In view of the problems that conventional fly ash carbon content prediction models are prone to fall into local optimal solution traps and have insufficient generalization ability, based on the boiler hot-state multi-condition tests, 28 key characteristic parameters are selected through data collection, processing, Pearson correlation analysis of variables, and importance ranking, the sparrow search algorithm (SSA) is used to determine the optimal hyper-parameters of the random forest (RF) model, and an SSA-RF prediction model is constructed. The model verification results show that the root-mean-square error of the SSA-RF model in the training set and the test set decreases to 0.010 8 and 0.019 1 respectively, and the coefficient of determination R² increases to 0.999 7 and 0.998 1 respectively, demonstrating the excellent prediction accuracy and generalization ability of the model. Furthermore, the ISSA-RF-SSA algorithm is proposed. The SSA is improved by integrating multiple strategies to achieve global extreme value optimization of combustion parameters. Engineering verification shows that after optimization, the carbon content in fly ash decreased from 2.500% to 1.345%, and the prediction error was only 0.003 percentage points, verifying the accuracy of the model. The research results indicate that the ISSA-RF-SSA method improved by multiple strategies significantly enhances the optimization performance of the algorithm, providing a new idea for the combustion optimization of coal-fired units.

Supercritical water coal gasification for hydrogen production is a clean and efficient power generation technology. Based on entropy generation theory, numerical investigation on the non-equilibrium condensation flow of an H₂O/CO₂ mixed working fluid in the final-stage cascade is conducted. The losses are quantified by identifying regions within the cascade where different types of losses occur and calculating the entropy generation in each region. The mechanisms behind the impact of back pressure and CO₂ mass fraction in the mixed fluid changes on various losses and entropy generation sources are analyzed. The effects of these parameters on the loss distribution are explored, including a detailed description of how shock waves influence wake losses and the entropy generation distribution within the boundary layer. The results show that wall losses, wake losses, and boundary layer losses consistently account for over 90% of the total losses under different operating conditions. The main sources of entropy generation are wall dissipation, direct dissipation, and turbulence dissipation. When the back pressure increases by 5.03 kPa, the total loss decreases by 31.73%. However, when the CO₂ mass fraction in the mixed fluid increases by 40%, the total loss increases by 4.71%. The variation in turbulent dissipation entropy generation within the wake loss is the primary cause of the total loss change and is closely linked to the velocity gradients in the flow field. This study offers significant insights for the loss analysis of the wet steam region in mixed medium steam turbines and for aerodynamic optimization.

As an important parameter reflecting the combustion process, temperature distribution in a furnace is related to the safety, economy and pollutant emission level of the combustion process, which is of great significance for boiler control and the study of the combustion process in the furnace. The radiation imaging method is suitable for reconstruction of furnace temperature field due to its high temporal and spatial resolution and easy implementation on site. An online measurement technology of furnace temperature field based on optical tomography is proposed. A reconstruction algorithm combining deep learning with regularization algorithm is adopted to solve the ill-posed problem in the temperature field reconstruction process. Firstly, a radiation imaging model is established according to the set parameters such as furnace size, medium radiation characteristics, and CCD camera installation position. A large amount of data is obtained through direct problem calculation. Then, the appropriate Tikhonov regularization parameter is found through an automatic optimization algorithm to construct the training data set, and the accuracy and stability of the solution are evaluated. Finally, a deep neural network model is established to predict the optimal regularization parameter and then reconstruct the temperature field. The results show that this furnace temperature field reconstruction algorithm has an error less than 5%, showing good accuracy. After adding the measurement error, the reconstruction error is within 5%, indicating that the method is robust. At the same time, this method has high computational efficiency and meets the requirements of real-time monitoring of temperature fields.

