Scientific achievements and developments
Most Significant Research Results (2025)
The Institute of General Energy of the NAS of Ukraine has developed a mathematical model for the operation of distributed generation from wind and solar power plants integrated with energy storage systems. Based on instantaneous power values, this model determines generation energy, charge-discharge processes, and technical-economic indicators, while also establishing the conditions required to achieve self-sufficiency modes.
Modeling of transient modes within the “wind power plant – energy storage system” framework demonstrated that utilizing an energy storage system with a capacity equivalent to that of the wind power plant, combined with adaptive regulators, ensures compliance with regulatory requirements for frequency and active power deviations in the integrated power system.
This development will contribute to enhancing national energy security and defense capability, as well as ensuring the resilient operation of critical infrastructure during wartime and post-war periods.
A two-level system of mathematical models has been developed for forecasting the long-term development of the integrated power system and district heating systems. At the upper level of the system, an advanced mathematical model is applied to forecast the long-term development of the generating capacity structure of the integrated power system and heating systems. This model ensures the balanced coverage of electricity and heat demand utilizing combined heat and power (CHP) technologies and Power-to-Heat options. At the lower level, an advanced model for optimizing the capacity dispatch of power systems is implemented, incorporating the use of energy storage systems and Power-to-Heat technologies. This approach ensures their balancing reliability and the utilization of surplus generation from renewable energy sources, while jointly meeting the demand for electricity and heat for each year of the forecast period.
The “GreenPowerAtlas” software and information complex has been developed for the automated collection and processing of satellite meteorological data (wind speed, insolation, cloud cover, precipitation, temperature, etc.) utilizing NASA’s POWER core datasets and an adaptive interface. This development enabled the advancement of a methodology for rapid spatio-temporal evaluation of the generation potential of wind and solar power plants to support the design of distributed generation and enhance power grid resilience under critical load conditions.
A method has been developed for the coordinated integration of advanced mathematical models covering the overall energy balance, optimal capacity dispatch of power units within the integrated power system, and the transformation of the coal industry. This method enabled the construction of situational energy balances under conditions of significant destruction in the energy sector and structural changes in the economy. Furthermore, energy supply pathways for the country up to 2030 have been formulated, which envisage optimizing the structure of coal-mining enterprises, determining the required sources and volumes of coal imports, restoring thermal power plants to cover the critically necessary loads of the integrated power system, and gradually replacing coal-fired power units with highly flexible gas-fired capacities and energy storage systems.
A techno-economic analysis of options for configuring secondary automatic generation control (AGC) systems has been conducted. The analysis demonstrated that utilizing energy storage systems as a regulator enables the development of a system compliant with ENTSO-E requirements. Furthermore, owing to the high responsiveness of energy storage systems, this approach reduces the time required to compensate for imbalances within the power system, ensures the efficient use of regulator capacity, and enhances both the quality of frequency regulation and the overall operational reliability of the power grid.
A method has been advanced for evaluating the angular distributions of pollutants in the vicinity of energy facilities. This method is based on a combination of the inverse cumulative distribution function method for generating random angles with a given distribution and the method of trigonometric moments to obtain empirical distributions from sample data of random angles. This approach enabled the estimation of the probability density of pollutant concentration in polar coordinates based on sensor data, and allowed for the proposal of a monitoring system structure founded on a hybrid architecture utilizing artificial intelligence, aligned with leading global benchmarks.
An ultrasonic non-destructive testing method based on the magnetostrictive effect has been developed. The method involves exciting a hemispherical surface wave and scanning the inspected surface with a point receiver—a small-aperture magnetostrictive sensor that converts the acoustic signal into an electrical one. The parameters of this electrical signal are then used to determine the acoustic pressure distribution for detecting defects, as well as identifying their type and location. This method requires no special surface preparation of the tested objects or the use of immersion fluids to ensure acoustic contact, and it enables the inspection of surfaces with significant radii of curvature. It can be applied for the inspection of gas turbine engine rotor blades, aircraft blade spars, riveted joints, and thin-walled elements of load-bearing structures.
