China has abundant high-alkali coal resources. This article provides a comprehensive review and summary of the research and engineering application progress of high-alkali coal combustion technology from the aspects of basic research, key technologies, and engineering practice. In particular, the latest status of the mechanism research and practice of fully burning Xinjiang high-alkali coal in a wet-bottom boiler is introduced. The review aims at providing a reference to develop more economic combustion technology that can safely co-fire a high proportion or even solely burn Xinjiang high-alkali coals in a long operational period.

Although the reserves of high-alkali coal represented by Zhundong coal is huge, the problem of coking on heating surface of the boiler is prominent during co-firing high-alkali coals in thermal power units, which not only reduces the boiler thermal efficiency, but also seriously threatens the safe, stable and economic operation of the unit. In order to solve this problem and promote the utilization of high-alkali coal, this paper reviews the researches on coking of the heating surface of high-alkali coal boilers and the prevention. Up to now, extensive researches have been carried out at home and abroad on the characteristics of coking on the heating surface of coal-fired boilers, coking mechanism, influencing factors, prevention and control measures, and so on, and fruitful research results have been achieved. On the basis of controlling the quality of coal, improving boiler structure, and optimizing boiler operation, the preparation of coating on the heating surface of boilers has also become an important technical path for preventing and controlling coking. In the future, the coating should possess excellent comprehensive properties such as high temperature resistance, corrosion resistance, wear resistance, thermal conductivity, thermal fatigue and so on, while having outstanding coking resistance. Meanwhile, the coating also should have desirable preparation economy and preparation efficiency, especially the on-site applicability.

High-alkali coal such as Zhundong coal has huge reserves in Xinjiang, in which rich alkali metal elements can easily lead to fouling and slagging problem on heating surface of the furnace, thus to decrease the safety of boiler. It is of great significance to develop efficient and clean combustion power generation technology for high-alkali coal to achieve the “double-carbon” goal. The research progress of the online monitoring technology in high-alkali coal combustion furnace based on spontaneous emission radiation analysis is summarized. The development trend and dynamics are discussed focusing on the research status and application of emission spectrum technology and spontaneous emission radiation imaging and image processing technology in high-alkali coal combustion monitoring. Emission spectroscopy can obtain the temperature and component concentration by processing the spectral radiation signal emitted by the flame at different wavelengths. Recently, it has been widely used to measure the combustion temperature and the gaseous alkali metal concentration in the industrial furnace and judge the slagging trend in the furnace qualitatively. Different from emission spectroscopy technology, spontaneous emission radiation imaging and image processing technology has the ability to analyze the spatial distribution of signals. The technology obtains the spontaneous radiation image in the furnace via CCD, CMOS and other surface array sensors. Based on image processing technology and thermal radiation imaging theory, the temperature distribution of the combustion field in three-dimensional space can be obtained combining with solving radiation inverse problem, which makes it possible to monitor the three-dimensional visual of slagging formation. In the future, monitoring of the fouling and slagging on the heating surface in two or three dimensions should be carried out based on emission spectroscopy technology, spontaneous emission radiation imaging and image processing technology. Combined with the distribution of parameters such as combustion temperature and gaseous alkali metal concentration in the furnace, a quantitative judgmental index of fouling and slagging on the heating surface of high-alkali coal combustion should be established to achieve the goal of online prediction of fouling and slagging on the heating surface.

Further research on slag-tap boiler can promote the application of fully burning high-alkali coal technology. In this study, a supercritical 350 MW once-through double-U flame slag-tap boiler is taken as the research object and the combustion chamber, slag collection tube bundle and cooling chamber are taken as the calculation units, the thermal calculation is performed from the perspective of heat balance. The flow field, temperature field and component field in the boiler under design condition and at variable loads are studied. The deviations of several flue gas temperature results obtained by thermal calculation and numerical simulation are within 40 K. At the outlet of the combustion chamber, the deviation is only 1.2 K. The temperature deviation of flue gas at the outlet of cooling chamber is 15.6 K. After verification and comparison, it is concluded that the thermal calculation method adopted can be applied to the thermal calculation on double-U flame slag-tap boiler that fully burning high-alkali coal. The flow field is well organized. The recirculation zones formed by swirling flow can increase the movement path of pulverized coal particles in the combustion chamber and promote the burning. When the flue gas flows through the slag collection tube bundle, the temperature greatly reduces. The flow field is also disturbed, which can effectively capture the ash. At variable loads, the velocity field in the boiler decreases proportionally according to the reduction ratio of the amount of coal. However, the size of the recirculation zones is basically unchanged. The temperature level in the boiler reduces, when the amount of coal reduces from 100% to 75%, the flue gas temperature at the outlet of the combustion chamber reduces by about 75 K, and the flue gas temperature at the outlet of the cooling chamber reduces by about 200 K. This study can provide reference for fully burning high-alkali coal in double-U flame slag-tap boiler.