A field test and numerical simulation study is carried out on the slagging problem of a 1 000 MW double-tangential coal-fired boiler during the co-firing of high ash melting point coal and low ash melting point coal. The test results show that as the proportion of low ash melting point coal increases, the slagging in the furnace shows a significant aggravation trend. When the proportion of low ash melting point coal is 50%, slight slagging occurs in the furnace. When the proportion increases to 67%, large-scale coking occurs on the bottom of the large screen heat transfer surface. When the proportion reaches 83%, the slagging situation deteriorates significantly, and the proportion of slag blocks in the furnace slag exceeds 40%. The numerical simulation results of slagging are in good agreement with the field operation test results. The results show that slagging is mainly concentrated in the front and rear wall areas, and the degree of slagging on each heat transfer surface increases with the proportion of low ash melting point coal. Although the addition of low ash melting point coal does not significantly change the near-wall temperature, the significant reduction of the ash melting point of the mixed coal is the fundamental reason for the deterioration of slagging. The operation mode of low ash melting point coal in the burner has a significant effect on slagging, especially when the low ash melting point coal is co-fired in layers D and C, the slagging trend is particularly obvious. It is recommended to prioritize the arrangement of low ash melting point coal in layers A and B, followed by layer F, and avoid co-firing low ash melting point coal in layers D and C.

The optimization design of the first domestically produced full-capacity feedwater pump used for No.9 unit of the Huaneng North Power Dalat Power Plant Phase V expansion project (1×1 000 MW) is introduced. The three-dimensional structural model of the feedwater pump is established by using ANSYS Workbench software, and the thermal stress analysis of the pump body and finite-element calculation of the impeller strength are conducted. Moreover, the trial operation of the turbine-driven feedwater pump unit and optimization suggestions are provided. The feedwater pump runs under various load conditions of the unit, ensuring that the feedwater flow and pump outlet pressure meet the operational requirements, with the temperature and vibration indicators of each bearing in the steam pump unit falling within the excellent range. Based on the performance assessment test data of the feedwater pump, the calculated efficiency is 84.32%, which exceeds the guaranteed efficiency value. The successful application of this domestically produced full-capacity steam feedwater pump unit in a 1 000 MW coal-fired unit can provide experience for planned or newly constructed units and has certain reference value.

When multiple units are used for combined heating, the distribution of thermoelectric loads among the units significantly affects overall energy consumption. For a thermal power plant where Unit 1 and Unit 3 adopt a dual-mode coupled heat-supply method with zero output of the low-pressure cylinder and steam extraction, and Unit 2 and Unit 4 adopt a triple-mode coupled heat-supply method with high back-pressure, heat pump, and steam extraction, an off-design condition model was established using EBSILON software. The thermoelectric characteristics and energy consumption characteristics were analyzed by adjusting parameters such as main steam flow, zero output steam volume of the low-pressure cylinder, heat supply power of the heat pump, and high-back-pressure heat-supply flow rate. The operational boundaries of electrical and thermal loads and the relationship between coal consumption and thermoelectric load were fitted using the least squares method. Under the fixed boundary conditions for the entire plant’s heating load and power supply load, the optimization of thermoelectric load distribution was achieved using particle swarm optimization. The results indicate that large-capacity high back pressure heat pump units should provide heat load, and small-capacity high back pressure heat pump units should provide electric load. After optimization, the total coal consumption of the whole plant was reduced by 0.6~10.0 t/h, resulting in a degree of optimization of 0.3%~3.9%.

Phosphate ester fire-resistant fluids, serving as hydraulic working medium for the speed regulation system of steam turbines, play a crucial role in the normal operation of steam turbines. Currently, imported products dominate the phosphate ester fire-resistant fluids market for the speed regulation system of steam turbines in domestic power generation units. To break the power industry’s high dependence on imported fire-resistant fluids, it is imperative to develop domestic phosphate ester fire-resistant fluids through independent research and application. Through performance evaluation of various domestic tri-aryl phosphate esters, tri-(dimethylphenyl) phosphate was identified as the optimal choice for domestic fire-resistant fluid development. Via oxidation and adsorption refining processes, the stability of the domestic tri-(dimethylphenyl) phosphate was significantly enhanced, resulting in the successful development of high-performance phosphate ester fire-resistant base oil. After the research on various additives, an optimized additive formulation was established, ultimately producing high-performance phosphate ester fire-resistant fluid that meets the new fluid requirements specified in Guide for Operation and Maintenance of Phosphate Ester Fire-resistant Fluid Used in Power Plant (DL/T 571—2014). Static and dynamic simulated aging tests demonstrated that the domestic phosphate ester fire-resistant fluid exhibits superior anti-aging performance compared to the commercially available alternatives. Following one year of industrial demonstration in power generation units, the fluid maintained new-oil quality standards throughout the application period, with the turbine governing system operating normally.