Most Significant Results of Fundamental and Applied Research of the Institute of General Energy of the NAS of Ukraine:
2024
For the first time, a method for utilizing wind and solar power plant energy has been proposed, which consists of using the self-generated energy of these power plants to stabilize frequency and power within the grid without involving external generation sources. This method employs energy storage systems to accumulate electricity in a specified proportion, ensuring the operation of wind and solar power plants in a self-sufficiency mode. This approach simultaneously addresses several issues of national importance: enabling full payment for electricity generated by these plants, transitioning the Ukrainian energy market from a state of hidden bankruptcy to profitability, and reducing frequency and power stabilization costs. The implementation of the proposed method enables the Ukrainian energy market to avoid losses of up to 16 billion USD annually, frees up more than 30 million tons of coal products originally allocated for backup thermal power plants, and reduces greenhouse gas emissions. Collectively, this will represent a significant contribution to the energy, economic, and environmental security of the country.
For the first time in Ukraine, a system of mathematical models has been created for the study of local power systems based on low-carbon distributed generation facilities. This system utilizes the principles of optimal facility dispatch when configuring and loading energy system assets. It enables the determination of the wind and solar capacity required to meet the electricity demand of a local power system while maintaining balancing reliability. Furthermore, it allows for an economic feasibility assessment of deploying distributed generation sources within local energy hubs during both synchronous and isolated operational modes.
For the first time, a country-level energy supply model has been developed, distinguished by its detailed and coordinated representation of technological processes within the electricity and coal sectors, taking into account the capacity utilization levels of the Integrated Power System (IPS) of Ukraine. The model is designed to calculate national energy balances for the short-term perspective under critical conditions, such as wartime, and enables forecasting directions for the coordinated transformation of energy sectors—specifically, the closure of unprofitable coal enterprises while ensuring the economy’s demand for electricity and coal products is met.
For the first time, the use of the discrete Hilbert transform has been substantiated as a foundation for implementing software-based measurement complexes for signal processing, thereby increasing the information capacity of monitoring systems in the energy sector. Utilizing this transform for the identification and monitoring of power quality indicators in general-purpose grids enables the determination of new deterministic and statistical characteristics. These characteristics are used to form databases that describe the condition of power equipment, power quality parameters, and the dynamics of their changes.
For the first time in Ukraine, pathways for the decarbonization of the power sector and energy-intensive industries—specifically iron and steel, ammonia, and cement production—have been proposed in alignment with domestic environmental policies and the country’s international commitments. These pathways account for the technical condition and existing installed capacities of industry and power sectors, electricity shortages, and post-war reconstruction prospects. This enables an assessment of achievable greenhouse gas emission reductions, the investments required to implement decarbonization measures and technologies, the carbon intensity of electricity and energy-intensive industrial products, as well as shifts in demand for fuel, energy resources, and raw materials.
For the first time, an optimization model has been developed to determine the installed capacity of renewable energy power plants and energy storage systems to supply electricity to consumers in decentralized grids, based on the use of historical data regarding electricity generation and consumption volumes. The objective function of the model is to minimize the levelized cost of electricity (LCOE), accounting for both production and storage costs. This enables minimizing the cost of the technological structures of polygeneration power supply systems and enhancing the utilization efficiency of energy equipment.
2023
At the Institute of General Energy of the NAS of Ukraine, pathways have been proposed for the first time to improve the operational efficiency of the Integrated Power System (IPS) based on a new structure of an ultra-large electro-thermal system through the electrification of heat supply utilizing energy from autonomous renewable sources. This approach enables addressing the issue of frequency stabilization within the Integrated Power System and guaranteeing the financial stability of the Ukrainian energy market’s operation.
The theory of systems research in the energy sector has been advanced; specifically, a new concept of the research process has been proposed for the first time: object – energy – information/signal – model – measure – method/algorithm – software – result. Unlike existing approaches, this concept enables a holistic complex of theoretical, simulation, and experimental studies on the functioning of energy facilities across three key areas: the technical system, which includes subsystems for measurement, control, diagnostics, monitoring, and state identification; products for energy markets; and the ecological state of the environment.
For the first time in Ukraine, a mathematical model for the restructuring of the coal industry has been developed based on multi-factor efficiency criteria for the operation of coal-mining enterprises. Unlike existing models, it simultaneously accounts for mine viability indicators, national demand for specific grades of coal products, and the constraints of low-carbon economic development scenarios. The mathematical model has been integrated into a system of models for the mutually coordinated transformation of fuel and energy complex sectors, which enabled the study of coal industry restructuring scenarios during the economy’s transition to low-carbon development.
