Based on the concept of high efficiency of gas turbine variable back pressure operation regulation, a high back pressure gas turbine combined cycle power generation system scheme is proposed, in which a pre-compressor and an expander are set in front and behind the main top cycle respectively to maintain and regulate the gas turbine exhaust pressure. Key parameters of the combined cycle are designed based on the initial parameters of the F-class gas turbine, and the case and characteristic analysis are carried out for the temperature of recirculated gas (divided into two conditions: cooling to normal temperature and not cooling), the main top cycle pressure ratio and the gas turbine back pressure. The results show that, the combined cycle efficiency of the recirculated flue gas cooling is not as high as that of the non-cooled flue gas cooling, which is 58.07% and 58.94% when the turbine back pressure is 0.30 MPa. The exergy loss rate of the main compressor is lower because the exit temperature of the main compressor is higher when the recirculated flue gas temperature is higher. When the gas turbine back pressure is 0.30 MPa, the maximum pressure ratio of the combined cycle system efficiency is 17.0, the corresponding combined cycle efficiency is 58.97%, and the specific work is 563.87 kJ/kg. Considering the specific work comprehensively, the recommended main top pressure ratio is 15.4, and when the turbine back pressure is from 0.03 MPa to 0.35 MPa, the variation range of the combined circulation efficiency under the two conditions is about 56.00%~58.57% and 55.81%~59.12%, respectively, which increases at first and then decreases, and the variation range of the combined efficiency is not large at high back pressure. At the same time, based on the practical engineering application, the design of a single waste heat boiler is considered, and its thermal characteristics and possible flexible, low-cost and efficient utilization of renewable energy are analyzed, which provides a new system scheme reference for the flexible and efficient modern combined cycle with multi-energy complementarities.

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.

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.

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%.

The Brayton cycle is widely recognized as a key power cycle in the third-generation solar thermal power generation technology. Leveraging the strengths of artificial neural network methods for importance evaluation and quantitative analysis, this research employs a control variable approach to identify critical parameters, including turbine inlet temperature and compression ratio, from a range of operating parameters. In this method, the significance of parameters increases as the R² value decreases. Notably, when excluding these key parameters, the R² values fall to 0.57 and 0.64, respectively, both are lower than other operating parameters. Furthermore, the quantitative analysis of output power in the Brayton cycle yields exceptional results, achieving an R² value exceeding 0.999. The R² values for thermal efficiency and input heat are 0.992 and 0.988, respectively. Finally, the multi-objective optimization results suggest optimal settings of 500 ℃ for turbine inlet temperature and 2.19 for the compression ratio, corresponding to a thermal efficiency of 46.58%, output power of 100.97 kJ/kg, and input heat of –176.5 kJ/kg. This study offers valuable insights for the operational efficiency and performance assessment of the Brayton cycle in solar thermal power plants.

Based on the design and operational conditions of Guangdong Huaying LNG Terminal and its surrounding industrial environment, a cascade utilization scheme integrating thermodynamic power generation with shallow cold storage was developed. Moreover, key process parameters were modeled and solved using HYSYS software to enhance energy efficiency and maximize cold energy utilization. The results show that, under the condition of minimum daily send-out (228 t/h), the original single-stage thermodynamic cycle coupled with cold storage achieved an annual power generation exceeding 32.83 GW·h while meeting the cooling demand of a 7 500 m³ cold storage facility. The optimized scheme adopts a two-stage thermodynamic cycle with shallow cold storage, via employing a 40% (weight percentage) ethane and 60% (weight percentage) propane mixed working fluid, and elevating heat source temperature, this improved design increased the annual power generation to 62.04 GW·h, and raised the net power output per unit mass of LNG from 17.54(kW·h)/t to 33.02 (kW·h)/t, with estimated annual electricity cost savings of approximately 53.641 million yuan. Although multi-stage heat engine cycles can reduce irreversible losses caused by temperature differences, considering factors such as cost-benefit ratio and operational reliability, the second scheme demonstrates strong engineering feasibility and economic viability by closely aligning with the actual conditions of the Huaying LNG Receiving Terminal. Both cascade utilization designs demonstrate distinct advantages for different development stages of the receiving terminal and different evaluation indicators for LNG cold energy utilization, providing valuable references for post-commissioning cold energy applications.

A novel healthy state monitoring method for offshore booster station platforms is proposed to enhance the damage detection capabilities under complex operating conditions. Using a deep learning framework based on memory unit autoencoders, the method magnifies fault-relevant features via denoising and angular domain resampling high-frequency vibration data from offshore boosting stations. The model employs a deep convolutional neural network to learn historical data patterns, constructs a hidden state memory bank, and achieves sparse matching between sample encoded features and the memory bank. Finally, a Gaussian mixture probability model is employed to model the generated membership scores to assess the health status of the booster station. A case study of the offshore booster station in Rudong, Jiangsu, validates the approach, achieving an anomaly recall rate and accuracy of over 98%, outperforming other comparison algorithms.

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.

Ammonium bicarbonate is a potential denitrification reducing agent that can efficiently produce ammonia gas through direct solid pyrolysis. The pyrolysis reaction of ammonium bicarbonate solid is numerically simulated, a pyrolysis ammonia production system suitable for coal-fired power plants is designed, and the economic feasibility of the ammonium bicarbonate pyrolysis ammonia production process is analyzed. The simulation results show that, the pyrolysis process of ammonium bicarbonate favors the atmosphere pressure and the conversion rate of pyrolysis rapidly increases when the reaction temperature is above 110 ℃. The pyrolysis system of ammonium bicarbonate for a 660 MW unit has been designed and calculated. An external heating pyrolysis reactor is adopted to realize the utilization of waste heat and stable solid feeding. Steam or flue gas from the coal-fired power plant is used as the heat source for pyrolysis. At 110 ℃, a conversion rate of 95% can be reached within 10 minutes for ammonium bicarbonate feed. Compared with the urea hydrolysis process, the equipment cost, land occupation and operating cost of the ammonium bicarbonate solid pyrolysis process all significantly reduce, showing good prospects for promotion and application.

