Operation Of Power Plants Research Articles

Life cycle greenhouse gas emissions assessment: converting an early retirement coal-fired power plant to a biomass power plant

Decommissioning aging coal-fired power plants (CFPPs) represents an effective strategy for reducing greenhouse gas (GHG) emissions, accelerating energy mix diversification, and achieving nationally determined contributions and net-zero emissions targets. However, dismantling the CFPP and building a renewable energy-based power plant with a capacity equal to a dismantled CFPP could burden state finances. Therefore, converting coal to 100% biomass fuel in the aging CFPP is one of the proposals that needs to be studied. This study conducted an environmental assessment concerning the Life Cycle Greenhouse Gas (LC GHG) emissions, encompassing raw material extraction and power plant operation. Five scenarios were analyzed. Two scenarios related to using sawdust and agroforestry residue for biomass fuel in the aging CFPP. The other three scenarios used biomass fuel from Calliandra wood harvested from tropical forests, production forests, and marginal land, which produced GHG emissions from Land Use Change (LUC). This study demonstrates that sawdust and agroforestry residue can reduce global warming impacts compared to coal. The LUC in higher carbon stock land will increase global warming impacts, while the LUC in lower carbon stock land will reduce global warming impacts. A decrease in the aging CFPP efficiency, when coal is converted to 100% biomass, will cause an increase in global warming impacts.

Low-level ionizing radiation-induced DNA responses in the Asian green mussel Perna viridis

Cesium-137 (Cs-137) is a radioactive isotope present in marine environments due to the operation of nuclear power plants and weapons testing. Radiocesium poses a potential risk to marine life due to its long half-life and bioaccumulation. This study evaluated the genotoxicity of low doses of Cs-137 in the Asian green mussel Perna viridis, a sentinel species for marine pollution monitoring, by performing the comet assay and micronucleus test on hemolymph samples. Genotoxicity was assessed after exposing mussels to Cs-137 at dose rates of 0, 5, 10, and 15 μGy/h for 48 h. Cs-137's organ-specific distribution was also determined using HPGe gamma spectrometry. Even at low radiation doses, Cs-137 was found to exert genotoxic effects. Significant increases in DNA strand breaks (%Tail DNA) and micronucleus formation (MNF) were observed at all tested dose rates compared with the levels in controls, with dose-dependent responses. Cs-137 predominantly accumulated in the soft tissues, specifically the gills and digestive gland. The findings support the recommended safety level of 10 μGy/h for aquatic organisms, suggesting its appropriateness as a fundamental criterion for developing the national marine water quality standard for Cs-137 in Thailand.

Enhancing photovoltaic power prediction using a CNN-LSTM-attention hybrid model with Bayesian hyperparameter optimization

Improving the accuracy of solar power forecasting is crucial to ensure grid stability, optimize solar power plant operations, and enhance grid dispatch efficiency. Although hybrid neural network models can effectively address the complexities of environmental data and power prediction uncertainties, challenges such as labor-intensive parameter adjustments and complex optimization processes persist. Thus, this study proposed a novel approach for solar power prediction using a hybrid model (CNN-LSTM-attention) that combines a convolutional neural network (CNN), long short- term memory (LSTM), and attention mechanisms. The model incorporates Bayesian optimization to refine the parameters and enhance the prediction accuracy. To prepare high-quality training data, the solar power data were first preprocessed, including feature selection, data cleaning, imputation, and smoothing. The processed data were then used to train a hybrid model based on the CNN-LSTM-attention architecture, followed by hyperparameter optimization employing Bayesian methods. The experimental results indicated that within acceptable model training times, the CNN-LSTM-attention model outperformed the LSTM, GRU, CNN-LSTM, CNN-LSTM with autoencoders, and parallel CNN-LSTM attention models. Furthermore, following Bayesian optimization, the optimized model demonstrated significantly reduced prediction errors during periods of data volatility compared to the original model, as evidenced by MRE evaluations. This highlights the clear advantage of the optimized model in forecasting fluctuating data.

