The heat transfer characteristics and safety of a single tank thermal storage system during charging and discharging cycle are important indicators affecting the performance of the thermal storage tank. By coupling finite volume method and finite element method, a comprehensive model of a multi-layer wall structure molten salt single tank system is established, and the effects of inlet flow velocity and inlet/outlet temperature difference on the dynamic thermal characteristics and mechanical properties of the thermal storage tank during continuous charging and discharging cycling process are explored. The results indicate that, increasing the inlet flow rate will reduce the heat storage and improve the thermal efficiency, but will also increase the equivalent stress on the tank wall. Increasing the temperature difference between the inlet and outlet will increase the heat storage and reduce the thermal efficiency, and also increase the equivalent stress on the tank wall. To ensure the heat storage and thermal efficiency of the single tank heat storage system, as well as the safety of the system, for the single tank system with a heat storage capacity of 40 MW·h, the inlet flow rate of molten salt should be controlled within 0.002 60~0.003 46 m/s, and the temperature difference between the inlet and outlet of molten salt needs to be controlled within 200~250 K.

Data quality is a key factor affecting the application effectiveness of optimization models of denitrification system operation. In response to the problems of lagging and poor representativeness of monitoring parameters in denitrification system operation, a denitrification performance parameter dimension reduction technology suitable for real-time performance monitoring is developed. The utilization rate of reducing agents that can reflect the denitrification ability of the denitrification system itself is set as the monitoring and evaluation parameter for denitrification system operation status, to improve the efficiency of data generation. Based on this, an optimization method for denitrification system operation that can eliminate adjustment delays is established, and an identification technology for typical abnormalities in denitrification system operation is constructed to guide the economic, safe, stable, and standard operation of the denitrification system. This technology has been implemented and applied in a 1 000 MW coal-fired unit at different loads. The results show that, the denitrification system operation guided by the utilization rate of reducing agents reduces the unit consumption of urea solution by 1.5%~8.4% and the ammonia escape at the denitrification system outlet by 10.7%~27.0%, and all of the ammonia escape at different loads meets the general control value of ammonia escape rate. The variation range of NO_x emission mass concentration in the exhaust reduces from 44.5~58.3 mg/m³ to 9.2~10.6 mg/m³, and the distribution deviation significantly decreases from 59.2%~75.2% to 21.4%~25.1%, which is more conducive to the automatic and stable control of the denitrification system.

The formation and emission of SO₃ in coal-fired flue gas not only pose significant threats to atmospheric environments and human health but also negatively affect power plant operations. Injecting alkaline sorbents into flue gas has proven to be an effective method for SO₃ removal. The removal efficiency of SO₃ by injecting Na₂CO₃ and Ca(OH)₂ absorbents was investigated under different flue gas conditions, and the removal performance was compared with that of the blended absorbents. Moreover, the physicochemical properties of the alkaline absorbents before and after the reaction were characterized using SEM, XRD, FT-IR, and XPS techniques. Based on experimental data and characterization results, the gas-solid reaction model were proposed to elucidate the mechanisms of SO₃ removal by Na₂CO₃ and Ca(OH)₂. Furthermore, the adsorption process of Na₂CO₃ on SO₃ was simulated, and the adsorption energy was calculated and compared with that of Ca(OH)₂. The results showed that, Na₂CO₃ demonstrated superior SO₃ removal efficiency compared with Ca(OH)₂, and the removal efficiency was enhanced by increasing the reaction temperature, SO₃ mass concentration, absorbent stoichiometric ratio and residence time. The blended absorbent with a molar ratio of Ca:2Na:S=5.00:1.25:1.00 achieved an SO₃ removal efficiency of 86.07% under practical operating conditions at a low cost. The findings indicated that the gas-solid reaction between Na₂CO₃ and SO₃ followed the shrinking core model, while the reaction between Ca(OH)₂ and SO₃ adhered to the grain model. The adsorption energy of SO₃ on Na₂CO₃ was higher than that on Ca(OH)₂. This study can provide theoretical insights and technical support for efficient and cost-effective removal of SO₃ from coal-fired flue gas.

