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Assessment of the impact of demographic, economic, and climatic factors on long-term forecasting of electricity consumption
Relevance: long-term electricity demand forecasting is a crucial task for efficient energy resource planning, de velopment of energy supply strategies, and ensuring the stability of the energy system. In the context of global changes such as changes in ambient temperature, population growth, and economic development dynamics, the accuracy of electricity demand forecasts becomes particularly important for making informed decisions in energy strategy formulation. Demographic, economic, and climatic factors shape the overall electricity consumption picture, but the impact of each of these factors can vary significantly depending on specific conditions. The weight coefficients of factors, calculated within regression models, allow for a quantitative assessment of the impact of each factor on long-term changes in electricity consumption. Thus, the assessment of the weight coeffi cients of factors is an important part of the analysis, as it allows improving the accuracy of forecasts and identify ing the most significant elements that require attention when planning electricity demand in the long-term fore casting. Therefore, the study of weight coefficients of demographic, economic, and climatic factors and their impact on electricity demand forecasting is an important step toward more accurate and grounded forecasts in the energy sector, which has practical significance for the development of sustainable and adaptable energy supply models in changing conditions. Aim: to analyze the main factors influencing the long-term forecasting of electricity consumption. Methods: there were used statistical methods of analysis and forecasting. Results: the analysis revealed that current electricity consumption has the greatest impact on long-term consump tion (59.54%), followed by demographic (21.91%) and economic factors (12.28%). The climatic factor has the least influence (6.27%). The model demonstrated high accuracy (RMSE = 0.1611) and can be applied for long term forecasting in the power system.
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The Cluster Approach for Developing Power Supply Systems in Uzbekistan's Remote and Hard-to-Reach Territories
Relevance: the Republic of Uzbekistan is gradually developing remote and hard-to-reach territories that possess reserves of various natural resources. One of the main problems that needs to be addressed is the issue of sustainable energy supply (electrification) for such territories. The use of traditional methods, such as constructing power lines, developing energy infrastructure, etc., in remote areas requires significant costs that will pay off over many years. In the context of developing market relations in the energy sector, it is necessary to create conditions for attracting entrepreneurs and businessmen, securing investments, introducing new technologies, ensuring staffing, and so on. Such work on electrifying remote areas needs to begin in advance due to the long development periods of electrification processes. The electrification of remote areas should occur through alternative and renewable energy sources (АRES) and the utilization of local resources. Therefore, analyzing the effectiveness of electrification methods for remote areas and developing proposals for their implementation is relevant. This work proposes the consolidation of distributed energy facilities by creating virtual clusters as a tool to ensure the sustainable development of power supply systems in remote and hard-to-reach areas. Aim: to analyze and develop proposals for the clustering (consolidation) of small energy facilities in remote and hard-to-reach areas to create sustainable conditions for their operation. Methods: theoretical approaches to clustering small and medium-sized energy facilities, system analysis methods, and multi-criteria evaluations were used, along with consideration of ESG principles. Results: an analysis was conducted, and proposals were developed for the effective clustering of distributed energy facilities in remote territories, enabling their consolidation and thereby ensuring the sustainable functioning and development of the power supply system.
