The RNG k-ɛ model was used to numerically simulate the flow and heat transfer characteristics of supercritical CH₄-H₂ mixtures in horizontal pipe. The thermal physical properties of the CH₄-H₂ mixtures with hydrogen ratio of 0~30%, as well as the heat transfer process of the CH₄-H₂ mixtures with hydrogen ratio of 0~15% in the horizontal tube were analyzed. The influences of mass flow rate (150~250 kg/(m²·s)) and heat flux density (150~250 kW/m²) on flow and heat transfer of the mixed working fluid with hydrogen ratio of 10% were studied. The results show that when the hydrogen ratio increases from 0 to 30%, the pseudo-critical temperature of the mixed working fluid increases slightly from 190.4 K and then sharply decreases to 181.7 K, and the pseudo-critical pressure increases from 4.3 MPa to 12.3 MPa. With the increase of the hydrogen ratio (0~15%), the heat transfer between the fluid and the wall is strengthened. The increase of mass flow rate strengthens the heat transfer capacity of the mixed working fluid and weakens the heat transfer deterioration caused by buoyancy effect. The increase of heat flux strengthens the heat transfer degree of the wall under the mixed working medium, and weakens the heat transfer degree of the upper wall due to the advanced appearance of the gas-like film. Increasing the mass flow rate and heat flux density can enhance the heat transfer to varying degrees. The research can provide theoretical reference for mixed working medium heat exchangers in hydrogen-doped natural gas transmission and power circulation systems.

To construct a prediction model for carbon emission from coal-fired power plants and address the problem of general lack of real-time elemental analysis for coal entering the furnace of coal-fired units, according to the in-furnace coal quality information of a million kilowatt unit in 2023, the low calorific value, volatile matter, and sulfur content were used as the basis for coal quality classification, K-means++ algorithm was used for clustering analysis, and correlation analysis was used to screen the input parameters of the carbon emission prediction model. The BP neural network suffered Bayesian optimization was used to construct carbon emission prediction models for each cluster data after clustering, and the models were tested for working conditions such as load increase and decrease. The results show that, the accuracy of the coal quality clustering model in predicting carbon emissions increases significantly. Compared with the non clustered model, the optimal cases of average root mean square error and average relative error reduce by about 53.4% and 49.2%, respectively. Especially under variable load conditions, the predicted results are more in line with the actual values. This indicates that the proposed method can not only effectively predict the carbon emissions of coal-fired power plants, but also maintain high accuracy in the case of complex and variable coal quality.

The fuel adaptability of a certain type of gas turbine combustion chamber is systematically investigated in response to the characteristics of blast furnace gas composition and its significant fluctuations in its calorific value. By coupling the detailed chemical reaction mechanism with numerical simulation methods, the comprehensive performance characteristics of the gas turbine combustion chamber under different calorific values and composition conditions were obtained, with a focus on analyzing the distribution of temperature and concentration fields and their influencing mechanisms. The results show that, under the same initial conditions and fuel calorific value, as the volume fraction ratio of H₂ to CO in the gas increases, the average temperature at the combustion chamber outlet decreases from 1 769.35 K to 1 710.11 K, the temperature distribution coefficient decreases from 0.044 to 0.016, the NO_x emission concentration at the outlet decreases from 7.56×10^–6 mol/m³ to 1.49×10^–6 mol/m³, and the CO emission concentration decreases from 993.98×10^–6 mol/m³ to 421.95×10^–6 mol/m³, and the combustion efficiency increases from 98.48% to 99.14%. As the volume fraction ratio of CO₂ to N₂ in the gas increases, the average temperature at the combustion chamber outlet decreases from 1 739.30 K to 1 694.99 K, the temperature distribution coefficient fluctuates in the range of 0.032~0.045, the NO_x emission concentration at the outlet decreases from 3.18×10^–6 mol/m³ to 1.39×10^–6 mol/m³, the CO emission concentration increases from 633.73×10^–6 mol/m³ to 832.45×10^–6 mol/m³, and the combustion efficiency decreases from 98.89% to 98.56%. In addition, as the fuel calorific value increases, the average temperature at the combustion chamber outlet significantly increases from 1 587.30 K to 1 862.39 K, the temperature distribution coefficient shows a downward trend, the NO_x emission concentration increases from 0.29×10^–6 mol/m³ to 18.66×10^–6 mol/m³, the CO emission concentration increases from 459.25×10^–6 mol/m³ to 1 030.61×10^–6 mol/m³, and the combustion efficiency decreases from 99.14% to 98.33%. Finally, 20 sets of data are selected for nonlinear surface fitting. For the blast furnace gas with a heat value range of 3~5 MJ/m³, all the the R² values of the fitting formula are greater than 0.90, indicating this formula can provide a theoretical basis for the control of low-heat-value fuels in gas turbine combustion chambers.