In order to compare the particle formation characteristics of typical high-alkali and high-chlorine Xinjiang coal under combustion conditions, a three-stage high temperature drop tube furnace was used to carry out the combustion experiment of Zhundong coal (ZD) and Shaerhu coal (SEH) in air atmosphere. The characteristics of particulate matter after combustion were analyzed. Particulate matters were collected by Dekati low pressure impactor+ (DLPI+) and the mass-based particle size distribution, elemental compositions and morphology were discussed. The results showed that the particulate matter produced by the combustion of the two coal samples presents a double-peaked model. The fine particle yield of SEH is significantly higher than that of ZD. The main components of sub-micron particles were Na and Cl. The Cl in PM₁₀ accounts for 11.8% and 28.9% of the Cl content in ZD and SEH raw coal, and Na accounts for 2.66% and 7.53% of the Na content in ZD and SEH coal ash. High levels of alkali metals and Cl promoted the formation of fine particles. A large amount of Cl in SEH raw coal migrated into particles and contributed greatly to the formation of sub-micron particles.

As a kind of slag-tap boiler, cyclone-fired boilers exhibit significantly different aerodynamics comparing with pulverized coal (PC) boilers. However, by far there are still lack of CFD models that are able to provide effective guidance to the design and operation of cyclone-fired boilers. A CFD model of cyclone-fired boilers was developed in which the capture of coal particles by the molten slag layer was considered through a slag layer coal particle capture model. This model was then employed to investigate the aerodynamics and flue gas recirculation (FGR) optimization design of a 550 MW cyclone-fired boiler. The results demonstrate the highly nonuniform characteristics of furnace aerodynamics of cyclone-fired boilers due to the strong swirling flows created by the cyclones leads to the formation of localized high temperature zones and severe boiler fouling problems at the entrance of boiler convection pass. Thus, it is critical to adapt the FGR design with the nonuniform furnace flow and temperature distributions. The simulation results show that, with the optimized FGR design, the high temperature zones and the resulting severe fouling problems were effectively mitigated.

In order to understand the key parameters and operating experience on fully burning and high proportion blend burning high-alkali coal in boiler with slag-tap furnace, long-term engineering tests were conducted based on a 300 MW boiler with slag-tap furnace in a power plant. An analysis was conducted on the possible combustion organization, nitrogen oxide control, slag flow, and ash deposition issues. Modifications were made to the combustion system, thermal modification system, and slag flow system. So long-term operational data and key parameter records were conducted, after fully burning and high proportion blending burning of 300 000 tons of high-alkali coal, all operating parameters of the boiler were normal. Based on recent operations and comprehensive tests, the optimized boiler with slag-tap furnace in a specific power plant demonstrates strong adaptability to high-alkali coal. Within the control range of coal ash components with w(Al₂O₃)<25%, w(Fe₂O₃)<15%, 12%<w(CaO)<30%, silica-alumina ratio>1.7, acid/alkali ratio>0.5, the normal operation of the boiler can be ensured without obvious ash deposition. Burning high-alkali coal can effectively reduce the inlet flue gas temperature of the first-level heating surface to below the design value, effectively avoiding the occurrence of slagging on the first-level heating surface of the boiler, and the generation of nitrogen oxides is also reduced by more than 30% compared with using the original design coal.

Xinjiang high-alkali coal is a cost-effective power coal，but when it is used in large proportions, boiler equipment is prone to severe slagging problems. The design principles of the combustion system for boilers using Zhundong coal are inconsistent with conventional technical measures to improve low-load stable combustion performance. To solve this problem, based on the mechanism of stable combustion of pulverized coal, measures such as optimized layout of tiny oil ignition burners, interlaced arrangement of middle layer burners, online adjustable coal powder concentration and burner design optimization have been studied. The technology was applied in a 350 MW unit's deep peak regulation retrofit project using Zhundong high-alkali coal as fuel, and achieved a stable combustion load of less than 18% rated condition without oil injection.