Development of a Network Architecture for Real-Time Monitoring of the Condition of Centralized Inverters
Relevance: in power plants based on renewable energy sources, centralized inverters represent a key energy technological component. During operation, they are frequently exposed to deviations and failures due to load variations, environmental influences, thermal stresses, and aging of power electronic components. Therefore, comprehensive real-time monitoring of the electrical, thermal, and operational condition of centralized inverters, control of data quality (DQ), identification of risk indicators (FT, FU, FI), and state classification based on the reliability index (HI) are of significant scientific and practical importance. This approach enables improvement of inverter reliability, early detection of emergency conditions, optimization of maintenance activities, and prompt operational decision-making. Aim: to develop a network architecture based on real-time acquisition and processing of electrical, thermal, and operational parameters of centralized inverters; to design monitoring and diagnostic algorithms that provide data quality assessment, detection of critical conditions (WARNING/CRITICAL), and classification of inverter states in the “Green/Warn/Red” format based on the reliability index HI(t). Methods: in this study, the condition of centralized inverters was evaluated using the following methods: a parameter vector x(t) was formed based on the main electrical, thermal, and operational parameters obtained from the inverter (Udc, Idc, Uac, Iac, P, Q, cosφ, f, Ths, Tigbt, RPM, Fault). The collected data were subjected to quality control through time synchronization, range validation, and anomaly detection. Results: as a result of the proposed approach, a structural model, logical scheme and algorithm for real-time monitoring of centralized inverters were developed. A data quality control and recovery (filter/recovery) module was implemented, reducing erroneous decisions caused by unreliable data. Based on the analysis of electrical and thermal parameters, early detection of hazardous conditions was achieved, and an automatic transition logic to the “WARNING/CRITICAL” mode was established. The principle of color-based classification (Green/Warn/Red) and automatic notification based on the HI(t) index was substantiated. Under laboratory conditions, the TEX 6.2KBGN inverter was selected, parameter dynamics were investigated under various operating modes, and an informative set of indicators for monitoring was formed.
Study of the Efficiency of Optimizing the States of Complex Power Systems Using Artificial Intelligence Methods
Relevance. at present, a steady increase in global demand for electrical energy, the limited availability of conventional resources, and the necessity to ensure environmental safety and sustainability require more efficient use of resources in the energy production process. Taking these considerations into account, this paper presents the results of a study on the applicability and comparative performance of five artificial intelligence–based methods and algorithms for power system state optimization, namely the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Differential Evolution (DE), Artificial Bee Colony (ABC), and Ant Colony Optimization (ACO). This approach is significant not only from a theoretical perspective but also in terms of practical implementation and enhancing the stability of power systems. Aim: the objective of this study is to improve models and algorithms for short-term planning and operational control of modern complex power systems based on an analysis of the effectiveness of artificial intelligence methods in optimizing their operating states. Methods: the research employed modern theoretical approaches to the calculation and optimization of steady-state operating conditions of electric power systems, as well as nonlinear mathematical programming, system analysis, and artificial intelligence methods. Results: in general, the problem of optimizing power system operating states represents a complex multi-extremal problem involving a large number of equality and inequality constraints of simple, functional, and integral types. In certain cases, the use of traditional solution methods leads to the necessity of approximation, which results in reduced accuracy and difficulties associated with the unreliability of iterative computational processes. To overcome these difficulties, the application of artificial intelligence methods is considered essential. A comparative analysis of their performance was conducted using a representative case study. The results demonstrate that the Particle Swarm Optimization (PSO), Differential Evolution (DE), Artificial Bee Colony (ABC), and Ant Colony Optimization (ACO) algorithms exhibit approximately similar performance and show higher efficiency compared to the other considered methods.
A study of heat transfer in a flat-panel solar air heater with laminar convection
Актуальность: для Республики Узбекистан весьма актуальной проблемой можно считать снижение расхода традиционных видов топлива и улучшение экологического состояния регионов путем использования солнечной энергии в системах потребителей низкотемпературной тепловой энергии. К таким пользователям тепловой энергии относятся многочисленные сушильные установки сельхозпродукции и системы воздушного отопления, в которых часто применяются различного рода электрические калориферы и нагреватели. В этой связи наиболее простым и доступным способом получения теплоты для такого типа установок можно считать применение плоского солнечного воздухонагревателя, который без дополнительных расходов может не только отапливать помещения, но и сушить различного рода продукцию непосредственно в фермерских хозяйствах. Поэтому актуальной задачей является определение экспериментальным путем возможного теплового температурного потенциала такого коллектора в условиях республики и определения его тепловых параметров. Цель: определить степень подогрева воздуха в плоском солнечном воздухонагревателе, в летний период Республики Узбекистан; возможный температурный напор, возникающий в воздушном коллекторе и рассчитать такую важную теплотехническую характеристику как коэффициент конвективной теплоотдачи в канале коллектора. Методы: натурные исследования на экспериментальном образце воздушного плоского коллектора. В экспериментах по измерению температуры стенок абсорбера и воздушного потока на входе и выходе солнечного воздухонагревателя, использовались современные датчики температуры и тепловизор. Результаты: экспериментальным путем в июне месяце в г. Фергане в течении дней: 3, 17, 19, 20, 21 июня 2025 года получены значения температуры стенок абсорбера и воздушного потока на входе и выходе из коллектора при его движении с малой скоростью (0,28 м/c). На основании полученных данных по известным теплотехническим формулам проведены расчеты теплового потока и коэффициента теплоотдачи.
