The digital economy implies structural transformation in many industries, including the energy sector, without considering the state specifics of the industry, for which full-fledged digitalization can be harmful. The aim of the study is to develop a methodology and to determine the level of digitalization in the energy sector in an intercountry context. Based on the methods of comparison and analysis, the work analyses the concept of “digitalization” and defines the indicators applied to the assessment of digitalization. The developed methodology is based on the index method, which makes it possible to assess the rating of countries by the level of digitalization in the energy sector. The article discusses modern technological development and socio-economic aspects that determine theoretical research and the development of digitalization in the energy sector. The reasons and stages of digitalization in the energy sector are highlighted. Using the comparison method, the analysis of existing approaches to assessing the digital energy of enterprises is carried out. End-to-end technologies are highlighted, as well as their practical application at the enterprises of the energy sector. An analysis of the key areas for the development of digital energy is presented. Conclusions are made about the feasibility of developing microprograms and the main directions of digitalization are highlighted.

The paper considers the problem of adolescent and young students’ personalities’ development in the conditions of face-to-face and distance school learning. The scientific novelty of the study is the proposed classification of pedagogical technologies according to the degree of their novelty: modernized technology, combinational technology, progressive technology, pedagogical technology of the combinational type, the essence of which is shown in its title. A specific model of pedagogical technology of the combinational type “Teaching in cooperation, in a team using flipped classroom” was developed. The developed technology was implemented during the classes of the humanities and natural-mathematical cycles. Nine hundred and eight adolescent and young students (divided into experimental and control groups) and 32 teachers participated in the experimental work. To analyze the differences between the experimental and control groups in terms of the student’s personality manifestation, several criteria and indicators were considered. For mathematical and statistical processing of the obtained results, the multifunctional statistical Fisher’s F-test was used. Analysis of the implementation of the developed technology in the conditions of face-to-face and distance learning showed a positive dynamics of experience formation of the student’s personality manifestation. This allowed the authors to consider the developed pedagogical means effective.

Ensuring access to sustainable, affordable and clean energy sources is a top priority of the global energy agenda. It is reflected in the seventh goal of the UN Sustainable Development Agenda with the three dimensions of economic growth, social inclusion and environmental protection. The seventh...

A promising method of energy storage is the combination of hydrogen and compressed-air energy storage (CAES) systems. CAES systems are divided into diabatic, adiabatic, and isothermal cycles. In the diabatic cycle, thermal energy after air compression is discharged into the environment, and the scheme implies the use of organic fuel. Taking into account the prospects of the decarbonization of the energy industry, it is advisable to replace natural gas in the diabatic CAES scheme with hydrogen obtained by electrolysis using power-to-gas technology. In this article, the SENECA-1A project is considered as a high-power hybrid unit, using hydrogen instead of natural gas. The results show that while keeping the 214 MW turbines powered, the transition to hydrogen reduces carbon dioxide emissions from 8.8 to 0.0 kg/s, while the formation of water vapor will increase from 17.6 to 27.4 kg/s. It is shown that the adiabatic CAES SENECA-1A mode, compared to the diabatic, has 0.0 carbon dioxide and water vapor emission with relatively higher efficiency (71.5 vs. 62.1%). At the same time, the main advantage of the diabatic CAES is the possibility to produce more power in the turbine block (214 vs. 131.6 MW), having fewer capital costs. Thus, choosing the technology is a subject of complex technical, economic, and ecological study.

The process of establishing relay protection and automation (RPA) settings for electric power systems (EPSs) entails complex calculations of operating modes. Traditionally, these calculations are based on symmetrical components, which require the building of equivalent circuits of various sequences. This approach can lead to errors both when identifying the operating modes and when modeling the RPA devices. Proper modeling of measuring transformers (MTs), symmetrical component filters (SCFs), and circuits connected to them effectively solves this problem, enabling the configuration of relay protection and automation systems. The methods of modeling the EPS in phase coordinates are proposed to simultaneously determine the operating modes of high-voltage networks and secondary circuits connected to the current and voltage transformers. The MT and SCF models are developed to concurrently identify the operating modes of secondary wiring circuits and calculate the power flow in the controlled EPS segments. This method is effective in addressing practical problems related to the configuration of the relay protection and automation systems. It can also be used when establishing cyber–physical power systems. For a comprehensive check of the adequacy of the MT models, 140 modes of the electric power system were determined which corresponded to time-varying traction loads. Based on the results of calculating the complexes of currents and voltages at the MT terminals, parametric identification of the power transmission line was performed. Based on this, the model of this transmission line was adjusted; repeated modeling was carried out, and errors were calculated. The modeling results showed a high accuracy when calculating the modules and phases of voltages using the identified model. The average error value for current modules was 0.6%, and for angles, it was 0.26°.