In the context of the rapid development of digital technologies and increasing demands on energy efficiency, sustainability and competitiveness of industrial enterprises, the fuel and energy (FEC) and mineral resources (MR) complexes are undergoing major changes. Digital transformation is becoming a key factor in improving the efficiency, reliability, and sustainability of production processes, as well as an important element of the strategy for technological sovereignty and the modernization of production systems. Modern approaches to managing equipment and process chains are based on the use of machine learning methods, big data analysis, digital modeling, and the creation of digital twins, which, in turn, allows not only the optimization of technological and business processes, but also the formation of new control architectures from local systems to industrial metauniverses.

This study investigates the use of Singular value decomposition to decompose time series of electricity consumption from substation feeders. The goal is to identify and classify the electrical load patterns of mining enterprises. The need for continuous improvement in process efficiency is dictated by current trends and tendencies towards increased consumption of fossil fuels and energy resources. The proposed algorithm uses the decomposition results to identify similarities in consumption patterns, enabling the categorization of loads into broader groups. Based on the results of the analysis of electricity consumption data for two independent feeders, the formation of similar recurring characteristic load changes (temporal patterns) with a period of three days was identified. The results facilitate the automated typification and classification of load profiles. This is vital for integrating economic incentives into demand management and for assessing the feasibility and potential of consumer participation in load schedule regulation via demand side management technologies. The proposed algorithms enable the use of these typical consumption profiles to calculate quasi-dynamic electrical modes, supporting tasks related to the long-term development of energy supply systems and energy efficiency improvements for mining enterprises.

Grinding is the most energy-intensive process among all stages of raw material preparation and determines the course of subsequent ore beneficiation stages. Level of electricity consumption is determined in accordance with load characteristics forming as a result of ore destruction in the mill. Mill drum speed is one of process variables due to which it is possible to control ore destruction mechanisms when choosing speed operation mode of adjustable electric mill drive. This study on increasing energy efficiency due to using mill electric drive is based on integrated modelling of process equipment – grinding process and electromechanic equipment – electric drive of grinding process. Evaluating load torque by means of its decomposition into a spectrum, mill condition is identified by changing signs of frequency components of torque spectrum; and when studying electromagnetic torque of electric drive, grinding process is monitored. Evaluation and selection of efficient operation mode of electric drive is based on the obtained spectrum of electromagnetic torque. Research results showed that with increasing mill drum speed – increasing impact energy, load torque values are comparable for the assigned simulation parameters. From the spectra obtained, it is possible to identify mill load condition – speed and fill level. This approach allows evaluating the impact of changes in process variables of grinding process on parameters of electromechanical system. Changing speed operation mode will increase grinding productivity by reducing the time of ore grinding and will not lead to growth of energy consumption. Integration of digital models of the technological process and automated electric drive system allows forming the basis for developing integrated methods of monitoring and evaluation of energy efficiency of the entire technological chain of ore beneficiation.

In the article the basic principles of energy conservation and efficiency of the enterprises of metallurgy. The analysis of the energy saving potential in the metallurgical complex. We describe the stages of implementation of energy management, energy analysis of the structure of the enterprise.

In the case of phosphoric furnace the influence of changes in voltage and current to the power distribution in ore-smelting furnaces between the arc shunt resistance and melt are considers.

The method of diagnostics and estimation of a residual resource of the electromechanical equipment, based on the analysis of electric parameters is offered. Block diagram’s of a diagnostic complex and the data processing program are presented. The way of application of artificial neural networks for data processing of diagnostics and an estimation of a residual resource is considered, and also levels of influence of damages on working capacity of the equipment are resulted.

The review of existing methods of technical diagnostics of an industrial electric equipment is submitted, expressions for definition of the basic diagnostic parameters are resulted at diagnostics of a condition of the equipment on electric parameters.

Problems of increase reliability electro-supply distributive networks of an average voltage at the mountain enterprises are considered. It is shown, that introduction decentralized with application of automatic points of sectioning considerably reduces systems consumption the electric power. Algorithms decentralized managements of emergency operation work of a network are resulted.

Mathematical model of induction motor with installation of longitudinal capacitive compensation is considered. Starting modes of asynchronous motor without load and with significant load on the shaft, without installation of longitudinal capacitive compensation and with longitudinal compensation are investigated. Starting modes of asynchronous motor in soft and rigid network are analyzed, improvement of starting conditions with considerable loading on a shaft of a powerful remote asynchronous motor in the scheme with the installation of longitudinal capacitive compensation (reduction of acceleration time, increase of voltage on the motor terminals, disappearance of negative values of moment) is shown. Conditions of occurrence of electromagnetic instability of start mode, permissible parameters of longitudinal compensation and shunt resistance are defined, at which occurrence of instability is excluded, the boundary of stable operation of investigated motor in start mode is set.