Modern promising development directions of alternating current converters plants
Relevance: the relevance of the work is explained by the fact that it presents modern development trends in powerful alternating current converters, which are widely used in various industrial production processes, agriculture, and other areas. Today, the most widely used method for creating powerful alternating current converters is the use of double energy conversion systems (DECs). The article presents the electrical scheme and functional tasks of the DECs system, as well as the technical and schematic capabilities of the IKM inverter, its hybrid and matrix structure, and the importance of the effective use of independent (autonomous) filters to improve the harmonic content of the output parameters. The article also shows that the hybrid structure can be used in conjunction with high-harmonic filters to improve the input power factor and eliminate the problems of electromagnetic incompatibility. Aim: To increase the effective application of various schematic objectives of modern high-power alternating current converters in industrial production, agriculture, and other fields through the use of dual energy conversion systems (DECs). Methods: the most widely used double energy conversion systems (DECs) and simulation modeling methods were used to create powerful AC converters. Results: The use of rectifiers with pulse width modulation and harmonic filter in the creation of dual energy converters, which are widely used in various industrial production processes, is explained by the fact that it is possible to improve the input power factor of the device, increase the input power factor of the device, and solve the problem of electromagnetic compatibility that may arise with the network, and the matrix structure of the converter allows you to increase or decrease the output voltage frequency relative to the primary source frequency, while increasing the reliability of the system.
Modeling and Analysis of Various Operating Modes of 0,4 kV Low Voltage Electrical Networks
Relevance: the annual increase in electricity demand, particularly the uneven distribution of loads in 0.4 kV low-voltage distribution networks, leads to a deterioration in power quality. In such networks, asymmetrical connection of consumers across phases often results in voltage unbalance, increased active and reactive power losses, and conditions that negatively affect the operating modes of electrical equipment. In practice, the design or operation of many low-voltage electrical networks is evaluated based on simplified calculation methods. This leads to an insufficient accounting of real operating modes, especially asymmetrical load conditions. Consequently, actual voltage levels in the network, phase-to-phase unbalance, and power losses are not accurately assessed. The results obtained are of significant scientific and practical importance for developing recommendations to reduce electricity losses, improve voltage quality, and ensure the optimal operation of low-voltage networks. Aim: the main objective is to model the symmetrical and asymmetrical operating modes of a 0.4 kV low-voltage electrical network using DIgSILENT PowerFactory software and to conduct a comprehensive analysis of the impact of phase load distribution on phase-to-phase voltage unbalance and active/reactive power losses in the network. Methods: computational modeling methods were used to study the operating modes of low-voltage networks. Results: Symmetrical and asymmetrical operating modes of the 0.4 kV low-voltage electrical network were modeled in the DIgSILENT PowerFactory software package, and their impact on the electrical network was evaluated. The results showed that the asymmetrical distribution of loads across phases in low-voltage electrical networks leads to a decrease in power quality and an increase in power losses.