Research on the collaborative operation strategy of shared energy storage and virtual power plant based on double layer optimization

Large-scale access to distributed energy resources leads to new energy consumption problems and safe operation risks in the power system. Virtual power plants and shared energy storage are effective ways to promote the flexible consumption of distributed energy resources and improve the reliability and economy of power system operation. Based on the concept of sharing economy and considering the complementary characteristics of source and load resources between different virtual power plants, this paper focuses on the optimisation of shared energy storage and multi-virtual power plant operation. Firstly, distributed wind power, distributed photovoltaic and flexible load resources are aggregated into virtual power plants to analyze the cooperative operation mode of shared energy storage and multi-virtual power plant systems. Secondly, a two-layer decision model for shared energy storage configuration and multi-VPP system operation optimisation is constructed, with the upper model solving the optimal energy storage configuration scheme by maximising the revenue of the shared energy storage operator, and the lower model optimising the multi-VPP system operation strategy by minimising the total operation cost, the maximum amount of new energy consumed, and the minimum amount of carbon emission as the multi-objective optimisation strategy. Finally, a simulation analysis is carried out, and the results show that compared with the independent operation mode of each virtual power plant, the model proposed in this paper increases the annual profit of the shared energy storage operator by 7180¥, reduces the operating cost of the VPP system by 7.08 %, improves the rate of renewable energy consumption by 0.82 %, and reduces the annual carbon emission by 54.91 t, which realizes the mutual benefits of the virtual power plant and the shared energy storage.

Perceived effects of coal-fired power plant operations on the living standards of the selected municipality in Quezon province

Perceived effects of coal-fired power plant operations on the living standards of the selected municipality in Quezon province

Management Method to Handle Frequent Start-up & Shutdown Operation in Power Plant Using Steam Turbine Digital Twin Technology

Management Method to Handle Frequent Start-up & Shutdown Operation in Power Plant Using Steam Turbine Digital Twin Technology

Assessment of Power Equipment Operational Safety in the Sustainable Management of Residual Lifespan

Introduction. Ensuring the safe operation of energy facilities is a critical issue at all life cycle stages. It is associated with the adoption of management decisions when rescheduling and assessing the remaining resources, which are made based on a comprehensive assessment of the technical condition of the equipment, taking into account the economic efficiency and environmental requirements for further operation, which is the basis for technical and economic assessments. Aim and tasks. This study aims to develop a technical and economic assessment of the safe operation of power equipment to ensure sustainable management of the remaining service lifespan. Results. An algorithm for assessing pipeline system elements by the coolant environment is proposed, which allows for the pipeline load and changes in erosion and corrosion caused by coolant movement. It was proposed that the equipment be systematised by safety class and coolant. When conducting a technical and economic assessment, these parameters and the costs of extending the service life and upgrading the existing equipment were considered in the standard calculations of a certain type of equipment. For this purpose, mathematical models for calculating the residual life for each type, obtained and confirmed based on empirical studies, are proposed. Research findings into ensuring the reliability and safety of operation with various heat carriers have shown that it is necessary to consider low-cycle and high-cycle loads and erosion processes. It was found that the erosive wear rate is 0.3-0.4 mm/year for bending sections of the main circulation pipeline, where maximum loads occur relative to low-cycle and vibration loads, and the stress is 212.5 MPa when assessing the residual life of 7 years. Conclusions. The cost-effectiveness of reassigning the service life is reasonable, as it does not require additional investment in upgrading or replacing equipment subject to annual technical diagnostics. The systematisation of pipelines, improved codifiers, lifespan assessment models, and algorithms for evaluating the remaining life under various loadings enhance the regulatory framework for safe nuclear power plant operations and support technical and economic evaluations for extending their lifespan.

