With the increasing demand for flexible operation of power plant boilers, frequent variable-load operation leads to a wide range of fluctuations in pollutant concentrations and flue gas parameters. Modeling of key indicators such as single pollutant or flue gas parameter can no longer meet the actual demand, so it is necessary to consider the coupling of multiple key indicators for synergistic predictive modeling. Based on the historical operation data of coal-fired power plants, feature extraction is performed through kernel function mapping, and a long short-term memory neural network with a hard parameter sharing structure is constructed for multi task prediction modeling. The prediction model is optimized using uncertainty loss methods. The experimental results show that, the proposed prediction model exhibits high prediction accuracy under variable load conditions, and the prediction errors for the key metrics involved in this study are reduced by 25.5%, 41.8% and 4.7%, respectively. The proposed method is capable of predicting several key indicators of utility boilers under variable load conditions, which can assist power plants to achieve pollution control and optimize the thermal efficiency of combustion, and provide technical support for intelligent operation of power plants.

To enhance the cybersecurity protection capabilities of power monitoring systems, a security reinforcement middleware for interal unidirectional safety isolating device for electric power has been designed. This middleware integrates compatibility adaptation, file format correction, encryption authentication, load balancing, and access control functions, addressing the security issues such as business system compatibility, hardware failures, and plaintext communication faced by isolation devices during the upgrading and reinforcement process. It enhances the security control of data transmission channels in power monitoring systems and achieves an “efficient and unobtrusive” and “standardized” security upgrade and reinforcement of the isolation devices. This middleware has been successfully applied to all thermal power, hydropower, and new energy power stations of Huaneng Group, strengthening the cybersecurity boundary protection capabilities of critical information infrastructure in power monitoring and ensuring the information security of power production.

In China, Xinjiang province has vast reserves of high alkali coal resources. However, in coal-fired boilers, fouling and slagging on heating surface caused by alkali metals significantly limit the efficient utilization of the coals. Based on gas-phase alkali metal detection, combined with flue gas temperature monitoring, heat transfer calculation and other methods, slagging monitoring was carried out on the heating surface of a tangentially-fired boiler burning high alkali coal. The influence of air distribution on flame temperature, gas-phase alkali metal mass concentration and heating surface heat transfer in the furnace was analyzed, and a quantitative relationship between the gas-phase alkali metal mass concentration and the heating surface heat transfer was established. Preliminary monitoring of fouling and slagging on the heating surface was also conducted. The results indicate that, slag sample on the water wall side was quite different from that on the flue gas side. The covered water wall surface was loose and porous, while the flue gas side was dense and hard black coke. Significant macroscopic differences were observed, with sodium crystalline phases mainly in the form of feldspar. The highest alkali metal concentration were observed in the main combustion zone of the boiler. The higher the ratio of upper to lower secondary air, the higher the temperature and gaseous alkali metal concentration in the furnace. An increase in the average gaseous alkali metal concentration by 1 mg/m³ resulted in a decrease in the heat transfer of the water wall by 0.82×10⁸ kJ at 300 MW on a tangentially-fired boiler burning high alkali coal.

To address the issues of flashback and high NO_x emissions in hydrogen-enriched gas combustion, a swirl-stabilized burner was designed using mild premixed combustion technology, and a feasibility study was conducted for its application in industrial boilers. Using a combination of experimental and numerical simulation methods, the study explored the equivalence ratio adjustment range of the mild premixed burner and the influence of hydrogen blending ratio on flame shape and pollutant emission characteristics. The experimental results showed that the mild premixed burner can achieve a wide hydrogen blending heat ratio adjustment range of 0~100%. The addition of hydrogen promoted a more uniform flame distribution, and the flame height decreased with the increasing hydrogen blending ratio. Additionally, the NO_x mass concentration experienced a rapid increase (for hydrogen blending ratios less than 30%) followed by fluctuations around 60 mg/m³. As the hydrogen blending ratio increased, the critical equivalence ratio for local flashback decreased, narrowing the stable combustion range between the blowout limit and the partial flashback limit. The widest equivalence ratio stable combustion range was achieved at a hydrogen blending ratio of 40%, which was 0.54~1.06.

To understand the inner wall temperature distribution characteristics of boiler heating surfaces during fast peaking operation, this study incorporates the coupling of non-uniform heat flux distribution on the combustion side with a multi-tube flow-resistance model on the working fluid side. This corrects the resistance and mass flow distribution among the rows of tubes in the superheater, forming a comprehensive heat transfer calculation model that couples the non-uniform heat flux on the flue gas side with the actual flow rate on the working fluid side, allowing for more accurate prediction of superheater temperatures. This model is applied to the calculation and analysis of wall temperature characteristics of a 660 MW counter-flow coal-fired boiler’s screen superheater at various loads and swirl angles. The study reveals that during deep load-following, the highest tube wall temperature at 30% load (868.4 K) exceeds that at 50% load (861.9 K), approaching the maximum temperature the material can withstand. The tube wall temperature at 50% load is higher than that at 75% load (849.7 K). Additionally, changes in swirl angle significantly affect the non-uniform distribution of flue gas and the working fluid temperature on the steam side. When the swirl angle is 45°, the high-temperature zone is primarily distributed at both ends of the tube screen. When the swirl angle is 15°, it concentrates in the middle front and middle rear regions. As the swirl angle increases, spatial heterogeneity of the flue gas field in the furnace enhances, leading to greater temperature non-uniformity across the superheater width. The research results can provide technical support for the design and retrofit of boilers during rapid load-following processes.