To enhance the peak shaving performance of heating units, a new process for double-reheat heating unit integrating five thermo-electric decoupling technologies, namely cylinder cut-off, high-/medium- and low-pressure bypass heating, heat pump, hot water tank and electric boiler, has been proposed. A detailed thermodynamic model of the system was established, and the peak shaving performance of the novel power plant is compared with that of a reference power plant. Relying on the electricity market, a systematic economic operation strategy was put forward, and a techno-economic analysis was performed. The results show that, when the heating demand is 1 460 MW, the reference plant cannot meet the heating demand under the extraction-condensing condition. Under the cylinder cut-off condition, the load regulation range of the reference plant is 77.9% to 80.0% of the rated load, and it almost loses its load regulation ability. While under the cylinder cut-off + bypass condition, the load regulation range of the reference unit is 50.0%~80.0%, and its peak regulation ability has been improved. For the novel plant, in the same heating demand, the load regulation range has been expanded to 0~80.0%, and zero-power grid connection can be achieved especially during the low electricity demand period. Compared with the reference plant, the novel plant can reduce the power output during peak shaving periods by 107 600 MW·h per month, save 17 700 tons of coal, achieve an annual net profit increase of approximately 68.988 million yuan during the heating season, and have a payback period for new equipment investment of 5.6 years, demonstrating significant economic benefits.

As the core of thermal power units, the operation efficiency of the direct air cooling system is significantly restricted by the geographical location of the power plant and the surrounding environmental parameters. Taking the direct air cooling system of a power plant as the prototype, a three-dimensional numerical model of the air cooling system and the surrounding buildings and mountain environment is established, and the composite wind prevention measures for the windward side of the air cooling island or the units with unfavorable heat transfer are proposed. The windproof measures and optimization mechanism of the direct air cooling system with strong applicability and good effect are explored, and the influence of air flow field reconstruction inside and outside the air cooling unit on the cooling performance of the direct air cooling system is analyzed. The results show that the internal and external wind-proof measures of the direct air-cooled unit can effectively improve the thermal performance of the unit. When the wind speed is 5 m/s, the large cross wall windshield has a good effect on improving the heat transfer performance of the air-cooled island. The frontal wind speed of the radiator increases by 0.24 m/s, and the surface temperature of the radiator reduces by 2.40 ℃. After the reconstruction of the air flow field inside and outside the air cooling unit, the average surface temperature of the radiator in the direct air cooling system reduces by 5.77 ℃, and the back pressure reduces by 2.92 kPa. The reconstruction of the air flow field inside and outside the air cooling unit can significantly improve the cooling effect of the direct air cooling system and improve the operating performance of the cold end system of the power station. In the future, the optimization design of the diversion device of the direct air cooling system can focus on the improvement of the uniformity of the flow field.

Scramjet engines are mainstream power systems for hypersonic vehicles, and it has significant thermal protection demand and power supply demand during the long-time and high-Mach-number flight of hypersonic vehicle. An integrated cooling and power generation system based on supercritical CO₂ Brayton cycle is designed for a certain type of scramjet engine. The characterization model of wall heat source for this scramjet engine is constructed. The influences of key design parameters, such as heat absorption pressure, turbine inlet temperature, heat release pressure, and regeneration degree, on the system thermodynamic performance are investigated, as well as the coupling relationships among various design parameters. The optimal design schemes and performance of the integrated cooling and power generation system are obtained by the multi-parameter collaborative optimization. The thermodynamic advantages of the proposed system are also evaluated by comparing with the conventional system with a simple cycle as the baseline. The results show that the proposed integrated cooling and power generation system can achieve a maximum power generation efficiency of 15.9% and a continuous power supply of 206.2 kW, which exhibits a good potential for actual application. The smaller the pinch temperature difference during the heat absorption process of the engine wall, the more significant the thermal performance advantage of the proposed system compared to the benchmark scheme, and the maximum relative increase in power generation efficiency can reach 9.3%.