DEVELOPMENT TRENDS OF SOLAR POWER ENGINEERING BASED ON THE MATERIALS OF THE SCIENTIFIC AND PRACTICAL CONFERENCE «RENEWABLE ENERGY AND ENERGY EFFICIENCY IN THE 21

The main results of the reports at the "Solar Energy" section were considered and summarized, in particular, one of the areas of solar energy engineering - solar power generation. Specialists from Ukraine and the Republic of Uzbekistan took part in the work of the section in this field. A total of 32 reports were presented, focusing on topics such as the implementation of distributed generation facilities based on photovoltaic systems, improving the energy efficiency of solar power plants, etc. The reports demonstrated the primary trends to highlight the issues of building and operation of energy-efficient solar power plants in today's realities.

EVALUATION OF TECHNOLOGICAL PLASTICITY OF HIGH BORON CORROSION-RESISTANT STEEL DURING HOT DEFORMATION OF PIPES USED FOR SPENT NUCLEAR FUEL STORAGE

Statement of the problem. The sustainable development of the global nuclear power industry in the future depends on how effectively the problems of radiation safety and nuclear proliferation are addressed. Such problems occur, among other things, at the final stage of the nuclear fuel cycle – spent fuel management. This task is currently on the agenda of both the international community and national governments of countries that develop or intend to develop nuclear energy [1−3]. Today, in connection with ensuring the safety of nuclear energy, boron-containing steels are widely used in the world practice as a material for biological protection and for the manufacture of special equipment parts. This is due to the fact that the B10 isotope in steels provides neutron capture [4]. Hexagonal pipes made of high-boron steel were needed to shield the support cover of the compacted spent fuel storage facility at nuclear power plants. Corrosion-resistant steels alloyed with boron are widely used in the nuclear power industry due to their special nuclear properties. During the operation of nuclear power plants, fuel assemblies that have served their useful life must be stored in special storage facilities using containers – hexagonal tubes made of 04Сr14Ti3B2V steel. To reduce costs during in the construction and operation of NPPs, part of the spent nuclear fuel management should be performed at Ukrainian enterprises. This will provide a significant import substitution effect. To manufacture hexagonal tubes from 04Сr14Ti3B2V steel according to the ingot-hot deformation-profiling-heat treatment scheme, it is necessary to develop the parameters of hot deformation and subsequent technological operations. The use of these pipes in compacted spent fuel storage facilities of NPPs will allow to increase the storage capacity by 2 times, which will give a significant national economic effect Material and methods of research. Material used for the study was steel 04Сr14Ti3B2V (CS-82), smelted using two variants (vacuum-induction – “VI” and vacuum-induction followed by vacuum-arc remelting – (“VD”). Steel grade 04Сr14Ti3B2V belongs to high-alloy, corrosion-resistant ferritic steels with a high boron content of up to 2 %. The method of differential thermal analysis was used to study the phase transformation temperatures in the steel. X-ray diffraction and micro-X-ray spectral analysis were used to assess the phase state. The steel samples were tested for weldability After cooling, the welded samples were subjected to X-ray transmission [5]. Hot twisting tests and mechanical tests at high temperatures were also performed. The macro- and microstructure of the metal was studied. Results. The macro- and microstructure of steel was evaluated depending on the smelting method. The phase composition of the steel was studied. The study of the plastic properties of steel ChS-82 by means of penetration and hot twisting tests showed that the temperature range of maximum plasticity is in a wide range (from 1 025 to 1 150 0C) with a rather low resistance to deformation. During hot deformation in the temperature range of 1 175 0C and above, metal fracture was observed along the grain boundaries at the melting points of the Cr−Fe−B boride phase. The optimal temperature range for hot deformation of steel ChS-82 is 1 000−1 050 ⁰С. Scientific novelty. For corrosion-resistant high boron steel used for spent nuclear fuel storage, the temperature range of hot deformation was selected and the structural and phase composition was estimated, which will allow deforming the metal on the piercing mill and manufacturing pipes.