Identification of Factors Influencing the Improvement of Long-Term Operational Reliability of Centralized Inverters
Relevance: in power supply systems based on renewable energy sources, centralized inverters represent a key functional component. Their reliable and stable operation plays a decisive role in ensuring the efficiency of electricity generation and economic sustainability. Under real operating conditions, inverters are influenced by load variations, harmonic distortions, grid voltage quality, thermal regimes, mechanical impacts, and maintenance levels. These factors accelerate component degradation, increase the probability of failures, and reduce the remaining useful life. Therefore, identifying the electrical, thermal, mechanical, and operational factors affecting the reliability of centralized inverters and evaluating their interrelationships through correlation analysis is of significant scientific and practical importance. Aim: to identify the main electrical, thermal, mechanical, and operational factors influencing the long-term reliability of centralized inverters; to evaluate their relationships with the reliability index and remaining useful life (RUL) using correlation analysis; and to establish a hierarchical structure of dominant parameters that have the greatest impact on degradation processes. Methods: key operational parameters were selected based on IEC, IEEE, GOST, and ISO standards. Current, voltage, power, total harmonic distortion (THD), temperature, vibration, and maintenance indicators were collected using monitoring systems. Thermal, load, and harmonic effects were evaluated using mathematical models. The reliability function R(t), mean time between failures (MTBF), and failure intensity λ were calculated. Relationships between parameters were analyzed using Pearson (r) and Spearman (ρ) correlation coefficients. The results were visualized using heat maps. Dominant factors were identified, and their impact on reliability was evaluated using a comprehensive approach. Results: the study identified the main factors affecting the reliability of centralized inverters, and their interrelationships were quantitatively evaluated. Correlation analysis revealed that internal temperature (Tin), harmonic distortion (THD), number of temperature cycles (Ncycle), rate of temperature change (dT/dt), and voltage deviation (ΔU) exhibit strong negative correlations with the reliability index. Heat map analysis confirmed that Tin is the central driver of degradation. The efficiency of the cooling system and the quality of maintenance were shown to be critical factors in improving reliability. The proposed approach enables prediction of the remaining useful life, optimization of preventive maintenance, and reduction of operational risks.
Analysis of the Efficiency of the RITM-200 Nuclear Power Installation Using Neutron-Physical and Thermo-Hydraulic Modeling for Autonomus Energy Systems
Relevance: in remote regions facing energy shortages, reliable autonomous energy sources are essential. Small modular reactors (SMRs) can provide continuous power supply with high safety standards and extended fuel cycles. Aim:to analyze the efficiency of the RITM-200 nuclear power installation using neutron-physical and thermo-hydraulic modeling for autonomous energy systems. Methods: the study applied neutron-physical modeling of the reactor core considering fuel composition, enrichment, and absorbers, as well as thermo-hydraulic calculations covering temperature regimes, heat transfer, and the Rankine cycle. Results: the use of silumin and erbium dioxide in the fuel composition significantly increases fuel burnup depth and fuel cycle duration, while enhancing operational safety. The calculations confirm the applicability of the installation for energy supply in hard-to-reach regions.
Development of a maximum power point tracking algorithm for a counter-rotating dual-rotor wind turbine
Relevance: although the share of renewable energy sources in the global energy system is increasing year by year, the rapid growth in demand for electricity and the limited availability of traditional fuel resources necessitate the development of new, highly efficient energy technologies. In particular, wind energy is of particular importance due to its environmental cleanliness, renewability, and wide geographical coverage. In particular, according to the Bes law, the maximum energy received from the wind flow is limited by 59.3%, and the circular flow (wake) formed behind the rotor further increases energy losses. As a result, the efficiency of SRWT systems in low and medium wind speeds is significantly reduced. From this point of view, counter-rotating two-rotary wind turbines (CRWT) have recently become the focus of scientific research. In CRWT systems, the second rotor allows for the reuse of the circular flow energy exiting the first rotor, increasing the total power factor to 15-30%. This makes CRWT a particularly promising solution for regions with low wind speeds. However, the widespread implementation of CRWT systems is associated with a number of unresolved scientific and technical problems. One of the most important among them is the task of accurate and stable monitoring of the maximum power point tracking (MPPT). Traditional MPPT algorithms (TSR, Perturb & Observe, Hill Climb, and others) are mainly developed for single-rotor systems, and their direct application to two-rotor, aerodynamically interconnected systems is considered ineffective. In the CRWT system, due to the aerodynamic interaction between the front and rear rotors, the distribution of torques, and the zero dependence of rotational speeds, there is no single power extremum, and the problem of multidimensional optimization arises. This leads to a decrease in the stability of existing MPPT algorithms, power fluctuations, and energy losses. Moreover, despite the growing need for intelligent control, real-time adaptation, and intelligent algorithms in modern wind energy systems, research on high-speed and stable MPPT algorithms adapted for CRWT, taking into account rotor interaction, is insufficient. Existing scientific works mainly focus on aerodynamic or structural aspects, and the issue of deep integration of control algorithms is insufficiently covered. Aim: development of a stable and highly efficient real-time monitoring algorithm for the maximum power point tracking (MPPT), taking into account aerodynamic and electromechanical interactions between the front and rear rotors for a two-rotor counter-rotation wind turbine (CRWT), as well as scientific substantiation of its energy, dynamic, and economic efficiency. Methods: the complex of theoretical, computational, algorithmic and experimental research methods: optimization theory, gradientless search, and heuristic methods are used. Results: an expanded mathematical model is proposed that takes into account the aerodynamic interaction between the front and rear rotors in a two-rotor wind turbine rotating oppositely. A new hybrid MPPT algorithm has been developed that determines individual optimal working points for the front and rear rotors and adaptively adjusts their interaction.
