International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

The increasing demand for electrical energy, the reduction of fossil fuel reserves, and growing concerns about environmental pollution have driven the development of technologies for energy production from renewable sources, particularly solar energy. The efficiency of photovoltaic systems depends on the angle of incidence of solar radiation on photovoltaic panels. Static systems cannot maintain the optimal orientation toward the sun throughout the day, resulting in reduced electricity generation. For this reason, mechanisms for automatic solar trajectory tracking have been developed, significantly improving the performance of photovoltaic systems. This paper addresses the design, development, monitoring, and operation of a single-pole dual-axis mechanism for solar trajectory tracking of the SM44M3V15P type, integrated with photovoltaic modules. The system was developed as a prototype and later implemented near the Mechatronics Laboratory at the Faculty of Mechanical Engineering, University of Prishtina. The mechanism enables continuous tracking of the sun’s trajectory through two independent axes: the azimuth axis and the elevation axis. The system includes linear actuators, a mechanical structure, electronic components, and software for automatic monitoring and control. The study includes experimental analyses and simulations to compare the performance between a fixed photovoltaic system and a dual-axis tracking system. The results show that the dual-axis mechanism significantly improves electrical energy production compared to static and single-axis systems. Annual energy production increased from 4156.13 kWh in the fixed system to 5487.42 kWh in the dual-axis tracking system. The findings demonstrate that dual-axis solar tracking systems represent an efficient and sustainable solution for improving the performance of photovoltaic installations in modern engineering applications.

In this paper, a comprehensive analysis of the process of natural gas reform in MIDREX technology was carried out, which was aimed at optimizing this process in order to increase hydrogen yield, reduce the specific consumption of natural gas and minimize the risks of soot formation. The paper also calculates the thermal balance, combined steam-carbon dioxide reforming (SMR + DRM). Based on the conducted studies, optimal reforming modes were determined: gas outlet temperature ~915-920°C; H2O/C ~1.8; increased CO2 fraction. Switching to an optimized reforming mode reduces natural gas consumption by 5.5%, increases H2 output by 6.4%, and reduces CO2 emissions due to better energy efficiency and H2 addition potential. The results obtained in this work are useful for upgrading existing Midrex installations in the direction of decarbonization, including the transition to MIDREX Flex/H2 technologies.

This article summarizes the preliminary preparations for conducting experiments with phase change materials to determine their behavior during continuing heating and cooling processes. The goal is to summarize conclusions about the possibilities of using these materials in boilers and other water-heating tanks for industrial and domestic applications. The techniques, materials, and equipment that will be used are described, as well as the theoretical behavior of the materials that will be compared

In the days of industrial development towards low-carbon production and the establishment of a circular economy, special attention should be paid to the implementation of green policies in real practices and training of all personnel of enterprises. The presented study examines the “green” models of labor organization in the context of the transition to a low-carbon economy. Training of personnel in the ideas of an environmentally friendly economy becomes a good practice for achieving the commitments made by companies to improve energy efficiency and optimize resources. Thus, the policies of senior management are implemented in all working units of enterprises and give a common course for companies to achieve the set goals towards low-carbon production. Training has always been and will be the main means of achieving given goals, ideologies and tasks. Training also equalizes all employees, regardless of their hierarchical position in the system, to fulfill the same requirements.

A significant transformation is underway, driven by the rise of new companies that challenge traditional energy models and bring forth innovative technologies and business strategies. These innovative companies are leading the way in advancing cleaner, more sustainable energy systems. They concentrate on renewable energy generation, energy storage, smart grid technologies, and enhancing energy efficiency. By decentralizing energy production and offering customer-focused solutions, these companies are reshaping the way energy is produced, distributed, and consumed. This article explores how these new players are not only contributing to global sustainability goals by reducing carbon emissions but also creating economic opportunities, such as job creation and attracting investment in the clean energy sector. Despite the promising benefits, these firms face significant challenges, including regulatory hurdles, competition from established players, and financial constraints. Overcoming these barriers will require coordinated efforts from policymakers, industry leaders, and investors to create an environment conducive to innovation. Ultimately, the ongoing evolution of the energy sector presents an opportunity to build a more resilient, efficient, and sustainable energy system for the future.

Energy efficiency is an important part of the EU’s ambition to transition to a carbon-neutral economy by 2050. Greater energy efficiency will be needed in the future if the EU is to achieve this goal. All sectors of the economy have the potential to contribute to energy efficiency. Consistent energy management helps organisations realise untapped energy efficiency potential. In this way, they will benefit from cost savings and make a significant contribution to protecting the environment and climate by reducing harmful emissions and carbon footprints. This study aims to analyse the potential opportunities for businesses to realise savings, gain competitive advantages and achieve sustainable development and a positive image.