In order to study release characteristics of sodium during thermal conversion of high-alkali coals, the release characteristics of sodium in high-sodium coal and low-sodium coal were compared and analyzed through combustion experiments and pyrolysis experiments of raw coal and water-washed coal, so as to explore the release law changes of different forms of sodium in coal samples during combustion and the influence of atmosphere changes on sodium release. The results show that, during the combustion experiment, the release of sodium from high-alkali coal increases slowly at 300~500 ℃ and rapidly at 500~1 100 ℃, and the release of sodium from low-alkali coal increases rapidly at 300~500 ℃ and slowly at 500~1 100 ℃. It can be seen that, coal quality is one of the main reasons affecting sodium release, and sodium release will be greatly affected by the difference in coal composition. The release law of sodium during combustion and pyrolysis is basically the same, the sodium release rate changes slowly during the pyrolysis process, and is about 7.0% lower than that of the combustion process. The release characteristics of organic sodium and water-soluble sodium are different due to different release routes.

In order to reduce fuel procurement costs and ensure fuel supply, a certain power plant in Gansu burns a large proportion of Xinjiang high-alkali Guanghui coal and Xinjiang Energy coal. After burning the high-alkali coal, the boiler experiences severe high-temperature corrosion and coking on the heating surface, and the maximum load can only be carried to 85% ECR. In order to reduce high-temperature corrosion, research has been conducted on coal quality characteristics, combustion optimization adjustment, and equipment improvement technology for boilers. The research results show that, the boiler still experiences severe high-temperature corrosion even when burning low sulfur coal, which is mainly related to the high content of alkali metals such as sodium and calcium, as well as chlorine in Xinjiang coal. By increasing oxygen content, reducing primary air volume, weakening the swirling strength of outer secondary air of the burner, and increasing wall-attached air, operation adjustment measures can improve the high-temperature corrosion characteristics of the water wall to some extent. But to completely solve this problem, it is necessary to start with the use of additives, high-temperature corrosion prevention spraying, adding soot blowers, improving wall-attached air and burner design, and other corresponding technologies. The results of this study can provide useful reference and guidance for power plants that encounter similar problems during the process of high-alkali coal burning.

With the continuous increase of installed capacity of new energy generation in power grid, thermal power units have to undertake more peak shaving. However, the flexibility and peak shaving capacity of current thermal power units are generally insufficient. A subcritical 300 MW coal-fired unit is retrofitted for molten salt energy storage. Six heat storage strategies and two heat release strategies are proposed and investigated. The influence of heat storage and release process on the peak shaving capacity and thermal performance of the unit under three working conditions is analyzed, the technical and economic analysis is performed in terms of the net present value. The results show the feasibility of extracting reheated steam for heat storage is higher, with a peak shaving depth of 58.9%. However, the coal consumption would increase at the same time. During the releasing heat stage, the maximum increment of power generation up to 11.3% of the rated power generation is achieved by heating the water supply to generate steam, while the higher temperature of the molten salt is required. Using high-temperature molten salt instead of low-pressure heater to preheat water supply is proved to have more advantages, while the power generation increment is relatively small. During the whole process of heat storage and release, the maximum circulating electricity efficiency can reach 0.987. The economic analysis of heat storage transformation is conducted. The dynamic investment payback period is 11.65 years, and the net present value is 49.118 million yuan. Therefore, the renovation scheme is feasible.

As a large number of new energy is connected to the grid, the participation of supercritical thermal power units in peak regulation tends to cause the superheat of intermediate points to fluctuate greatly, resulting in superheated steam over temperature and other problems. In order to better control the intermediate point superheat to achieve stability, a prediction method of intermediate point superheat based on double-depth input convex neural network multi-model (muti-DDICNN model) was proposed. Sub-models with different prediction step sizes were trained respectively, and the intermediate point superheat state prediction network (SPNN) and error prediction network (EPNN) were constructed. Based on the convex property of prediction network, a multi-model predictive controller (DDICNN-MPC) based on convex neural network with double-depth input is designed. The control problem is transformed into a convex optimization problem, the Jacobian matrix of control matrix to objective function is obtained, and the optimal solution of control matrix is calculated by gradient descent method. The simulation results show that, the DDICNN-MPC can track the intermediate point superheat setting quickly and stably, and the steady-state error is small, so it has good adjustment ability.

As a fundamental component of the organic Rankine cycle (ORC), the scroll expander's operating characteristics critically influence the ORC's overall performance. Initially, we establish a three-dimensional transient simulation model of the scroll expander. This allows us to systematically analyze the effects of various operating conditions on aspects such as suction pressure, exhaust pressure, rotational speed, and the output power and isentropic efficiency of the scroll expander, using numerical simulation. Following this, we study the effect of different operating conditions on the transient performance and mechanical properties of the scroll expander, and achieve a more comprehensive understanding of the mechanisms involved. Ultimately, we verify the accuracy of our numerical model using a laboratory-built test bench of the ORC low-temperature waste heat oil-free power generation system. The close correlation between the experimental results and numerical simulation outcomes authenticates the reliability and applicability of our numerical simulation method. In conclusion, this research's findings offer significant referential value for the design and optimization of the scroll expander.