A decentralized control method for eliminating voltage asymmetry in low-voltage electric networks with integrated solar panels
Relevance: modern electric power systems based on a centralized management architecture demonstrate vulnerability in emergency and non-standard situations. Such events indicate the need to move to a new management model focused on decentralized and sustainable solutions, especially in the context of the active integration of distributed photovoltaic (PV) sources into low-voltage networks. In the context of the energy transition in Uzbekistan, accompanied by digitalization, the development of "green" generation and the introduction of Smart Grid elements, the task of ensuring voltage symmetry and reliability of power supply with a high proportion of renewable energy sources is of particular relevance. One of the most effective approaches to solving these problems is decentralized management based on local intelligent controllers, which ensures the autonomy, adaptability and stability of electrical networks. Aim: to substantiate the effectiveness of using a decentralized control system to reduce voltage asymmetry and increase the stability of low-voltage electric networks with integrated solar panels, using local measurements, IoT infrastructure and phase redistribution. Methods: comparative analysis of Smart Grid control architectures, assessment of the influence of single-phase generation on voltage symmetry, as well as structural modeling of cascade and general decentralized control circuits were used. Results: the proposed architecture of decentralized management in PV networks provides high adaptability, ease of implementation and reduces the need for a large-scale communication infrastructure.
Increasing the thermal efficiency of a solar air heater coated with a functional nanocomposite ceramic film
Relevance: solar air heaters are widely used in low-potential thermal systems, and their practical importance in industry, agriculture, and construction is steadily increasing. However, the practical thermal efficiency of these devices is significantly limited by radiative and convective heat losses occurring at the absorber surface. In the literature, various design solutions aimed at improving efficiency have been proposed, including the installation of turbulators in the flow channel, the creation of artificial roughness, and the complication of airflow direction. Nevertheless, such approaches often lead to increased pressure losses and higher structural complexity of the system. Therefore, improving the thermal efficiency of solar air heaters without modifying their geometric structure by means of modifying the physical properties of the absorber surface is considered an актуальная scientific and practical problem. Aim: the objective of this study is to analyze the thermal efficiency of a solar air heater with a metal absorber coated with a thin ceramic composite film based on an energy balance model and to compare its performance with that of a solar air heater of simple design under identical operating conditions. Methods: In this study, the thermal processes of the solar air heater were analyzed using an energy balance model based on the law of conservation of energy. The ceramic composite film was considered as a selective surface, and its influence on the solar radiation absorptivity coefficient (α) and the emissivity coefficient (ε) was taken into account. The outlet air temperature and thermal efficiency indicators for the conventional absorber and the ceramic-coated absorber were determined and compared under identical operating conditions. Results: the calculation results showed that the thermal efficiency of the solar air heater coated with a ceramic composite film increases by 17–19% compared to a solar air heater of simple design. This increase is explained by the enhancement of the solar radiation absorptivity coefficient and the reduction of the emissivity coefficient of the absorber surface. It was established that the proposed approach allows an increase in the thermal efficiency of the device without changing the geometry of the flow channel and without additional pressure losses, which represents a significant practical advantage.