The methodology for investigating building airtightness and indoor microclimate has been advanced. Specifically, the following have been enhanced: the algorithm for calculating building heat losses, taking into account infiltration heat losses of multi-layer wall structures; the heat transfer coefficients for internal and external surfaces, refined based on changes in the hydrodynamic and thermal characteristics of the air environment; and the method for monitoring thermal resistance using a CFD model of a building envelope segment. This approach enabled a reduction in the impact of instrumental factors on the research process, accounting for conductive and convective-radiative heat transfer.
2022
The theoretical foundations of object-oriented identification of phenomena, processes, and assets have been advanced at the Institute of General Energy of the NAS of Ukraine, based on investigations into the information resource—specifically, the characteristics of noise fields generated by energy facilities. For the first time in the world, constructive models of noise signals from energy facilities have been proposed, which account for historical and current information about the state of the asset and reflect its lifecycle. The application of these constructive noise signal models enables the analysis of the energy facility’s current condition, including the monitoring of atmospheric emissions, and the utilization of this information to forecast its future operation. This aligns with top global benchmarks and will be deployed in the energy sector as well as within the monitoring and control processes of technologically hazardous facilities.
For the first time in the world, the feasibility of co-operating wind and solar power plants with backup conventional power plants to cover the electrical load profiles of the power system has been theoretically substantiated and experimentally proven, which will enhance their energy-economic performance and the profitability of the Ukrainian energy market. Utilizing digital simulation, it was established that without the application of the proposed approach, the lost profits of Ukraine’s energy market in 2021 amounted to approximately 3 billion USD. The expected additional profits of the Ukrainian energy market at the 2030 horizon are estimated to reach around 6 billion USD.
For the first time, a new method has been developed for diagnosing components of complex energy facilities using deep learning algorithms for artificial neural networks. This paves the way for creating an efficient, data-driven diagnostics system for power equipment capable of processing and retaining events that occurred thousands of discrete time steps ago, which in turn improves the accuracy of reliability forecasting and residual life assessment for equipment. The practical value of the obtained results lies in the development of an operational algorithm for a computerized system to monitor the fuel combustion process with stepped correction of the air-fuel mixture formation based on feedback signals from an oxygen sensor, making it possible to maintain the excess air coefficient in the flue gases within the required range and achieve a reduction in harmful emissions. A structure for the fuel combustion control and monitoring system has been proposed, based on the application of a wideband oxygen sensor and a variable-frequency drive for the forced-draft fan, which ensures efficient fuel combustion in the boiler unit by maintaining a stoichiometric air-fuel mixture while reducing the generation of harmful emissions, and is recommended for implementation in the modernization of boiler units.
For the first time in Ukraine, a mathematical programming model for the dispatch of electrical and thermal energy generating capacities has been proposed. This model simultaneously ensures the balance between production and consumption for both electricity and heat according to daily demand profiles throughout the year. It also optimizes the operation of electric heat generators that consume electricity based on the electrical load profile and supply thermal energy to meet the needs of consumers connected to the district heating system. This enables the flattening of electrical load profiles and prevents temporary shutdowns of thermal power plants during nighttime hours, significantly improving their operational conditions. The results have been implemented at NPC Ukrenergo under commercial contract No. 1916 dated September 28, 2022.
For the first time in Ukraine, a software and information tool for forecasting the national energy balance has been created, which is resilient to increasing constraints on the completeness of data availability. The tool integrates the capabilities of statistical and technological approaches to determine the coefficients of the Leontief input-output matrix, which will enable the determination of optimal energy supply volumes for energy subsystems, facilities, and individual production processes from various supply sources, as well as the monitoring of fuel and energy resource utilization. The developed software and information tool will be utilized in formulating the “Annual Forecast Fuel and Energy Balance,” which is prepared by the Ministry of Economy of Ukraine.
For the first time in Ukraine, a new methodological approach has been developed to determine the forecast volumes for the regional deployment of heat pump stations within district heating systems, which was utilized to identify the composition and assess the potential of low-potential heat sources. Recommendations regarding the directions and forecast volumes for implementing heat pump installations in Ukraine’s regional heating systems have been submitted to the State Agency on Energy Efficiency and Energy Saving of Ukraine. The proposed methodological approach will enable each region to determine the economically viable energy potential for deploying heat pump stations during the post-war reconstruction period of Ukraine.
