distribute, store and share energy between consumers. Knowledge on the dynamic behaviour of the physical phenomena related to energy generation, distribution and storage provides insight into the performance of the system as a whole. A mixed-integer linear algorithm is proposed, implementing a partitioned clustering program for subsequent classification of typical demand, grouping specific days with similar demand profiles together. From this arrangement, the optimal network configuration can be determined using an objective function, minimizing the economic and environmental impact. To validate the optimization results, a simulation of the network was built, which mimics its physical dynamic behaviour, and through which the distribution and storage capabilities of the network can be assessed. Advanced advice on fifth-generation energy networks is presented that can be applied to early-stage network design, reducing costs and emissions, along with data on the implementation of renewable energy technologies and their performance. Additionally, this research provides the foundation for numerical modelling of such energy networks which contributes to future research.

Radiation forecast is the milestone of the solar energy industry, making possible the existence of the whole market. Solar radiation models allow scientists and engineers to predict the behaviour of a PV system to perform technical and economic analysis. Despite the existence of numerous models, most of them are highly complex or require massive amounts of data, limiting solar energy start-ups. As a result, a state-of-the-art review was performed and based on it this study proposed a simple model that allows emerging solar companies to create preliminary analysis for their clients. The proposed model calculates the instant power of the envelope curve of PV generation, based on the Gaussian bell equation, by using the daily specific energy and a deviation proportional to the sun hours of the geographical information as parameters. With accurate meteorological data, results showed an acceptable performance, with a more straightforward implementation, when compared against those reported in the literature.

La industria farmacéutica se encuentra en la búsqueda constante de métodos de optimización de sus procesos. En la presente investigación se desarrolló un sistema de visión que permite caracterizar morfológicamente el lecho de tabletas farmacéuticas en el proceso de recubrimiento. Como resultado, se diseñó un algoritmo de visión artificial que permite cuantificar las tabletas presentes en la imagen y determinar el área de cada una mediante el uso de la transformada de Hough y el filtro de Canny, partiendo de un modelo plano y estático del lecho de recubrimiento de tabletas farmacéuticas. Se obtuvo una aproximación de la posición angular de las tabletas farmacéuticas respecto a eje óptico de la cámara, según la cantidad de capas de tabletas en el lecho.

El presente artículo describe el diseño del circuito de un inversor trifásico de siete niveles, seccionado en tres etapas: etapa de generación de onda monofásica, etapa de control y etapa de desfase. Para la etapa de generación de onda monofásica se utilizó un inversor asimétrico en cascada partiendo de tiristores. Para la etapa de control se utilizó una máquina de estados finitos con flip-flops JK. Para la etapa de desfase se prefirió un circuito desfasador con monoestables sobre circuito desfasador RC, debido a las pérdidas que produce en el sistema y efectos negativos en la onda de salida.