To improve the flexibility of coal-fired units, boilers need to have good controllability and the ability to adapt to rapid load changes. The flexibility of the boiler is closely related to the performance of the control system, which is designed according to the dynamic characteristics of boilers. To study the dynamic characteristics of boilers, a dynamic model of a supercritical 660 MW coal-fired boiler is built in the Dymola platform. The results show that the response time of steam temperature is longer than that of steam flow. When the feedwater temperature, feedwater flow, and fuel quantity are stepped increase by 5%, the main steam temperature changes by 10.2 ℃, –28.5 ℃, and 35.7 ℃, respectively. In the process of adjusting the water-fuel ratio of the boiler, different times of change in feedwater and fuel flow can have different effects on the main steam temperature. The maximum deviation of the main steam temperature during the transient process reduces by 27.4 ℃ when the feedwater flow is delayed by approximately 100 s compared with the fuel flow. When the load change amplitude is the same, the larger the load change rate, the more severe the fluctuation of the main steam parameters, and the longer it takes to stabilize.

In order to further investigate the loss mechanism in supercritical carbon dioxide turbines, the flow characteristics in a turbine stage were studied by numerical method. The losses in the passage of stator and rotor blades were decomposed, and the various loss values and their proportions were quantitatively calculated. The loss sequence of the supercritical carbon dioxide turbine stage was clarified. The results show that, the high density of supercritical carbon dioxide and low blade height result in a very large leakage loss in turbine stage. When the stage load coefficient is 0.93, the relative height of the stator clearance is 0.012 and the relative height of the rotor clearance is 0.010, the leakage loss accounts for 38.23% of the total loss, including 21.94% of the diaphragm seal leakage loss and 16.29% of the tip seal leakage loss. Except for leakage loss, when the average maximum thickness divided by chord length is 0.33 and the aspect ratio is 2.07 in stator passage, the profile loss is much higher than the endwall loss and trailing edge loss, accounting for 9.68% of the total loss. In rotor passage, when the average maximum thickness divided by chord length is 0.28 and the aspect ratio is 1.73, the difference among endwall loss, profile loss, and trailing edge loss is not significant, and the profile loss has the highest proportion, accounting for 15.39% of the total loss. The influence range of secondary flow in rotor is even wider, and its endwall loss is much higher than that of the stator. The main sources of endwall loss are viscous dissipation of fluid near the end wall and secondary loss caused by horseshoe vortices, passage vortices, etc. The research results will provide direction guidance and data support for the design and optimization of supercritical carbon dioxide turbines.

To enhance the whole process safety of fan operations and ensure accurate fault diagnosis and long-term production income of thermal power plants, predicting these risk issues is crucial to enhance the safety of the unit. In this paper, we proposed a fan fault diagnosis model of big data platform that integrates multilayer perceptron and polynomial fitting. The fan early warning model was established by multilayer perceptron and polynomial fitting modeling technology, and integrated into the big data platform to find abnormalities which were difficult to find manually during the operation of the fan. By combining data mining with mechanism analysis and feature value knowledge base, the parameters boundary information of fan stall could be excavated, the stall boundary conditions of the fan were accurately configured under various working conditions, and a stall boundary condition diagram was created. By combining those informations with normal operating conditions, the early stall zone can be obtained. Finally, a fault diagnosis model that covers the entire working condition of the fan can be established. Utilizing the comprehensive big data platform that covers, circulates, and maintains fan operation data, a system of intelligent fan patrol model was constructed. The intelligent patrol disk model which replaces the operator was then used to monitor and diagnose the fan running state regularly, which can achieve accurate and safe diagnosis of fan faults, minimize the fault incidence and maximize the personnel reuse rate.

In order to solve the problems of high error and low classification accuracy in the fault diagnosis process of wind turbines caused by the high dimension, feature redundancy and feature correlation of wind turbine supervisory control and data acquisition (SCADA) data, a three-stage feature selection method based on LightGBM-VIF-MIC-SFS is proposed. Firstly, based on the importance calculation of all features implemented by LightGBM, a preliminary feature space is determined. Secondly, a correlation discriminant matrix is constructed based on the variance inflation factor (VIF) and maximum information coefficient (MIC) to evaluate features with similar importance in a single screening, and discard input features with high similarity. Finally, the sequential forward search method is used to process the features for the third time, input the features obtained from the previous two feature selection one by one, and retain the features that can improve the system performance, so as to achieve the final feature selection. After the establishment of the model, the real SCADA data of the wind farm is used for performance evaluation, and the proposed algorithm is compared with the two comparison algorithms on six data sets. The results show that LightGBM-VIF-MIC-SFS has significant advantages over the two comparison feature selection algorithms. A ablation experiment was conducted on the three modules within the proposed algorithm, effectively verifying the effectiveness of each module within the proposed feature selection method and the rationality and accuracy of the optimal feature space obtained based on the proposed method.