A model for the monitoring and identification of energy facilities has been proposed, in which energy consumers are represented as a stochastic spatio-temporal energy consumption environment, and the intensities of air pollution information parameters in space and time are modeled as an $n$-dimensional random field. A hierarchical algorithm for monitoring air pollution caused by energy facilities has been generalized, defining the hierarchical levels of information generated by information-analytical centers and the access to this data for various user types. The algorithm incorporates a feedback loop from decision-making centers that influence the operation of the controlled facilities and regulate the amount of pollutants discharged into the air. This aligns with global best practices and will be utilized in the process of monitoring energy facilities.
For the first time in the world, based on fuzzy set theory, a multi-level model has been developed for the circulation-consistent, service-dominant transformation of a hybrid energy system’s structure. A system of corresponding equations has been formulated, and an organizational mechanism has been proposed for the interaction of energy service market participants with energy and fuel markets. The utilization of this multi-level model will enable the determination of the structure and volumes of optimal energy resources during the energy system transformation process, as well as the pathways for securing cross-border assistance. This aligns with global standards and will be utilized in the transformation of the fuel and energy complex during the country’s post-war reconstruction.
2021
For the first time within input-output theory, a price model and a price index model have been developed and comprehensively investigated. Unlike the Leontief price model and other well-known price models, these are built on fundamentally different principles; specifically, they are formulated based on the balance of outputs rather than the balance of inputs within the framework of Input-Output (IO) mathematical tools. As a result, the proposed new IO price models are free from methodological errors, which—under realistic baseline data for conventional IO price models—can reach tens of percent or even more.
Mathematical models for investigating frequency and power control processes in interconnected power systems (IPS) that include high-capacity wind (WPP) and solar (SPP) power plants have been developed and advanced by introducing dependencies that describe the operation of various types of fast-acting regulating generators, particularly battery energy storage systems (BESS). In contrast to existing models, new frequency control laws for power systems with WPPs and SPPs have been developed and utilized within the mathematical model. It was established that combining two components in the control law—namely, an adaptive and a proportional-integral-derivative (PID) component—yields qualitatively better results in terms of ensuring frequency accuracy and control system stability. The optimal ratio between these components has been identified, ensuring the maximum regulating effect. Additionally, an auxiliary (interval) adaptive control law was developed, which, when combined with the other components, enables a 20% reduction in the required capacity of regulating BESS. It has been experimentally proven that utilizing BESS and hydropower plants (HPP) to stabilize the operating regimes of the IPS with significant shares of WPP and SPP capacities ensures a stable frequency in the base-load zone of the electrical load profile. This frequency not only complies with the standard for the IPS of Ukraine (50 ± 0.2 Hz) but even exceeds the requirements of the European Union’s IPS (ENTSO-E, 50 ± 0.02 Hz). Furthermore, according to the conducted research, the integrated complexes of WPP, SPP, and BESS, together with HPPs, ensure the capability for frequency- and power-stable operation of the IPS not only in the base-load zone but even in the shoulder (semi-peak) and peak zones of the electrical load profile. This significantly enhances the competitiveness of the aforementioned complexes.
An important study has been conducted on the impact of the green tariff law on the functioning of the interconnected power system (IPS) and the economy of Ukraine as a whole. It is shown that the preferences granted under this law to the owners of wind (WPP) and solar (SPP) power plants are higher than any ever provided in the European Union. Performed calculations demonstrate that the costs incurred by electricity consumers for energy generation by wind and solar power plants with a total capacity of around 12 GW over a single year will be an order of magnitude higher than the costs for an equivalent volume of energy that could be supplied by conventional generation. At the same time, the difference in costs exceeds 3 billion USD, which constitutes financial losses for consumers. The electricity market of Ukraine, being the sole buyer of electricity from WPP and SPP owners, will not be able to sustain such losses. Even now, with the total installed capacity of WPPs and SPPs at around 8 GW, the Ukrainian energy market cannot independently settle accounts for the electricity produced by these plants. NPC Ukrenergo has issued construction permits for WPPs and SPPs totaling approximately 18 GW. Therefore, their installed capacity of 12 GW will be reached within the next 1–2 years, at which point the electricity market will face bankruptcy, making the threat of default a reality for the economy of Ukraine. To prevent this scenario, amendments to the green tariff law must be urgently adopted, and the first step should be the abolition of its archaic and binding “take-or-pay” principle.