Due to the significant volatility and randomness of wind power data, low prediction accuracy is often observed with a single model in wind power prediction. To overcome this, an ultra-short-term wind power prediction method is introduced, based on modal decomposition and a combined neural network model. Firstly, the wind power data are processed based on the improved fully integrated empirical modal decomposition and sample entropy, which decomposes the unsteady series into smoother sub-sequences and reconstructs the high-frequency oscillatory component and low-frequency smooth component synchronously. Secondly, a hybrid prediction model for wind power based on an adaptive sparse self-attention mechanism is constructed. For the high-frequency oscillatory component with high complexity, the adaptive sparse Transformer model is used to fully explore the fluctuation information. For the low-frequency stationary components, the sequence features are fully extracted by the bidirectional gated recurrent unit model. Finally, the final prediction outcomes are derived by overlaying the forecast results of each component. Test was performed with actual data from a wind farm in Shandong, and the results show that, compared with other commonly used models, the proposed model’s root mean square error and average absolute error has decreased by 2.644 MW and 2.42 MW, and the coefficient of determination has a notable 18.2% increase, implying it has a good prediction performance.

A 300 MW supercritical carbon dioxide (S-CO₂) Brayton cycle oxyfuel power generation system is designed, and a simulation model is constructed using process simulation methods to study the effects of key operating parameters (such as the primary dry cycle flue gas ratio, the economizer side split ratio, the cold primary air temperature and the high-pressure turbine inlet pressure) on the system’s thermal performance indexes. The effects of key operating parameters such as primary dry cycle flue gas ratio, economizer side split ratio, cold primary air temperature and high-pressure turbine inlet pressure on the system thermodynamics were investigated, and the thermal characteristics of the generating unit were revealed. The results show that, the boiler efficiency decreases with the increase of the proportion of primary dry-cycle flue gas, and when the proportion of primary dry-cycle flue gas reaches 50%, the net electric efficiency of the system is the highest, which is 42.93%. The boiler efficiency rises at first and then decreases with the increase of the coal economizer-side shunt ratio, and the net electric efficiency of the system reaches the highest (42.86%) when the coal economizer-side shunt ratio is 11%. With the increase of cold primary air temperature, the boiler efficiency keeps increasing, and the rising trend slows down and stabilizes at 99.29% at temperatures higher than 65 ℃, and the net electric efficiency of the system keeps increasing and reaches 43.06% at 95 ℃. With the increase of high-pressure turbine inlet pressure, the boiler efficiency firstly rises and then decreases, and reaches the maximum value of 99.35% at 29.5 MPa, and the net electric efficiency of the system reaches the optimal value (43.66%) at 29.0 MPa.

Molten salt energy storage technology is widely used in solar thermal power generation due to its high thermal capacity and good thermal stability. To optimize the influence of key operating parameters on energy storage efficiency, numerical simulation methods are used to analyze the mechanism of input velocity, initial temperature, temperature difference and other parameters on the formation of thermocline and heat storage efficiency at different horizontal positions. The results show that, increasing the temperature difference and the input speed can significantly promote the development of the thermocline, and increase the heat storage efficiency by more than 10%. The parameter optimization algorithm based on response surface methodology identifies an optimized parameter combination, which improves the heat storage efficiency by a maximum of 16.3 percentage points compared to the previous simulations. At the same time, to quickly and accurately predict the operating temperature of the system, three machine learning models are compared, and it finds out that the random forest model has the best prediction with an accuracy rate of 98.78%. The research results provide theoretical basis and application reference for the optimization design of molten salt energy storage systems.