Thermal Power Plant Performance Analysis by Estimating Boiler Efficiency via Indirect Method: A Case Study

The performance of power plants is very critical since it is directly related with operating and electricity production costs. Among the other different type of power plants, coal-fired ones have advantages such as reliability and low cost fuel. In this paper, a coal (lignite) fired thermal power plant having capacity of 160 MW is taken into consideration and the impact of condenser pressure, moisture content of lignite, excess air coefficient, efficiency of turbine pressure and heater numbers on power plant thermal efficiency is investigated. It is aimed to determine performance losses of each equipment by means of the thermodynamics and economic analysis. In this scope, it is expected that the power plant operator will be able to evaluate the reduction potential of equipment performance losses and ensure more effective use of the power plants by correctly planning the maintenance and rehabilitation needs and times. In the calculations, the boiler efficiency was determined with EN 12952-15 standard (indirect method) since this method has higher accuracy in coal fired boilers. It is seen that the condenser pressure and excess air coefficient increments have not significant impact on power plant efficiency compared to moisture content of lignite, excess air coefficient, efficiency of turbine pressure and heater numbers. The significant effect is observed for fuel moisture content which rises from 22% to 47% and the power plant efficiency falls from 40% to 28%. The variation of the power plant thermal efficiency in case of failure of heaters is investigated and the power plant efficiency has decreased from 40.17% to 36.09% when the pre-heaters are no longer in to be in use because of any reason. In addition, revenue losses are estimated for each main equipment efficiency reduction for better use of power plant capacities and electricity lowering production costs.

A Surrogate Model Approach to Predict Operations and Maintenance Cost for Combined Cycle Power Plant

Abstract In the transition toward carbon neutrality by 2050, renewable energy sources are gaining prominence. The variability of renewable energy poses challenges for power grid stability. Gas turbine combined cycle (GTCC) power plants play a crucial role in grid stabilization, especially during peak loads. In GTCC power generation, operations and maintenance (O&M) cost is the next most important after fuel and initial investment cost, and it is necessary to predict O&M cost according to changes in the operating environment for efficient and stable operation of GTCC power plant. However, various uncertainties exist when estimating O&M costs because actual design information is limitedly disclosed due to maintenance contracts between operators and manufacturers, and it is difficult to obtain accurate variables according to the operation condition. In this paper, the correlation was analyzed considering the uncertainty of the factors affecting the O&M cost of the GTCC power plant through sensitivity analysis, and the main factors were defined. In addition, a surrogate model was proposed that can quickly calculate fixed and variable O&M cost according to changing operating scenarios such as shortening startup time, enhancing ramp rate, or lower minimum load. Through the case study, short-term and long-term O&M costs can be estimated in the operating environment of the GTCC power plant currently being operated. Additionally, the model facilitates cost projections for new hybrid GTCC facilities (combining gas turbines with energy storage systems), aiding long-term investment planning.

Harnessing geothermal energy in Hungary

This paper provides a summary of the current status of geothermal energy utilisation in Hungary, with a brief reference to geothermal potential. Approximately 1,000 thermal wells are in operation, producing from two principal aquifers: carbonate aquifers (predominantly Mesozoic) and Upper Miocene siliciclastic aquifers. The utilisation of geothermal energy in Hungary commenced with balneological exploitation, with documented evidence dating back to the Roman era. Of particular note is the city of Budapest, which has the distinction of being home to 16 thermal spas, a fact that has led to its designation as the spa capital of Europe. In the Hungarian portion of the Pannonian Superbasin, 26 municipalities have implemented geothermal district heating systems. Furthermore, geothermal energy plays a significant role in the agricultural sector, with approximately 300 thermal wells currently in operation. Nevertheless, the generation of geothermal electricity is still in its infancy, with only one operational geothermal power plant. However, based on the exploration permits submitted, there are significant prospects for further development. The same is true for ground source heat pumps, where there is considerable potential for growth, particularly in comparison to our neighbouring country's utilisation. Recent research directions are promising, ranging from the use of geothermal energy from abandoned hydrocarbon wells as deep borehole heat exchangers, to the potential for extracting critical materials from thermal water, to exploring the possibility of underground heat storage. The favourable geothermal conditions in Hungary offer the potential to achieve up to 15-20 times the current production of 6.5 PJ, assuming the application of existing technologies. This presents a significant opportunity for the transition to a more sustainable energy source, particularly in the context of heating.