FMEA is an effective reliability analysis method for identifying potential failure modes in a system and evaluating their criticality. Conventional FMEA has many shortcomings such as not considering the weights of different risk factors, RPN being very sensitive to changes in risk factors, difficulty in handling expert subjective scoring information, and not considering the propagation and impact relationships between failure modes. Aiming at these shortcomings, an improved FMEA method was proposed by introducing house of reliability, rough set theory and VIKOR method to improve the accuracy and objectivity of risk priority analysis of failure modes. Compared with the conventional FMEA, the improved FMEA can not only effectively deal with the various subjectivities and uncertainties in the risk assessment process but also rank the risk of the identified failure modes with taking into account the effects of failure propagation, which is able to rank the risk priority of failure modes in the case of attribute conflict and various uncertainties. Based on the proposed FMEA, a real-word application of risk priority ranking of the failure modes in wind turbine was carried out and the risk priority order of each failure mode and each subsystem were obtained. According to the ranking results, the weak links and key subsystems of the reliability of wind turbine were identified, and the hazard weight of each failure mode and subsystem was given, which can provide data support for the reliability optimization design of wind turbine.

In order to explore the effects of mixed coal combustion on reducing the carbon content of fly ash in a subcritical 600 MW natural circulation balanced draft boiler, three types of coal with significant differences in characteristics were used, and numerical simulations were combined with experiments to study the mechanism of mixed coal combustion and its relationship with fuel characteristics, burnout rate, and carbon content in fly ash in the stratified combustion process of the balance boiler. Based on the results, a set of coal blending principles are proposed to improve the combustion characteristics of coal powder in power station boilers. Firstly, three extreme operating conditions were set up, and high-quality coal was respectively focused on the upper, middle, and lower layers of the burner for combustion. And then, through computational fluid dynamics (CFD) simulations, it was found that when the coal powder airflow of the balance combustion boiler flowed upward, and the high-quality coal was distributed in the upper layer of the combustion chamber while the poor-quality coal was distributed in the lower layer, the residence time of poor-quality coal in the furnace increased significantly, allowing it to fully combust in the high-temperature area of the upper layer, resulting in a low carbon content in fly ash. Furthermore, based on the analysis of the heat value, volatile matter and ash content of coal powder in different combustion layers under various working conditions, it was found that the difference in heat value and ash content is the main factor influencing combustion characteristics. Based on the actual operating conditions of the coal-fired power plant, a more realistic set of coal blending scenarios was established, and numerical simulations and on-site experiments were conducted, which showed that the overall combustion characteristics of coal powder under each working condition followed the aforementioned rules, and the carbon content in the fly ash reduced compared with the original operating conditions. Finally, the coal blending principles were established, which take into full consideration of the actual operating conditions of the power plant, recommend high-quality coal with low ash content to be used in the upper and middle layers of the combustion chamber while poor-quality coal with high ash content should be used in the middle and lower layers of combustion burner.

Thermal power units are faced with a variety of ways to sell electric heating products, such as electricity contract market, spot market electricity sales, auxiliary service market electricity sales, civil heating and industrial heating. It is necessary to optimize the distribution of limited thermal power unit electric heating products in various markets according to the market trading mechanism, operating costs and carbon emission cost to obtain maximum profits. The intelligent decision-making system can help thermal power units to provide the optimal group and bidding strategy at all levels of the market, business accounting and the optimal operation mode of units.

An improved grey wolf optimizer (MGWO) is used to optimize BiLSTM to predict water wall temperature. The improved algorithm adopts nonlinear factor adjustment strategy, adaptive position update strategy and dynamic weight modification strategy to improve the global optimization ability of the GWO. The improved grey wolf optimizer is used to optimize the number of hidden layers, learning rate and regularization parameters of the BiLSTM model to improve the prediction accuracy of the model. The data of a power plant in Xinjiang are used for prediction simulation. The results show that, the improved optimizer has higher prediction accuracy, and can predict the change trend of wall temperature when the unit is lifting and lowering load. Compared with the LSTM and BiLSTM models, the average root mean square error of the model reduces by 9.86% and 3.69%, respectively, and the overtemperature of water wall temperature can be predicted in advance, which is of great significance for the prevention of overtemperature of water wall.