Improving energy efficiency of pumping stations using optimal control methods
Relevance: In our republic, increasing the energy efficiency of large pumping stations (PS) necessitates investigating their joint operating modes with the electric power system (EPS), considering the combined influence on their respective modes. Aim: to analyze the mutual influence of large pumping station operating modes on electric power system modes, based on control theory methods, as well as methods for improving PS energy efficiency through optimized control. Methods: methods of system analysis were employed, and mathematical models for automatic control of PS operating modes were applied. Mathematical modeling and analysis methods were also utilized, allowing for the investigation of PS and EPS operation under various operating conditions and the determination of optimal functioning conditions. Results: the results confirm the possibility of using mathematical models for automatic control and optimization to analyze the efficiency of joint operating modes of large PS and EPS. The obtained results can be used in the design, modernization, and operation of pumping stations, as well as in the development of automated control systems for their operating modes.
Pump station control system under climate risks and temperature extremes
Relevance: in extremely harsh operating conditions of pump installations in open areas, especially in the mining and water management industries, the problem of equipment freezing at low temperatures becomes particularly acute. This leads to damage to pump units, disruptions in technological processes, and additional repair costs. Therefore, the development and implementation of simple and reliable automatic anti-freeze protection systems is of great relevance. Aim: development and experimental validation of the performance of an automatic anti-freeze protection system for a pump unit based on a microcontroller and temperature sensor. Methods: the study used digital signal processing methods, microcontroller-based control, simulation modeling of the decision-making algorithm, and laboratory testing on a model installation. Results: a system was developed that implements an algorithm for assessing the condition of the main pump based on current and ambient temperature. When a freezing hazard is detected, an auxiliary pump is automatically activated to maintain minimal water circulation. The functionality of the circuit, temperature response accuracy, and reliability of all components during extended operation have been experimentally confirmed.
Development of water and energy-saving measures for large pumping stations
Relevance: in recent years, in connection with the energy transition taking place in many countries worldwide, this process in Uzbekistan has been carried out with an intellectualization of key energy efficiency issues. This is particularly true for the operation of large pumping stations. Such stations operate in cross-border regions. The largest unique pumping stations of the Amu-Bukhar, Amuzang, and Karshi cascades operate in Turkmenistan. Analysis of global trends indicates potential for expanding the use of mobile power units. The use of mobile power units for agriculture and water management should be most developed, with an increase in the reliability of the mobile energy service system. The development of innovative technology, including the justification of the structure and technical service specialized in servicing mobile power units, is a pressing issue of scientific and practical significance. Aim: development and implementation of innovative technology for a mobile energy service system to improve the reliability and energy efficiency of pumping units. Methods: international experience and comparative analysis of methods for controlling the main parameters of pumps are used to ensure regulation of energy savings Results: the present research was conducted to create favorable conditions for the implementation of artificial intelligence technologies for energy resource management and optimization of energy efficiency of pump operation. The main direction for increasing the efficiency of the mobile energy service system is the modeling of optimal operating modes of systems, taking into account the probabilistic nature of changes in the operating factors.
Algorithm for estimating the required flexible capacity reserve of the power system
Relevance: the increasing share of renewable energy sources, characterized by high variability and low predictability of their output, imposes new requirements on the reliability and stability of electric power systems. Significant power fluctuations of wind and solar power plants lead to an increase in the amplitude and frequency of deviations in the power balance, which necessitates the availability of sufficient flexible reserve capacity to enable rapid response to changes in load and generation. Existing methods for estimating reserve capacity often rely on averaged forecasts or static characteristics of the power system, which reduces the accuracy of determining flexibility needs under the increasingly complex structure of the energy balance. In modern power systems, there is a need to develop algorithms capable of accounting for the dynamic properties of the grid, the probabilistic nature of renewable energy operation, and integrating data from system operational dispatching. Developing an algorithm for determining the required flexible reserve capacity is an important step toward improving power supply reliability, optimizing the operating modes of generating equipment, and reducing operational costs. The development of such algorithms is particularly relevant for countries that are actively deploying renewable energy and modernizing their energy infrastructure. Therefore, the proposed study addresses one of the key challenges of modern electric power engineering and possesses high scientific and practical significance. Aim: development of an algorithm for estimating the required flexible capacity reserve of power systems considering variable generation from photovoltaic and wind power plants, as well as daily fluctuations in electricity consumption. Methods: there were used statistical methods of analysis and forecasting. Results: the hourly required flexible capacity reserves necessary to maintain the power balance of the electric power system under variable generation from renewable energy sources and demand have been determined.