The complex and variable meteorological conditions have a significant impact on operational characteristics of indirect air cooling systems. To enhance the cooling performance of indirect air cooling systems, an optimized regulation strategy for circulating water in indirect air cooling systems is proposed. By taking the indirect air cooling unit in a power plant as an object and considering the influence of surrounding buildings, the optimization distribution of circulating water flow in each sector of the air cooling heat exchanger is numerically studied. Firstly, a one-dimensional thermodynamic model of the indirect air cooling unit and a three-dimensional numerical model of the indirect air cooling tower are established and coupled for numerical calculation. Secondly, the influence of different meteorological conditions on the operating back pressure of the unit and the flow and heat transfer characteristics of the cooling tower is analyzed. As a result, the economic back pressure variation law of the unit under specific environmental meteorological conditions is obtained. Finally, constrained by the economic back pressure of the unit, the circulating water flow rate of each sector of the indirect air cooling heat exchanger is optimized according to the so-called heat load matching principle, which enhances the flow and heat transfer performance of the indirect air cooling system. The research results indicate that as the ambient temperature increases, the economic back pressure will also increase accordingly. When the ambient wind speed increases, the economic back pressure of the unit also increases. By optimizing the distribution of circulating water flow in each sector of the indirect air cooling heat exchanger, the uniformity of the outlet water temperature in each sector can be improved, the average outlet water temperature of the intercooled tower can be reduced, the total circulating water flow can be decreased, and the operating economy of the unit can be improved. This study can provide theoretical basis and reference for optimizing the operation of indirect air cooling units.

The deposition of corrosion products in orifice of the steam generator of high temperature gas cooled reactor (HTGR) in nuclear power units threats to safe operation of the unit seriously. To effectively inhibit the deposition of corrosion products in the orifice, the influence of dissolved oxygen in water on the orifice deposition rate was studied under the simulated water condition in the secondary loop of the HTGR. Moreover, the variation law of ZETA potential with dissolved oxygen in iron solution was also studied. It is found that the deposition rate of corrosion products in the orifice area is extremely sensitive to the dissolved oxygen, it decreases with the increase of dissolved oxygen concentration in water. Secondly, over high pH value is not conducive to the inhibition of orifice deposition, which is mainly due to the effect of dissolved oxygen and pH value on the ZETA potential. The wall current electrokinetic effect plays an important role in the orifice deposition, and increasing the concentration of dissolved oxygen in feed water is an effective method to restrain the orifice deposition and clogging in the steam generator of HTGR.

With the increase in parameters and capacity of newly built coal-fired units, the expansion of critical long-distance and large-diameter pipelines due to high parameters becomes more significant, making the design of supports and hangers particularly important. In a case involving a 2×660 MW ultra-supercritical unit, the diagonal brace of a rigid hanger tripod supporting the main steam pipeline buckled, resulting in a pipeline subsidence of nearly 130 mm. A comprehensive inspection of the pipeline supports and hangers was conducted, along with mechanical analysis of the statically indeterminate tripod structure and stability analysis of the diagonal brace. The study concluded that the failure of the diagonal brace and the pipeline sinking were primarily caused by an incorrect design of the radial horizontal restraint gap. Additionally, the excessive constant force of the constant hanger also contributed to the damage of the diagonal brace. This research not only analyzed the design flaws of the pipeline supports and hangers, but also proposed an engineering solution to optimize the restraint gap, which was validated on-site. A rectification plan involving horizontal limit adjustment and pipeline lifting was developed and implemented, successfully restoring the pipeline to its designed state and resolving the issue. This problem is highly representative in the construction of large-scale power units and should draw the attention of designers to avoid similar issues in future projects.

In light of the intricate nature of surface defects in wind turbine blades, conventional convolutional neural networks face problems such as threshold screening and non-maximum suppression processes, which increase computational complexity and are not conducive to model deployment. A novel defect detection model that integrates real-time-detection transformer (RT-DETR) with YOLOv5 algorithm is proposed. Firstly, the backbone network of YOLOv5 is redesigned based on RepVGG and FasterNet to reduce the computational complexity of the model. Recognizing the presence of small-sized targets within the detection tasks, an efficient channel attention (ECA) mechanism is integrated into the neck network’s feature fusion component, thereby augmenting the expressiveness of the output features. Finally, the detection head of original network is reconstructed with the Decoder from RT-DETR, minimizing the effect of non-maximum suppression on the model’s performance. The experimental results show that, the average detection accuracy and accuracy of YOLO-RT are 87.2% and 92.7%, respectively, on a self-constructed dataset of wind turbine blade surface defects, reflecting improvements of 4.4 and 8.0 percentage points over the original YOLOv5 model. The detection rate reaches 118.3 frames per second, surpassing that of alternative detection models. The enhancements introduced in this algorithm significantly improve both detection accuracy and speed, making it highly suitable for practical applications in detecting surface defects on wind turbine blades.