There is a tendency to increase the use of demand response technology in the Russian Federation along with other developing countries, covering not only large industries, but also individual households and organizations. Reducing peak loads of electricity consumption and increasing energy efficient use of equipment in the power system is achieved by applying demand management technology based on modeling and predicting consumer behavior in an educational institution. The study proposes to consider the possibility of participating in the concept of demand management of educational institutions with a typical workload schedule of the work week. For the study, statistical data of open services and sources, Russian and foreign research on the use of digital and information technologies, analytical methods, methods of mathematical modeling, methods of analysis, and generalization of data and statistical methods of data processing are used. An algorithm for collecting and processing power consumption data and a load planning algorithm were developed, including all levels of interaction between devices. A comparison was made between the values of the maximum daily consumption before and after optimization, as well as the magnitude of the decrease in the maximum consumption after applying the genetic algorithm. The developed algorithm has the ability to scale, which will increase the effect of using the results of this study to more significant values. Load switching helps to reduce peak consumption charges, which often represent a significant portion of the electricity cost.

The results of tests for resistance to abrasive wear on highly abrasive hard rock white electrocorundum are presented. The main material of fast-wearing elements of mining and processing equipment-110G13L steel (Gadfield steel) in comparison with other 9 grades of steel and cast iron, including specially developed wear-resistant foreign steels such as Hardox and Miiluks, is analyzed. The studies were carried out using an experimental stand for studying the material wearing process. On the stand the sample was fixed in a holding device and, after being brought into contact with the abrasive, it was rotated under a constant load. As a result of the experiments, it was confirmed that the order of placement of the tested materials in terms of increasing wear resistance coincides with their placement in terms of increasing hardness. At the same time, the wear resistance of the most resistant material – U8A steel after quenching – is about 4 times higher than this indicator for the least resistant components – low-carbon steel 25L, including gray and high-strength cast iron SCH21, VCH35. The wear resistance of 110G13L steel, as well as 65G, U8 steels in the hardened state, is from 1.5 to 2 times higher than that of foreign steels M400, H450, M500, H500. The results of the conducted studies allow us to evaluate the analyzed materials on the basis of their wear resistance and hardness indicators on the feasibility of using them in the manufacture of fast-wearing parts of mining equipment. Based on the research data, it seems promising to develop new ways to increase the wear resistance of domestic steel, including 110G13L steel traditionally used in mining.

Нефтегазовые компании активно внедряют цифровые решения в свои логистические сети с целью оптимизации процессов и увеличения эффективности бизнеса. В рамках исследования были выявлены текущие задачи управления цепочками поставок в нефтегазовой отрасли и их потенциальные решения за счет использования цифровых технологий. В результате была разработана модель управления цепочками поставок нефтегазовой отрасли на основе блокчейн-технологий BCSCM O&G (Blockchain-based Oil and Gas Supply Chain Model) с применением смарт-контрактов и интернета вещей (IoT) (Internet of Things). Экспериментальное моделирование функционирования с имитацией работы IoT на различных этапах цепи поставок подтверждает потенциал для улучшения управления цепями поставок, обеспечивая прозрачность, надежность и оперативность получения результатов. Запись данных от IoT в блокчейн предоставляет участникам цепочки поставок доступ к точной и актуальной информации в режиме реального времени, что уменьшает риск допущения ошибок и число манипуляций. Смарт-контракты автоматизируют выполнение условий договоров, что способствует повышению эффективности и снижению затрат. Внедрение блокчейн-технологий в сочетании с IoT не только улучшает контроль процессов, но и позволяет формировать более безопасные и оптимальные цепочки поставок. Эти инновационные подходы ведут к пересмотру традиционных методов управления, создавая более устойчивые и конкурентоспособные модели, соответствующие требованиям современного рынка. Таким образом, цифровая трансформация управления цепочками поставок в нефтегазовой отрасли представляет собой важный шаг к повышению общей эффективности и устойчивости бизнеса.