Improving the output voltage quality in hybrid power plants using an integrated battery and supercapacitor system
Relevance: this article examines improving the quality and stability of electrical energy in solar-diesel hybrid power plants through the use of an integrated hybrid energy storage system based on batteries and supercapacitors. The main challenges of hybrid power plants include rapid fluctuations in inverter output voltage, dynamic load changes, variability in renewable energy sources (solar radiation), and harmonic distortion caused by nonlinear loads. These factors lead to increased total harmonic distortion (THD), phase errors, and RMS voltage instability. These factors lead to malfunctions in consumer equipment, reduced energy efficiency, and increased diesel generator over-runs. Aim: improving the quality of electrical energy supplied to the grid by reducing rapid voltage fluctuations, peak loads and harmonics (reducing the harmonic distortion coefficient, phase error and amplitude stability). Methods: international experience and methods of comparative analysis of demand management are used. Results: the combined use of batteries and supercapacitors in hybrid power plants offers significant benefits, including improved voltage stability, reduced harmonic distortion, extended battery life, and reduced diesel generator power consumption. This solution is highly effective for use in low-voltage grids, autonomous power supply for rural areas, industrial facilities, and Smart Grid systems..
Modern methods of energy saving in industrial enterprises
Relevance: the industrial sectors of Uzbekistan — metallurgy, petrochemical, construction, machinery and textiles - are the largest consumers of electricity, and the growth of their production analyze the load on the energy system and increases the cost of production. Government programs and updated laws on energy conservation require a reduction in specific energy consumption and the introduction of energy-efficient technologies. Energy saving today is not only about reducing costs, but also meeting international environmental requirements, In addition, in Uzbekistan and a number of other countries, the introduction of modern energy saving methods is supported by government programs, standards and tax benefits. Therefore, the study of modern methods of saving electricity is an urgent task for enterprises, researchers and future specialists, ensuring sustainable development and reducing operating costs. Aim: to analyze modern methods of saving electricity at industrial enterprises of the Republic of Uzbekistan and to study in detail the efficiency of variable frequency electric drives (VFD) as one of the key energy saving tools. Methods: The study utilized systemic, comparative, and analytical approaches to comprehensively evaluate modern energy-saving technologies at industrial enterprises. Thus, the combination of applied methods—structural analysis, mathematical modeling, regulatory review, and comparative assessment—enabled a comprehensive study of energy savings potential and the identification of the most effective solutions for industrial enterprises in the Republic of Uzbekistan. Results: the study showed that the greatest energy savings potential lies in pump, fan, and electric drive equipment. The implementation of variable frequency drives reduces energy consumption by 30–40% and pays for itself within two years on average. Additionally, VFDs reduce inrush currents, improve process control, and reduce operating costs. A comprehensive combination of VFDs, reactive compensation, energy-efficient motors, and digital monitoring systems can reduce overall plant energy consumption by 25–45% and increase equipment reliability.
Energy-efficient solar heating using a genetic algorithm
Relevance: the growth of global energy consumption, rising electricity tariffs, and increasingly stringent environmental requirements stimulate the search for sustainable and energy-efficient solutions for building heating. The residential sector accounts for a significant share of total energy consumption, especially in regions with cold winters where the main load falls on heating. Traditional electric boilers, despite their simplicity, exhibit high dependence on the power grid and contribute substantially to nighttime peak loads. In this regard, improving the energy efficiency and autonomy of heating systems becomes an urgent scientific and engineering challenge. Aim: to develop, mathematically describe, and simulate a hybrid residential building heating system (PV–TES–BESS) equipped with a GA-based operational scheduler, targeting Tashkent winter conditions, with the aim of minimizing daily grid energy consumption while maintaining T_in ≥ 20°C Methods: international experience and comparative analysis of practical implementations of these control methods are utilized. Results: modeling results for winter conditions in Tashkent show that the proposed system significantly reduces grid dependence and increases the autonomy of heating. The developed approach can serve as a basis for creating intelligent solar heating systems effective in cold climate regions.
