The agro-industrial complex of the Republic of Belarus, whose products account for about 7.0 % of gross domestic product (GDP), is an important sector of the country's economy, which ensures food security and a high share of exports. Belarusian products are exported to 117 countries. Reliable energy supply plays a key role in the stabilization and efficiency of the development of the agro-industrial complex of our country. Given global economic and environmental challenges, the global trend toward a transition to low-carbon energy and a sustainnable economy, as well as volatile energy prices, the design of an effective strategy for the development of the agricultural sector’s energy complex is particularly relevant. An important aspect of increasing the reliability of agricultural energy supply is the growth of resilience to emergencies related to natural disasters, leading to short-term, but very sensitive damage and destruction caused to industrial facilities as a result of disruption of energy supply. The article presents the results of a comprehensive study of energy consumption efficiency in the agro-industrial sector of the Republic of Belarus; based on these results an analysis of existing problems is made and recommendations for improving the efficiency of energy resources use are proposed. The implementation of these recommendations should not only increase the competitiveness of the agricultural sector, but also ensure the sustainable development of the economy as a whole. Also, it is shown that the introduction of new technologies into the energy supply of the agro-industrial complex of Belarus can significantly increase the economic efficiency of energy supply to small towns and rural areas. It is proposed to create distributed integrated energy systems (to be used as core energy supply facilities) based on energy hubs that combine existing electric, gas distribution and heating networks to optimize the use of traditional and local energy resources. The innovative solutions will not only reduce production costs and improve the reliability of energy supply, but also optimize the consumption of traditional energy sources, which is becoming particularly relevant in the context of growing interest in renewable energy sources, the need for the diversification of energy resources, and decarbonization of power industry and manufacturing.

LEDs are based on a semiconductor crystal with a surface in Miller indices (111), formed by diatomic molecules of gallium arsenide or indium phosphide in bulk clusters. A structure of positively charged ions of gallium and arsenic atoms in gallium arsenide and as well as of an exchange interaction between positively charged ions of indium atoms arises inside them. The positively charged skeleton is compensated by an electron cloud. An electric current of conduction and displacement occurs in LEDs. The crystal surface is covered with a monolayer of diatomic molecules with the formation of quadrate voids, which can accommodate single impurities (up to four different atoms) with the formation of negative ions. A crystal of gallium arsenide or indium phosphide with an admixture is used as the cathode, and aluminum is used as the anode. The ionization of negative ions of various impurities occurs under the influence of temperature and an applied external electric field. After ionization, free electrons arise which form an electric conduction current in the columnar void. An electric conduction current determines the power of light emission. The size of the light-emitting surface of the LED is ~10´10 nm. In the contact zone of the anode and cathode, a partial scattering of the electron flow of the conduction current occurs, which significantly reduces the power of light emission. A scattering is caused by the energetic transition of a free electron from the upper energy level to the underlying level according to the scheme as it occurs in atoms. The volt-ampere characteristics for LEDs are determined by measuring the electric bias current in the external circuit and the voltage at the current source. These data do not allow us to analyze the operation of the LED, since the LED operates on the conduction current that occurs inside it. It is difficult to determine what proportion it makes up of the total displacement current measured in the external circuit. As a result of the theoretical calculation, the optimal electrical conduction current in the LED should not exceed 10 mA, while the supply voltage ranges from 1.3 to 3.5 V. The LED is powered only through ballast resistance using pulse width modulation.

Modern transformer diagnosing is a lengthy and costly undertaking. A series of complex tests is often necessary, as modern diagnostic methods do not always clearly indicate the of electrical machines and transformers is largely determined by the reliability of the windings, which, in turn, is largely dependent on the condition of the winding insulation. Traditional test methods include measuring various parameters such as short-circuit impedance, no-load loss, transformation ratio, magnetization current, winding resistance and others. Currently, one of the most promising diagnostic methods is the frequency response method. The frequency response method has found wide application in detecting and assessing transformer damage during transportation. Also, this method, using a single set of measurements, provides information on the mechanical condition of the magnetic core, windings, and pressing structure. It has proven its ability to detect damage in windings during short-circuit resistance tests. This detection method complements visual inspection, as it makes it possible to detect small changes in the size of the windings, which are not always visible. Yet, small movements of taps and other parts are not always easily detected using frequency characteristics. In this paper, a method based on frequency response analysis using the method of three voltmeters and convolutional neural networks is proposed for detecting and classifying winding defects.