At home and abroad, the locations suitable for developing concentrated solar power are mainly in desert areas. Dust in these environments may accumulate on the heat absorbing surfaces of the receiver in the solar power tower system, resulting in failure of the wall and coating of the pipe. To protect the heat absorbing walls, a coupled heat transfer model is developed for the sand-pipe, and the effects of several parameters on the wall temperature are investigated, such as the dust particle diameter, the contact areas between the dust and tube wall, and the concentrated solar energy flux density. The results show that, the influence of dust particles on the temperature of the heat-absorbing pipes is limited to a small area, but it will cause local high-temperature hot spots on the pipes. With a high concentrated solar energy flux density, a large dust particle diameter and a small contract area between the dust particles and the heat-absorbing pipes, both the temperature of the dust particle and the hot spot at the pipes will increase greatly. The temperature of the dust particles could exceed their melting point, forming calcium-magnesium-aluminum-silicate (CMAS) deposits, which means the receiver is at risk of CMAS corrosion. Meanwhile, the high-temperature hot spots on the heat-absorbing pipes will affect the local thermal stress distribution, exacerbating the damage to the receiver. Therefore, during actual operation, the cleanliness of the heat-absorbing pipe walls should be regularly inspected to avoid the accumulation of large-sized dust particles. The research results can provide technical guidance for the operation and maintenance of the receiver in the concentrated solar power system.

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.

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.

To address the challenges of low diagnostic accuracy and poor interpretability for minority fault classes caused by imbalanced data distribution in coal mill pulverizing systems of coal-fired power plants, a fault diagnosis method integrating SMOTE data enhancement, Dirichlet prior smoothing, and Bayesian networks is proposed. The SMOTE technology expands the feature space of minority fault samples to alleviate data scarcity, while Dirichlet prior smoothing optimizes conditional probability estimation in Bayesian networks, resolving zero-probability issues caused by insufficient samples. A hierarchical Bayesian network architecture is constructed by incorporating domain knowledge and data-driven structure learning, enabling a dual-mode diagnosis strategy that combines rapid fault node inference with indirect attribute node analysis. The experimental results based on real industrial data demonstrate that the proposed method achieves high diagnostic accuracy and interpretability under imbalanced data scenarios. The solution provides real-time performance, precision, and transparency for coal mill fault diagnosis, offering significant engineering value.

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.

A hybrid prediction model combining enhanced grey wolf optimization algorithm (EGWO) and long short-term memory (LSTM) neural network is proposed to address the problem of low accuracy in predicting the mass concentration of NO_x at the outlet of selective catalytic reduction (SCR) denitrification reactors using conventional mechanism modeling methods. Firstly, based on principal component analysis (PCA), the raw data is processed and filtered to achieve dimensionality reduction of input variables. Then, the EGWO is used to optimize the hyperparameters of LSTM. Finally, the input variables are used as inputs for the EGWO-LSTM model to predict the mass concentration of NO_x at the outlet. Taking a 1 000 MW ultra supercritical thermal power unit in China as an example, simulation results show that the proposed model performs the best in error control, with root mean square error reduces by 50.36% compared to the conventional LSTM model, and by 76.14% compared to the BP model, and the mean absolute percentage error of the model is only 1.01%. The EGWO has fewer iterations and higher convergence accuracy compared to the GWO when converging to the optimal solution.

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.

As a core control parameter in peak regulation via banking fire, the banking fire duration directly affects the safety and economic efficiency of unit operation. However, due to the complex coupling and dynamic characteristics of thermodynamic parameters during the banking process, it is difficult for existing calculation methods to achieve efficient and accurate calculations. An energy-balance-based method was proposed for banking fire duration calculation in subcritical CFB boilers. A dynamic equilibrium model was established for heat storage and turbine heat utilization and heat dissipation during banking fire, deriving heat storage and release formulas for key heat sources, such as bed material, refractory, metal heating surfaces, working fluid, and carbon combustion. Finally, the banking fire duration was obtained. Taking a 300 MW sub-critical CFB unit as an example, the absolute error between the calculated value and the measured value is controlled within 5 minutes, and the relative error is less than 10%, which can meet the engineering requirements of fire-hold peak-shaving. The results demonstrate that, in terms of heat storage, the heat storage of metal heating surfaces contributes 35%~41% to the banking fire duration. The contributions of bed material and refractory are each approximately 20%, and the contribution of carbon combustion in the bed material is 10%~15%. The contributions of gas and working fluid heat storage are less than 2% and can be neglected. In terms of heat consumption, heat consumption for power generation accounts for the highest proportion, and it increases with the electrical load. The heat required for the steam turbine to overcome its own rotational resistance accounts for approximately 20%, and the proportion of heat dissipation of the unit is less than 5%. By raising the initial temperature of banking fire, increasing the amount of bed material, using coal with high volatile content, and reducing the electrical load of the unit during banking, the banking fire duration can be significantly prolonged. Notably, the banking fire duration exceeds 2 hours only when the average electrical load during banking is reduced to 1% of rated load.