Due to its high parameters and high efficiency, ultra supercritical units have become a powerful support for deep frequency regulation, peak shaving, and suppression of power grid fluctuations. The optimization and transformation of control strategies for ultra supercritical units are of great significance for the safe and stable operation of the power grid. Aiming at the optimization problem of coordinated control system for ultra supercritical units, an intelligent control strategy based on error self-disturbance rejection control strategy and reinforcement learning algorithm is proposed. Firstly, in framework of the error-based self-disturbance rejection control strategy, the controlled object model of the machine furnace coupling process is simplified according to operating characteristics of the unit’s turbine-boiler coupled process, and an extended state observer is designed to estimate and compensate for the unmodeled dynamic characteristics and external disturbances of the unit in real time. Secondly, a reward function is constructed and the flexible actor-critic algorithm is used to achieve self-adaptive adjustment of controller parameters. Finally, the effectiveness of the proposed control strategy is verified through simulation based on actual historical operating data of a certain ultra supercritical 1 000 MW secondary reheating unit.

When thermal power units participate in deep peak loading, real-time acquisition of furnace temperature field is helpful to power plant boiler control and research of combustion process in the furnace. With the promotion of intelligent power generation, machine learning provides an important means for real-time acquisition of furnace temperature field. The principle and application of the three most commonly used online monitoring technologies of furnace temperature field, namely acoustic method, absorption spectral tomography and thermal radiation imaging, are summarized at first, and the advantages and disadvantages in the application of boiler furnace temperature measurement are reviewed. Then, the principle of the coupled machine learning and CFD prediction method is described in detail, indicating that the method is less affected in the harsh furnace environment, and the application research of the method in the combustion flame structure and parameters and the furnace temperature field is reviewed, demonstrating the feasibility of applying the method to the furnace temperature field, indicating it can accurately predict the furnace temperature field. Finally, the future development trend of furnace temperature field online monitoring technology and coupled machine learning and CFD prediction method is analyzed, so as to provide ideas for obtaining more accurate furnace temperature field in real time under the continuous advancement of intelligent construction of power station.

Peak regulation in thermal power plants is an inevitable trend under the development of new energy. Under this condition, the initial condensing zone of steam turbine moves forward and the corrosion of low pressure cylinder intensifies. Several methods such as electrochemical testing, sample weight loss and metal surface topography analysis (SEM, EDS, XRD, and so on) were used to study the pitting corrosion characteristics of 2Cr13 steel (the material of low pressure cylinder of the steam turbine) under the conditions of simulated initial setting zone, with different mass concentrations and different mass concentration ratios of Cl^– to SO₄^2– of three anions (Cl^–, SO₄^2– and CH₃COO^–). The test results showed that, the corrosion rate of 2Cr13 steel increased with the anions’ mass concentration, and the maximum corrosion rate (0.095 23 g/(m²·h)) occurred when was 2:1. Pitting corrosion was observed in all samples, and the number of pitting corrosion increased with the anions’ mass concentration. With the change of, Cl^– and SO₄^2– on the metal surface of 2Cr13 steel changed from site competitive adsorption effect to mutual synergistic effect, resulting in the intensification of uniform corrosion and pitting corrosion. The chloride ions and sulfate in the initial coagulation zone of steam turbine will accelerate the corrosion rate of 2Cr13 steel and the occurrence of point corrosion. In actual operation of power plant, measures should be taken to prevent the leakage of condenser tubes and the broken particles of positive resin should be effectively removed.

With the growth of installed capacity of renewable energy power generation, coal-fired units need to undertake more peaking tasks. In order to improve the operational flexibility of coal-fired units, a 1 000 MW unit is taken as the research object, and six heat storage configurations and four heat release configurations of molten salt coupling are proposed based on the Ebsilon software, and the thermo-economic indexes of different heat storage and heat release coupling configurations are analyzed comparatively. The results show that, the peak shifting capacity of the system in the heat storage stage is positively correlated with the pressure loss of the heat transfer steam, and the thermal economy of heating the deaerator outlet feedwater in the heat release stage is the best. The heat storage of the electrically heated molten salt has the highest thermal and exergy efficiency, and configuration D-a has the strongest peak shifting capacity, with a peak shifting depth of up to 23.61%, but it has the largest coal consumption rate and exergy loss. Configuration F-d has the best thermal economy, with peak shifting depth, thermal efficiency, fuel efficiency and coal consumption rate of 23.42%, 39.61%, 38.40% and 310.2 g/(kW·h), respectively.

In order to study the effects of different drying conditions on crushing rate and pulverization rate of Baoqing lignite after drying, as well as the effects of different drying moistures on spontaneous combustion and explosion characteristics of the coal samples, several experiments were conducted, like the drying of raw coal, and the spontaneous combustion and explosion characteristics of coal samples with different moisture contents. The results show that, a drying furnace temperature above 300 ℃ and a higher heating terminal temperature can achieve a higher coal sample dehydration rate. Coal particles with smaller particle sizes tend to achieve higher dehydration rates and lower crushing rates. The pulverization rate of 6~13 mm coal particles is the highest under different drying conditions. Baoqing raw coal is a type of coal that is prone to spontaneous combustion. As the moisture content of the dried coal sample decreases, the spontaneous combustion tendency of the raw coal weakens and becomes a type of coal with moderate spontaneous combustion tendency. As the moisture content of the coal sample increases, the explosion tendency of the test coal sample decreases. As the fineness of coal powder R90 increases, the explosion tendency of coal powder decreases. Therefore, in the engineering application process of Baoqing lignite drying technology, the proportion of 6~13 mm coal particles should be reduced to lower the pulverization rate during the drying process. The air temperature during coal powder transportation should be appropriately reduced, or the fineness of coal powder should be appropriately increased to reduce the tendency for explosion.