The Impact of Retrofitting Natural Gas-Fired Power Plants on Carbon Footprint: Converting from Open-Cycle Gas Turbine to Combined-Cycle Gas Turbine

Since retrofitting existing natural gas-fired (NGF) power plants is an essential strategy for enhancing their efficiency and controlling greenhouse gas emissions, this paper compares the carbon footprint of natural gas-fired power generation from an NGF power plant in Brazil (BR-NGF) with and without retrofitting. The former scenario entails retrofitting the BR-NGF power plant with combined-cycle gas turbine (CCGT) technology. In contrast, the latter involves continuing the BR-NGF power plant operation with open-cycle gas turbine (OCGT) technology. Our analysis considers the BR-NGF power plant’s life cycle (construction, operation, and decommissioning) and the natural gas’ life cycle (natural gas extraction and processing, liquefaction, liquefied natural gas transportation, regasification, and combustion). Moreover, it is based on data from primary and secondary sources, mainly the Ecoinvent database and the ReCiPe 2016 method. For OCGT, the results showed that the BR-NGF power plant and the natural gas life cycles are responsible for 620.87 gCO2eq./kWh and 178.58 gCO2eq./kWh, respectively. For CCGT, these values are 450.04 gCO2eq./kWh and 129.30 gCO2eq./kWh. Our findings highlight the relevance of the natural gas’ life cycle, signaling additional opportunities for reducing the overall carbon footprint of natural gas-fired power generation.

The protection of nuclear installations in time of armed conflict – Old rules, new challenges

AbstractIn 2022, for the first time in some while, the public around the world was confronted with an armed conflict between states, which directly involved a nuclear facility, specifically a nuclear power plant in operation. Unfortunately, the situation following Russia's armed attack on Ukraine on 24 February 2022 and the acts of war around the Zaporizhzhya nuclear power plant once again draw attention to the need to protect nuclear facilities during armed conflicts. Therefore, this paper reviews the relevant rules of public international law and scrutinizes the norms that have been established through international legislation and soft law mechanisms to protect and guarantee the nuclear safety and security of nuclear installations.

Explainable, Deep Reinforcement Learning–Based Decision Making for Operations and Maintenance

This paper presents research that integrates condition monitoring and prognostics with decision making for nuclear power plant operations and maintenance aimed at reducing lifetime maintenance and repair costs. Additionally, a focal point of this research is to make the decisions explainable to operators, improving the trustworthiness of the decisions from what can be considered a black box model. In this work, we develop and evaluate an explainable, online asset management methodology to help reduce lifetime maintenance and repair costs. Using the latest advancements in condition monitoring, inventory management, deep reinforcement learning, and explainable artificial intelligence methods, we create a predictive maintenance methodology that can optimize the maintenance and spare part management of a repairable nuclear power plant system. To demonstrate these methods, preliminary studies were conducted on a representative maintenance system undergoing a stochastic degradation process that requires repairs or replacement to continue operation. Using deep reinforcement learning, we were able to reduce maintenance spending by approximately 50% compared to optimized, time-based maintenance strategies for the chosen system. A key component of our methodology is the integration of Shapley values to quantify the contribution of various factors to the decision-making process. This addition enhances the explainability and trustworthiness of our decisions, providing operators with transparent and understandable insights into the rationale behind maintenance strategies. The robustness and resiliency of our decision policy against observation noise were also thoroughly evaluated, demonstrating its effectiveness in uncertain operational environments.

