This paper presents a buck-boost DC-DC converter design featuring a wider voltage gain capability. The proposed topology offers advantages such as continuous input current and a common ground connection shared by the input and output ports. The proposed converter's low input current ripple makes it particularly suitable for renewable energy applications, such as photovoltaic (PV) systems. In contrast to conventional buck-boost converters, which typically invert the output voltage polarity, this design delivers a positive output voltage. Additionally, the converter employs only a single main switch, which also benefits from reduced voltage stress, enhancing both reliability and operational efficiency. The converter's operation is grounded in detailed mathematical modeling, with simulation and experimental validation confirming consistency between theoretical predictions and practical performance.

The unsustainable use of resources (water, gas, and electricity) contributes to the intensification of global warming. On the other hand, the indiscriminate use of electrical resources poses serious problems to the sustainability and operability of the power grid. One of the solutions to mitigate this problem refers to responsible use of resources by the domestic user, creating new habits, without giving up their lifestyle and comfort. The creation of a game supported by a web application, which allows the use of group game techniques, can promote the increase of efficient consumption by the users. This work presents the development of a game which aimed at the consumption awareness of the participants. The competition between users was stimulated by the attribution of points, using the weekly consumption comparison of groups formed by the participants. Other functionalities, allowing users to obtain extra points, were designed to keep a high level of engagement.

DC-DC converters play a crucial role in providing power conversion for the integration of renewable energy sources into the electric power grid or as standalone power sources. However, achieving proper integration of applications like photovoltaic generators often requires DC-DC converters with an enhanced voltage range due to conditions such as PV shadowing. This is a feature that is lacking in standard DC-DC converters. Addressing this need, this paper presents a novel transformerless buck-boost converter with a wide conversion voltage ratio. The proposed converter has only one active switch, simplifying the gate driver and control system implementation. The wide conversion voltage ratio is ensured by its quadratic voltage gain. Operates in both step-up and step-down modes, unlike most existing quadratic topologies, which are limited to either step-up or step-down operation, and shares a common ground between the input and output terminals. The operational modes of the proposed converter and its steady-state performance are thoroughly analyzed. Simulation and experimental tests were conducted to evaluate its performance.

Recently, Graphical Security Models (GrSMs) became widely used for security analysis. The basic formalism called Attack Tree (AT) has been augmented with new attributes covering defence, response, and countermeasure aspects to support security modelling and analysis in vulnerable systems. Although the models have strength in visualising and analysing small attack-defence scenarios, these suffer from lack of scalability when increasing nodes and adaptability with other refinement models to show the dynamic nature and state of systems in interest. In this work, Coloured Petri net (CPN) is used to fulfil the mentioned shortcomings in GrSMs (specifically Tree-based models). It is applied for evaluating each component´s interactions, the impact of threats as well as defence systems to mitigate those threats. For that end and pointing out the CPN adaptability with GrSMs, a set of mapping rules are proposed allowing translation of ATs extension into CPN and their analysis. The quantitative analysis aspect is addressed in this work by introducing computing transition. We validate our proposed approach by applying it in an example of SCADA systems cyber-security analysis.

The widespread use of electricity in the most varied sectors, among them the industrial and domestic sectors adding up to the largest amount of energy consumed in recent years. Currently, this dependence happens because there are several equipments that need electricity uninterruptedly for correct operation, such as security systems, refrigerating equipment and others. The increase in equipments present in homes is also a relevant factor, leading to greater consumption of electricity and consequently an increase in the electric bill. In order to obtain improvements during the use of electricity, Neural Networks were used, which allowed constant learning and the use of previous prices. In this way, Artificial Intelligence software was used, which is increasingly sought after, and which has allowed for numerous operations such as event forecasting. Due to the points presented above, the idea arose of creating a tool that would make it possible to predict electricity prices and, conclusively, to manage loads that would be displaced and allocated in temporal spaces where the price of electricity was lower. The implementation of this tool has as its main objective to provide a reduction in the electricity bill whenever good load management occurs based on the forecast coming from the implemented neuronal network.

The study and assessment of Power Quality issues is nowadays a very important subject, particularly regarding Cyber-physical and Industrial Agents based systems, which are extremely sensitive to Power Quality disturbances. Giving students or engineers practical experience in this field requires a large investment from teaching institutions. This paper presents a laboratory device that emulates Power Quality disturbances in order to provide the required experimental expertize in the subject. It addresses limiting aspects such as harmonic distortion, flicker, sags, swells and transients. The developed system presents a good opportunity for technicians, even without deep knowledge on the field of power quality, to learn basic principles and be able to identify Power Quality events. Since the system is based on real data, represents a valuable approach giving trainees practical knowledge on the field.