Energy consumption is currently growing at an accelerating pace, evidenced by the mechanization of industrial and domestic sectors, rising energy costs for quality of life, and the advent of electric vehicles. At the same time, the rational and efficient use of energy sources is becoming increasingly important. In particular, the use of power active filters (PAF) is an urgent area in the electric power industry. The advantage of PAF is the ability to simultaneously compensate for both the reactive power of the electrical load at the fundamental frequency and higher harmonic distortion, which significantly improves the quality of electricity in distribution networks. The implementation of PAF control systems based on instantaneous power theory (pq-theory) has significantly advanced in recent decades. This approach provides effective compensation in steady-state conditions, but its effectiveness decreases with dynamic load changes. The most advanced PAF control methods are those based on neural networks and digital signal processing. In most cases, an adaptive threshold logic element (Adaline) is used as the basic element of a neural network. This element is a second-order digital FIR filter that can be configured using a steepest descent algorithm. This structure allows adaptive filtering of harmonic components in real time. Furthermore, the use of digital signal processing technologies makes it possible to use adaptive spectral estimation and interference suppression methods, which enable controllers to adjust their parameters in real time when the non-sinusoidal mode in the network changes. This is especially important when working with pulsed electrical loads, characterized by rapid changes in the spectral composition of the current. The present article analyzes known methods for controlling the PAF for electrical circuits when connecting a pulsed electrical load. It was found that the adaptive method is the most effective one in terms of minimizing the harmonic distortion coefficient (THD) of the current with a transient settling time of t £ 0,01 s, where the THD after connecting the PAF is 1.57%. This confirms the high efficiency of intelligent control algorithms for ensuring power quality in modern electric power systems.

In accordance with the Concept of the National Strategy for Sustainable Development of the Republic of Belarus for the period up to 2035, the main objective in the gas sector is to maintain production assets at a level that ensures safe energy supply. The basis of these production assets are gas distribution networks, directly gas pipelines. It is known that the factor that poses the greatest threat to the technical condition of steel underground gas distribution pipelines is corrosion. To compensate for the global corrosion factor, steel underground gas pipelines are equipped with special anticorrosive agents, including protective insulating coatings. Bitumen-mastic insulating coatings (BMIC) are the most common coatings in the domestic gas distribution system, which were used earlier than others in industrial practice for corrosion protection. The article provides a comprehensive analysis of BMIC in terms of their design, materials used, and the evolution of coatings from bitumen-mineral to bitumen-rubber and further to bitumen-polymer. A brief overview of the development of theoretical provisions on the structure, physico-chemical properties and component composition of bitumen is presented. The general mechanism of structural degradation of bituminous materials is shown, characterized by a gradual increase in internal stresses, increased viscosity, and brittleness, leading to complete and irreversible destruction. Depending on the temperature conditions and the associated intensity of oxidative processes, autooxidation (low-temperature, low-intensity) and thermal (high-temperature, intensive) oxidation of bitumen hydrocarbon compounds are distinguished. The place of autooxidation and thermal oxidation at the pre-operational (technological) and operational stages of the life cycle of bitumen materials is shown, as well as the influence of temperature effects on the coating material at the technological stage, manifested in an increase in the heterogeneity of the initial state of the coating before its operation.

The steam turbine installations in nuclear power units are of the condensation type. The main parameters affecting the performance of condensation-type steam turbine installations are the steam flow rate at the turbine inlet, the temperature variation, and the flow rate of cooling water entering the condenser. Any change in these parameters directly influences the amount of electrical energy produced by the steam turbine. To study their influence, it is necessary to collect a large amount of data and synthesize a mathematical model. Data collection through measuring and recording equipment is a complex, time-consuming process associated with both the technological time required for gathering and subsequent processing. Simulation modeling is a modern research tool that allows studying energy systems without disrupting the technological process. This modeling involves developing an analogue of an existing object in a graphical software environment where geometric and physical parameters characterizing the object’s properties are defined. The results obtained from solving the simulation model must be compared with data from characteristic operating modes of the examined object. The present paper aims to develop a simulation model for assessing the performance of a condensation-type steam turbine installation of a nuclear power unit model K-1000-60/1500-2. This steam turbine installation is typical for nuclear power units of the VVER-1000 type. The data obtained from the simulation model will be used to construct a mathematical model determining the parameters characterizing the operation of the condensation steam turbine installation.