Improving the flexibility of coal-fired power generation units is of great significance for ensuring the reliable and stable operation of the power grid. The heat and mass transfer process in the CFB boiler furnace is investigated deeply. It is found that when the load changes, the air volume entering the furnace responds rapidly, driving the change of the particle suspension density in the dilute phase zone, thus triggers the rapid change of the convective heat transfer coefficient and the total heat flux. Different from pulverized coal-fired boilers, the average furnace temperature of the CFB boiler changes little with load. During the load change process, although the heat storage capacity is large, the thermal inertia is not fully manifested, and it does not have a negative impact on the load change rate. Therefore, the load adjustment process of the CFB boiler is based on the rapid response of the heat transfer coefficient under near constant temperature conditions, which is essentially different from the load-changing mechanism of the pulverized coal-fired boiler. In addition, a considerable amount of unburned carbon in the bed material can serve as a potential fuel supply source when the load increases. When the oxygen supply is increased, the combustion rate can be rapidly improved. Combined with the heat storage of bed materials and castable, the CFB boiler can be regarded as having a built-in “energy storage” function, providing long-term energy support for load adjustment. Measures such as reducing the average bed material size, decreasing the feeding coal size, and adding powdered-coal and circulating ash can further increase the load-changing rate of the CFB boiler. The test results on a 300 MW subcritical CFB boiler unit show that the load increasing and decreasing rate can reach 4%~9%Pe/min, approaching the load-changing capability of a gas turbine unit. The research demonstrates that the CFB boiler has the potential for rapid load change in principle and will play a more crucial role in the new power system dominated by renewable energy sources.

The deep peak shaving and flexible operation of thermal power units increase the risk of crack faults in the rotors of main and auxiliary equipment, posing a serious threat to the safe and stable operation of the units. According to the established vibration equation of the cracked rotor, the main vibration characteristics of the cracked rotor are summarized. On this basis, combined with the field diagnosis experience, a practical method of identifying the cracked rotor through vibration analysis is proposed, with criteria including continuously climbing fundamental-frequency vibration and ineffective rotor dynamic balance, continuous increase of second harmonic vibration, abnormal Bode curve, and so on. Finally, three cases of rotor crack fault identification in the operation of a steam turbine, a generator and a boiler primary air fan are given to illustrate the practical application process and accuracy of this method.

Carnot battery (CB) is an energy storage technology with the advantages of high energy storage density and low investment cost. The single-stage heat pump of basic Carnot battery have a low coefficient of performance (COP) under high energy storage density conditions, resulting in a phenomenon of high quality but low utilization of heat. In order to solve this problem, a CB using cascaded heat pump (CHP) and supercritical organic Rankine cycle (ORC) is proposed. Through modeling and analysis, the optimal combination of CHP-CB working fluids is obtained, and the effects of waste heat source temperature, high and low temperature heat storage tank temperature, CHP intermediate temperature on system COP, energy conversion efficiency, energy storage density (E_D) and system exergy loss are discussed. The results show that under high energy density conditions, the COP of the CHP-CB is about 23.5% and 26.9% higher than that of the basic CB when the temperature of the low-temperature storage tank is 50 ℃ and 32 ℃, respeetively. When the temperature of the low-temperature storage tank is 30 ℃, the energy conversion efficiency of the CHP-CB can reach 63.11%. The E_D can reach 13.9 kW·h/m³ when the temperature difference between the high- and low-temperature storage tank is 93 ℃, and cascade heating for the heat storage working fluid can be realized.