• Energy Research

The article describes the implementation of IoT technology in the teaching of microprocessor technology. The method presented in the article combines the reality and virtualization of the microprocessor technology laboratory. A created IoT monitoring device monitors the students’ microcontroller pins and sends the data to the server to which the teacher is connected via the control application. The teacher has the opportunity to monitor the development of tasks and student code of the program, where the functionality of these tasks can be verified. Thanks to the IoT remote laboratory implementation, students’ tasks during the lesson were improved. As many as 53% (n = 8) of those students who could improve their results achieved an improvement of one or up to two tasks during class. Before the IoT remote laboratory application, up to 30% (n = 6) of students could not solve any task and only 25% (n = 5) solved two tasks (full number of tasks) during the class. Before implementation, 45% (n = 9) solved one problem. After applying the IoT remote laboratory, these numbers increased significantly and up to 50% (n = 10) of students solved the full number of tasks. In contrast, only 10% (n = 2) of students did not solve any task.

The article describes the design of a universal simulation model of a voltage regulator for applications compatible with the globally used PSpice program. Users can create a model of any type of integrated switching voltage regulator that is currently available on the market by setting its individual parameters. The proposed connection of the regulator was applied in the connection of the buck DC–DC converter. The accuracy of the model was verified by comparing the results obtained by the simulation to other official models and to practical measurements taken on a real sample of the converter. The versatility of the model was proven by comparison with another type of converter with different parameters.

The article describes the principles based on which it is possible to obtain energy from renewable sources more efficiently. The principles use the conventional DC-DC interleaved buck converter based on the common electronic component types and the control strategy. A novelty of such a proposed solution lies in the methods which are not new, but with the right combination, better results can be achieved. The resulting method can be implemented into various topologies where the highest efficiency for wide input power is required. In case of the renewable energy sources where the power can vary hugely during the day, the proposed method can be implemented. Therefore, the article provides several steps, from calculation through simulation to experimental results that brings reader close to understanding of a such proposed solution.

As the global emphasis on solar energy intensifies, optimizing the efficiency of photovoltaic panels becomes crucial in meeting energy demands sustainably. Addressing this, our research delves deeply into advancing maximum power point tracking (MPPT), a pivotal component in perfecting the energy conversion process. Leveraging state-of-the-art mathematical modeling, in-depth simulations, and comprehensive experimental validation, we set out to markedly refine the performance of non-isolated multi-branch buck DC–DC converters. In this pursuit, we introduce an innovative algorithm meticulously designed to adjust the number of active branches. This adjustment is rooted in robust efficiency metrics, ensuring optimal power delivery even under dynamic and fluctuating conditions. We place a distinct emphasis on the transformative role of current in determining converter efficiency. Drawing from our findings, we advocate for an adaptive control strategy, precisely engineered to thrive in a spectrum of operational contexts. With this study, we not only present pivotal contributions to the domain of photovoltaic technology but also chart out clear expectations for future endeavors. Our hope is that these advancements serve as foundational steps, guiding the evolution of sustainable energy generation.