Method of automation of chemical desalination of water at TashChP
Relevance: thermal power plants (TPP, TChP) are among the largest consumers of water. They are characterized by a large amount of wastewater and pollution, which are dangerous for the natural environment. The wastewater from the chemical plant of TashTChP is largely formed by water from loosening rinses, spent regeneration solutions and wash water from ion-exchange filters. For chemical desalination plants, part of the effluent contains excess acid, usually sulfuric acid, part of the effluent contains excess alkali, and the neutralized effluent contains a significant amount of salt components, often exceeding maximum permissible concentrations (MPC), for example, for sulfates and chlorides. Aim: to analyze and substantiate the application of the electrical conductivity measurement method, followed by the algorithmization of salt concentration calculation in water, to improve the control of regeneration processes for hydrogen-cation exchange demineralization filters at a thermal power plant. Methods: the electrical conductivity measurement method and algorithmization of salt concentration calculation in water are utilized. Results: Automation of water-chemical regime control processes and cation exchange resin regeneration processes in filters optimizes reagent and water consumption, and reduces downtime of filtration equipment.
Analytical review of contemporary carbon footprint and life cycle assessment methodologies for renewable energy technologies and prospects for their adaptation to Central Asian conditions
Relevance: The review shows that CF and LCA methodologies for renewable energy technologies are globally well developed, but their regional applicability remains highly uneven, with Central Asia still underrepresented. The analysis identifies the main barriers to their transfer to regional conditions, including the absence of local life cycle inventory datasets, insufficient consideration of climatic degradation factors, and limited treatment of end-of-life scenarios. Priority research directions include the development of regional inventories, dynamic LCA approaches, and climate-adapted carbon footprint models for renewable energy systems in arid regions. Aim: The aim of this review is to systematize contemporary carbon footprint and life cycle assessment methodologies for the principal renewable energy technologies and to identify the main methodological gaps, limitations, and prospects for their adaptation to the conditions of Central Asia. Methods: The study applies a PRISMA-inspired systematic literature review approach. Publications from 2005–2025 were collected from major scientific databases of Scopus, Web of Science, Google Scholar, and eLibrary, screened according to predefined inclusion criteria, and 54 relevant studies were selected from approximately 450 identified sources for the final qualitative analysis. Results: The review shows that CF and LCA methodologies for renewable energy technologies are globally well developed, but their regional applicability remains highly uneven, with Central Asia still underrepresented. The analysis identifies the main barriers to their transfer to regional conditions, including the absence of local life cycle inventory datasets, insufficient consideration of climatic degradation factors, and limited treatment of end-of-life scenarios. The priority directions for future research include the development of regional inventories, dynamic LCA approaches, and climate-adapted carbon footprint models for renewable energy systems in arid regions.
Automated device for cleaning solar panels from dust contamination
Relevance: in the context of global climate change, renewable energy sources play a crucial role, particularly it is solar energy. . Therefore, in recent years, new photovoltaic power plants (PVP) of different capacities have been built. According to data, by 2030, electricity (EE) generation in Uzbekistan will reach 120,8 billion kWh/year, where the share of PVP will be 9,9 billion kWh (8.2 %). It should be noted that dustiness of the optical surface (OS) of solar panels (SP) of PVP is a serious problem that significantly reduces their efficiency. Dust contamination on the OP can reduce the efficiency of panels to 50 %, thereby reducing EE generation. Therefore, research on the development of automated cleaning devices is relevant. Aim: development and analysis of technical parameters of an energy-efficient automated device for cleaning the optical surface of a solar panel from dust contamination. Methods: international experience and methods of comparative analysis of demand management are used. Results: based on a comparison of various devices, an energy-efficient and automated device for cleaning solar panels from dust contaminants has been developed, which allows one cleaning cycle to be performed in 24 seconds.