For the first time, a mixed-integer mathematical programming model has been developed to determine the structure and expansion volumes of conventional and renewable energy while complying with international environmental agreements and security constraints. In terms of functionality, the model aligns with global best practices, some of which are currently utilized by ENTSO-E transmission system operators. Unlike its counterparts, this model incorporates a more detailed representation of Ukraine’s generating capacity structure, their techno-economic and physical-technical performance indicators, and the well-established operational regimes characteristic of power plants within the interconnected power system (IPS) of Ukraine. The versatility of the algorithms implemented in the model allows for its application across a wide range of studies. These include the short-term optimization of power system generation dispatch, the formulation of Ukraine’s electricity balances for the upcoming year or the medium term, and its integration into the development of strategic documents, such as the Energy Strategy of Ukraine until 2050. Utilizing this model, the structure of the generating capacities of the IPS of Ukraine up to 2040 has been formulated, ensuring the continued operation of existing nuclear power units alongside the integration of approximately 18 GW of installed wind and solar capacity, while strictly adhering to the principles of power system resource adequacy.
For the first time, a mathematical model has been developed to optimize the supply of coal products to the country’s economy, which accounts for coal products not only for the needs of the power sector but also for other consumers categorized by types of economic activity and the households. Unlike conventional models, this model integrates a detailed representation of the techno-economic performance indicators of mining and coal preparation plant equipment with algorithms for balancing the flows of all types of coal products. This enables the forecasting of the final coal product structure while ensuring the required quality indicators along the “mine – coal preparation plant – consumer” technological chain. Utilizing the software implementation of the model, a forecast structure of coal products for the electric power sector and an overall balance of coal products in the economy of Ukraine have been developed according to coal industry development scenarios for the period up to 2040. According to these scenarios, the maximum coal production under the optimistic scenario—61 million tons—will be reached in 2035, while under the baseline and pessimistic scenarios, the maximums of 46 million tons and 41 million tons, respectively, will be achieved in 2030.
An advanced methodology has been developed for determining the total energy intensity of products in multi-product manufacturing systems. Unlike the existing methodology, it incorporates several types of energy intensity at different hierarchical levels: direct energy intensity — at the level of a technological unit or shop; process energy intensity — at the level of the technological production chain within a shop or a group of shops; total plant energy intensity, which includes, in addition to process energy intensity, the energy intensity of fixed assets, labor inputs, and intra-plant transportation; and total product energy intensity, which adds the energy intensity of raw material extraction and transportation to the enterprise to the total plant energy intensity. The methodology for determining direct energy intensity has been enhanced by supplementing the algorithms for calculating the energy intensity of thermal and secondary excess-pressure energy resources, and by introducing a allocation coefficient for shared energy consumption in multi-product manufacturing. A new algorithm has been developed to determine the total energy intensity of labor inputs, which, unlike its predecessor, accounts for population income categories; additionally, the algorithm for the total energy intensity of fixed assets has been improved. A draft of amendments and additions to DSTU 3682-98 “Energy Saving. Methodology for Determining the Total Energy Intensity of Products, Works, and Services” has been prepared. Utilizing the advanced methodology, indicators for the total energy intensity of products in ferrous metallurgy, coke chemistry, co-generation of heat and electricity at CHPs, and primary petroleum refining have been determined for the period up to 2040. The results of the work were reviewed at a meeting of Technical Committee TC 48 “Energy Saving” and were recommended for inclusion in the National Standardization Program for 2022 and submission to the SE “UkrNDNC”.
To investigate the conditions for fulfilling the obligations undertaken by Ukraine upon joining the Global Methane Pledge (to reduce methane emissions by 30% by 2030 compared to the 2020 level), forecasts for methane emissions from the sectors of the fuel and energy complex up to 2040 have been developed for the first time in Ukraine. It was determined that in the coal industry, achieving the specified reduction in methane emissions is possible only if the capture and utilization of coal mine methane is increased from the current 10.3% to 21–52% across various industry development scenarios. It was also established that in the gas industry, achieving the target methane emission reduction by 2030 requires not only the implementation of mitigation measures but also the development of national methodologies for assessing methane emissions and the application of country-specific emission factors when formulating the National Inventory of Anthropogenic Emissions by Sources and Removals by Sinks of Greenhouse Gases.