To explore the ignition and stable combustion performance of ammonia fuel in simulated combustion chambers of gas turbines, ignition and combustion experiments were conducted on ammonia gas with different preheating temperatures and cracking degrees, and the ignition and combustion laws of ammonia fuel under certain experimental conditions were obtained. The results indicate that, stable combustion of ammonia requires a cracking degree of not less than 30% and an air preheater temperature of not less than 643 K. Within the temperature range of 743~943 K and combustion duration of 5~40 seconds in the air preheater, the internal temperature, tail temperature, and pressure of the combustion chamber generally increase with the preheater temperature and combustion duration. The NO emission volume fraction is significantly affected by the temperature of the preheater, it reaches the minimum (376 μL/L) at 673 K when the combustion efficiency is 96%. The zero dimensional simulation results show that, increasing pressure, ammonia cracking degree and temperature can help shorten the ignition delay time, and higher hydrogen content and slightly enriched combustion state can promote the increase of laminar flame velocity and optimize the combustion of ammonia.

The effectiveness of a data-driven model relies on the completeness of its training samples. For operating conditions beyond the scope of the training samples, the model’s generalization ability is compromised. Therefore, to develop a condenser model that can adapt to the wide load variation of the unit, it is essential for the training samples to involve a diverse range of power generation loads and ambient temperatures. However, achieving this complete dataset is difficult for newly-commissioned units because of their short operation time. To address these challenges, a method for characterizing condensing units using multi-fidelity data and transfer learning is proposed, even with incomplete data. In this method, a pre-trained model is firstly built based on the comprehensive operational dataset collected from a similar unit. On the basis of the pre-trained model, additional linear and nonlinear calibration networks are introduced. The calibration networks are updated through the incomplete data of newly constructed units, enabling the transfer of the pre-training model to the feature space that is adapted to the incomplete dataset. The effectiveness of this method is validated through the condenser of a 1 000 MW supercritical unit. The results indicate that, even with limited training samples, the method accurately predicts parameters such as condenser pressure and circulating water outlet temperature, with an average R² of 0.95, significantly outperforming the conventional data-driven model based on a single data set, of which the average R² is only 0.81.

The structural characteristics of once-through steam generators and throttling assembly in the demonstration project of high-temperature gas cooled reactors were introduced, and the reasons and influencing factors of sediment blocking the throttling holes were analyzed. Moreover, the deposition law of corrosion products on the throttling holes of steam generators in high-temperature gas cooled reactors was studied by dynamic cyclic tests at high temperatures and high pressures, including the effects of different iron sources, iron mass fractions, flow rates, and pH values on throttling hole deposition. The results show that, free iron is the main precursor of throttling pore sediments. The phenomenon of throttling hole sediment increases with the iron mass fraction in water. With the increase of local flow velocity, the sedimentation rate of throttling hole increases at first and then decreases, and there exists a maximum deposition velocity range. As the pH value of the water increases from 9.1 to 9.7, the phenomenon of throttle hole deposition intensifies. It is found that appropriately reducing the pH value of feed water and optimizing throttle hole structure size (adjusting flow rate) are effective methods to inhibit the deposition and blockage of steam generator throttling components.

In modern power systems, unit coordinated control faces complex dynamic characteristics and is influenced by faults and external disturbances. To address this challenge, a fault-tolerant control scheme designed for unit coordinated control systems under fault conditions is proposed. Firstly, the transfer function of the unit system is derived using mechanism analysis, and a mathematical model incorporating actuator faults is developed. This model enables the analysis of transient response, stability, and dynamic performance of the system. Secondly, by integrating adaptive techniques with H_∞ control theory, an adaptive fault-tolerant guaranteed-cost tracking control method is designed. This method can automatically compensate for degraded signals when faults occur in the system while further enhancing the robustness and fault tolerance of the system through performance indicator optimization. It satisfies the combined requirements for tracking accuracy and dynamic response. Finally, a simulation is conducted using a 300 MW unit coordinated control system as an example. The results demonstrate that, compared with the conventional fault-tolerant control methods, the proposed approach exhibits superior dynamic tracking performance, disturbance rejection capability, and fault recovery ability. This study provides a reliable control solution for ensuring the safe and stable operation of unit systems in power systems.