The health, climate, and equity benefits of freight truck electrification in the United States

Abstract Long-haul freight shipment in the United States relies on diesel trucks and constitutes ∼3% of U.S. greenhouse gas emissions and a significant share of local air pollution. Here, we compare the climate and air pollution-related health damages from electric versus diesel long-haul truck fleets. We use truck commodity flows to estimate tailpipe emissions from diesel trucks and regional grid emissions intensities to estimate charging emissions from electric trucks under various grid scenarios. We use a reduced complexity air quality model combined with valuation of air pollution-related premature deaths (using two hazard ratios (HRs)) and quantify the distributional health impacts in different scenarios. We find that annual health and climate costs of the current diesel fleet are $195–$249/capita compared to $174–$205/capita for a new diesel fleet, and $156–$177/capita for an electric fleet, depending on the HR. We find that freight electrification could avoid $6.2–8.5 billion in health and climate damages annually when compared to a fleet of new diesel vehicles (with even higher benefits when compared to the current diesel fleet). However, the Midwest and parts of the Gulf Coast would experience an increase in health damages due to vehicles charging using electricity from coal power plants. If old coal power plants (operating in 1980 or earlier) are replaced with zero-emission generation, electrification of all U.S. freight would result in $32.3–39.2 billion in avoided damages annually and health benefits throughout the U.S. Electrifying transport of consumer manufacturing goods (including electronics, transport equipment, and precision instruments) and food, beverage, and tobacco products would provide the largest absolute health and climate benefits, whereas mixed freight and manufacturing goods would result in the largest benefits per tonne-km. We find small variations in health damages across race and income. These results will help policymakers prioritize electrification and charging investment strategies for the freight transportation sub-sector.

Seismicity zoning at Coso geothermal field and stress changes from fluid production and migration

The Coso geothermal field is a major geothermal power production site in the western United States. It has been observed that low-magnitude seismic events (M < 3.71) are unevenly distributed in three distinct zones, namely, nearfield (<3 km), midfield (3–6 km), and farfield (> 6 km) from the Coso geothermal plant. These zones exhibit distinct changes in earthquake location before and during geothermal production episodes that began in 1986. After 1986, the midfield region of the main flank experiences a significantly lower seismicity rate than the surrounding areas before production episodes. During 2014–2019, the farfield earthquakes cluster in the eastern and western parts of the greater Coso area, which is discernably different from how those pre-production earthquake events were distributed along the conjugate NW-SE and SW-NW trending structures across the main flank. Here, we analyze the stage of stress with finite-element-based poroelastic simulations to illustrate how the spatiotemporal evolution of the seismicity is associated with the pattern of stress perturbations caused by fluid migration amid the operations of geothermal power plants. Generally, ∼70% of co-production seismicity is found in zones of increased Coulomb stress between 2014 and 2019 at >99% confidence. Meanwhile, the midfield zone of seismic paucity overlaps with the zone of decreasing pore-fluid pressure. Overall, the results provide a physical explanation of how decadal geothermal operations at Coso have perturbed stress-field changes and contributed to the evolving characteristic seismic pattern, shedding insights into assessing the seismic hazard in other geothermal settings.

Research on Assessment Method for Cognitive Influence Factors of Nuclear Power Plant Operators Based on Fuzzy Analytic Hierarchy Process and Deep Learning of Electroencephalogram Signals