This paper investigates the inverse problem for thermal bridges – determining design parameters (such as material, geometry, thermal resistance R of the components) of the bridge at a known Psi-factor. By using artificial neural networks, a thermal bridge type IF (wall-floor connection) has been considered to evaluate the effectiveness of the methodology. The results show that the approach provides a fast and accurate way to predict the optimal parameters that meet specific energy efficiency requirements. In the future, this approach could help to determine the parameters of thermal bridges using thermographic images non-invasively.

There are many different models and types of heat exchangers depending on the area of use. The type of fluids involved in heat transfer and their temperature play a critical role in selecting the appropriate model. Common heat exchangers include plate exchangers, tube-type exchangers, air-cooled exchangers, and graphite exchangers. In this study, a sustainable and original heat exchanger system was designed to increase energy efficiency and reduce natural gas consumption by utilizing the waste heat from natural gas. The design prioritizes ease of maintenance and cleaning. Detailed engineering analyses were conducted, and critical engineering errors identified in previous heat exchanger designs were resolved. The developed designs were validated through test studies and experiments, leading to the final design after an optimization process.
As a result of the study, a high-capacity, energy-efficient, and sustainable heat exchanger integrated with modern technology was developed.

The publication examines the use of artificial neural networks to calculate the linear thermal conductivity (Psi-factor) of thermal bridges given various parameters, such as geometrical data and the thermal resistance R of the thermal bridge components. The neural network is trained on examples of IF, IW, and B thermal bridges, considering the straightforward task of determining Psi using given parameters. The neural network training results show high accuracy in calculations – RMSE is 1.132% on training data and 1.1423% on test data, and the correlation coefficient (R²) is around 0.9997 for both data sets. The applicability of the approach to seismic conditions in the Balkans is assessed.

One of the biggest challenges of our century is climate change. The aviation industry is a major contributor to global carbon emissions, and airports are responsible for a significant portion of this impact. To reduce the carbon footprint of airports, it is necessary to implement energy efficiency measures that can help reduce energy consumption and greenhouse gas emissions. This study analyzes the impact of the use of photovoltaic panels (PV) and the replacement of boiler burners with oil, on energy efficiency and the reduction of carbon emissions at the airport of Tirana. The electricity produced by these panels is used to power airport buildings, lighting systems and other infrastructure, reducing the need for traditional energy sources.
The reviewed period covers the year 2023, because during this year important investments were made with the installation of photovoltaic panels and the replacement of oil boiler burners with LPG burner, in addition to the improvement of the lighting system and the replacement of diesel vehicles with electric vehicles. Energy consumption data is used to calculate the carbon footprint and key energy performance indicators. The results showed that the use of photovoltaic panels and the change of burners of oil boilers brought a significant reduction of the carbon footprint and a significant economic benefit.

This study examines the impact of component materials on the energy performance of solar panels designed for water heating. For this purpose, we have integrated numerical simulations and experimental analyzes enabled by algorithms developed with LabVIEW software. The primary objective of this investigation is to assess how the selection of materials in the construction of solar panels affects their overall efficiency in harnessing and converting solar energy into heat for water heating purposes. The research methodology involves the development and implementation of advanced algorithms using LabVIEW, a versatile software platform known for its proficiency in data acquisition, analysis, and control. Numerical simulations focus on modeling the behavior of solar panels under different conditions, taking into account factors such as radiation, temperature and the specific characteristics of different component materials. These simulations provide valuable assessments of theoretical aspects of solar panel performance and enable the identification of optimal material combinations. Through the physical model, experimental studies are conducted to validate the simulated results. Physical prototypes of solar panel components are built using various materials and their performance is rigorously evaluated under real-world conditions. Experimental measurements allow data collection, and enable comparative analysis with numerical simulations. The results of this study aim to contribute to the advancement of solar panel technology by providing a deeper understanding of how material choices affect energy efficiency. Moreover, the use of LabVIEW software in the development of algorithms ensures a systematic and accurate analysis of numerical and experimental data.

The importance of artificial lighting in our daily lives is growing, and street lighting has become a major focus over time. The creation of street lighting was motivated by the need to increase visual and property security and public safety. Current developments in metropolitan environments foreshadow the ‘smart cities’ of the future. The basic concept is that CCTV cameras, traffic lights and street lighting all have ‘smart functions’. Municipalities will be able to adapt to the needs of their inhabitants, thus increasing safety, comfort and energy efficiency. Given the adaptability of smart street lighting to the built environment, artificial intelligence is an essential element of smart cities, even in the systems already in place. Extensive sensor networks will facilitate the collection of environmental data by AI. In addition, unauthorised access to information available through IoT systems poses a serious threat. A critical point is the monitoring and protection of surveillance systems that are vital to the operation of smart systems.