2020
Models for investigating frequency and power control processes in interconnected power systems that include wind and solar power plants have been advanced by incorporating newly developed adaptive frequency and power control laws. It was determined that combining two components in the control law—namely, an adaptive and a proportional-integral-derivative (PID) component—yields qualitatively better results in terms of ensuring frequency accuracy and control system stability. The optimal ratio between these components has been identified, ensuring the maximum regulating effect. The resulting new control laws were integrated into the developed “Chastota-M” software and information complex, enabling studies to determine the conditions and deployment volumes of wind and solar power plants within the interconnected power system, as well as the required number of regulators to ensure stable power system operation. It was established that to meet European frequency stability requirements in the interconnected power system when utilizing fast-acting regulators based on battery energy storage systems, their capacity must be no less than the peak-to-peak variation of the combined wind and solar power output. Insufficient regulator capacity leads to a degradation in frequency control quality, which drops rapidly as the regulator capacity decreases relative to the fluctuations in wind power output.
A new mathematical model has been developed for the co-operation of a solar photovoltaic power plant and a battery energy storage system to support the stability of electricity supply under variable weather conditions (intermittent cloud cover). Such a hybrid system (a solar power plant and an energy storage system, specifically a battery) enables an operational regime that shifts a portion of the “surplus” electricity generated by the solar power plant during hours of peak insolation—which could potentially threaten the resource adequacy of the interconnected power system (IPS) of Ukraine—to the evening peak load period of the IPS. Model calculations demonstrated that for a 10 MW solar power plant, utilizing a storage system with a capacity of 3.0 MWh allows for shifting approximately 4.5% of the “surplus” electricity.
The mathematical model for assessing the levelized cost of heat over its life cycle has been advanced by incorporating detailed accounting for electricity costs—as the primary energy source for heat production—and grid connection costs, both of which are mandatory for electric boilers and heat pump installations. Calculations demonstrated that for electric boilers with a capacity of 0.54–50 MW(e), competitiveness in the existing heat market within Ukraine’s district heating systems is ensured, provided that their procurement electricity tariff is set at a level below 50% of the average tariff in the interconnected power system (IPS) of Ukraine.
A new mathematical model has been developed to optimize the production capacities of the coal industry in accordance with the steam coal requirements of thermal power plants within the interconnected power system (IPS) of Ukraine. Unlike existing models, this model incorporates a detailed representation of the techno-economic performance indicators of mining and coal preparation plant equipment, along with corresponding algorithms for balancing fuel flows. This enables the forecasting of the final coal product structure while ensuring its quality indicators across all stages of the “mine – preparation plant – thermal power plant” production chain, as well as reducing atmospheric emissions of harmful substances from coal combustion at thermal power plants.
The economic-mathematical model for optimizing the development of Ukraine’s coal mining sector, designed to determine re-equipment options for the longwalls of coal mining enterprises, has been advanced. For the first time, this model accounts not only for the potential of production concentration on a selected subset of longwalls and the competitiveness of coal products, but also for the volumes of coal mine methane emissions, the required production capacity of equipment for its utilization, the capital expenditure for such equipment, and the quality of the mined coal. The software implementation of the model enabled the development of coal industry expansion scenarios and forecasts for coal mine methane emission reductions for the period up to 2050, as well as the identification of efficient technologies and the optimal configuration of longwall mining complexes for mine modernization, ensuring the achievement of maximum production volumes alongside environmental safety.
The mixed-integer mathematical programming model for “Generation Dispatch under Electrical Load Profile Coverage within the Interconnected Power System of Ukraine” has been further advanced. For the first time, mathematical equations ensuring compliance with the required volumes of secondary reserves within the Interconnected Power System of Ukraine have been developed and integrated into the model, specifically in accordance with the Transmission System Code requirements. The application of the proposed equations ensures the availability of secondary reserves in the required volumes for each hour of the daily electrical load profile, which is critical given the participation of existing non-maneuverable high-capacity nuclear power plants in covering electrical load profiles. The proposed enhancements allow for the separate accounting of the required levels of both upward and downward secondary reserves, which are specified exogenously for each power unit and/or hydropower unit, taking into account their physical-technical indicators, particularly the ramp rates.