This study explores the factors influencing the cognitive processes of operators in digital nuclear power plants, with a focus on the correlation between these factors and electroencephalogram (EEG) features. Initially, based on expert consultations, seven factors were considered: stress, time, fatigue, procedural complexity, user interface experience, procedural clarity, and efficiency. From these, four were identified as the most crucial for each stage of the cognitive process, highlighting their significant roles in influencing cognitive performance and potentially correlating with distinct EEG characteristics. These were assessed using the fuzzy analytic hierarchy process (FAHP) to determine the weightings of influences across the cognitive stages of monitoring, decision making, and execution. Employing a simulated scenario of a steam generator tube rupture, subjective questionnaires were utilized to gauge participant perceptions of influencer impacts at each stage, calculating human factors fuzzy synthetic values. Concurrently, EEG signals were segmented by operational steps, extracting around 114 features across the time, frequency, and time-frequency domains, which were then dimensionally reduced to 17 principal components via adaptive principal components analysis (APCA). A correlation analysis was performed between the human factors fuzzy synthetic values and the APCA-reduced EEG features of participants. Subsequently, the EEG feature columns of the eight selected participants were used as inputs to construct a transformer-based self-attention network model to evaluate the participants’ human factors fuzzy comprehensive values. The findings confirm the transformer model’s efficacy in assessing these values, evidencing a significant correlation between the EEG features and human factors fuzzy synthetic values. Integrating FAHP with machine learning methodologies, this model proficiently estimated operators’ cognitive states during various cognitive processes, significantly enhancing human-machine interface design and the operational safety and efficiency at nuclear power plants.

Offshore Wind Power: Progress of the Edge Tool, Which Can Promote Sustainable Energy Development

Offshore wind is renewable, clean, and widely distributed. Therefore, the utilization of offshore wind power can potentially satisfy the increasing energy demand and circumvent the dependence on fossil energy. Thus, offshore wind power is an edge tool for achieving sustainable energy development because of its potential in large-scale energy supply and its important role in reducing environmental pollution as well as carbon emission brought by fossil energy. The worldwide development of offshore wind power has entered the era of large-scale research and commercial application. It displays a trend of rapid development, continuous technological breakthroughs, and high-speed market growth. This article systematically introduces the structural components and technical characteristics of offshore wind power. Moreover, the current developmental status of offshore wind power is summarized. By reviewing the current development and application status of offshore wind power technology worldwide, large wind turbines and fixed and floating offshore wind power technologies are analyzed. Additionally, the development of the offshore wind energy market is overviewed. The policy condition and key aspects such as the construction, operation, and maintenance of offshore wind power plants are also summarized. Finally, the prospective challenges and development trends of offshore wind power and its significance in achieving sustainable society development are proposed. We consider that the article can provide reference and inspiration for researchers and developers dedicated to offshore wind power.

Comprehensive assessment of the effectiveness of the hydrogen production and transportation system

Based on the energy development strategy of Russia until 2035, the article substantiates the prospect for the development of nuclear energy, according to which nuclear plants are planned to be forced to unload in the range of up to 50% of the rated power while participating in the regulation of daily unevenness of the electrical load. In addition, nuclear power plants will be involved in primary frequency regulation, which is also associated with the unloading mode of operation of nuclear power plants. All these circumstances force us to look for ways to provide nuclear power plants with base load. Along with pumped storage power plants, the article considers an alternative option in the form of using a hydrogen complex based on the electrolysis production of hydrogen, which satisfies the concept of its carbon-free production. The article presents the global dynamics of the introduction of electrolyzers, and in addition to the increase in the share of electrolysis hydrogen produced at nuclear power plants. The hydrogen complex in this case is a means of providing the nuclear power plant with a base load, which involves the consumption of unclaimed electricity at cost. This allows hydrogen to be produced at a competitive price compared to individual producers on the market. The resulting hydrogen is in great demand as a useful product in a number of industries. The article provides examples of hydrogen consumption in various areas of consumption depending on purity, taking into account the requirements of GOST. A number of consumer industries use hydrogen of a special degree of purity, i.e., more than 99.999% vol. In this regard, additional hydrogen purification on palladium membranes was taken into account. A comprehensive assessment of the efficiency of the hydrogen production system was carried out, taking into account its additional purification and delivery to the consumer in various ways, mastered and in demand in world practice. A comparison has been made of the methods of delivering hydrogen to the consumer in comparison with the production of hydrogen by electrolysis at the point of consumption. A comparison was made using the criterion of net present value for the option of third-party consumers who do not have their own hydrogen production.