The porous media methodology is used to describe the filter bags and their surface ash layer seepage flow. On this basis, the discrete particle model (DPM), as implemented in Fluent software, is employed to simulate the dynamics of dust particles movement and deposition in a baghouse filter. The effects of dust particle size on evolving morphology of the cake on the filter bags are investigated, and the influence of additional resistance of the filter cake on subsequent ash particle deposition is explored. The results show that, when the duration of dust removal is sufficiently long, the cake thickness and pressure loss in the baghouse filter increase in a linear fashion over time. For a constant dust mass flow rate, the pressure loss becomes higher with smaller dust particles. The smaller ash particles are transported more effectively by the upward airflow to the top of the vertical filter bag, whereas the larger particles, due to their weight, tend to settle in the middle area. This results in significant differences in the distribution of cake thickness. In contrast to conventional algorithms that neglect cake resistance, the proposed model, which incorporates this resistance through advanced development in commercial software, predicts a more uniform distribution of dust thickness, which is more consistent with the actual situations. This conclusion can provide references for improving the operational efficiency of baghouse filters.

In order to study the effect of molten salt thermal storage schemes on peak shaving capacity and economy of double reheat condensing units, by taking a 660 MW double reheat condensing unit as an example, seven bypass thermal storage schemes are designed by combing thermal storage with bypass system, considering different thermal storage sources. Through simulation, the changes in indicators of different schemes, such as the minimum power generation load rate, thermal storage load reduction number, compensation for increased peak shaving capacity and coal consumption costs, are studied in the heat storage initial range from 30%THA to 50%THA. The results show that, the minimum power generation load rate of the schemes with multiple parallel heat storage sources are lower than that of the schemes using a single heat source. Scheme VII with three parallel heat storage sources can reduce the minimum power generation load rate to below 18% under different initial heat storage conditions. However, in the Scheme I with superheated steam heat storage, the load reduction number of heat storage exceeds 2.00, and the load reduction capacity per unit of heat storage power is the largest. As the load rate of the initial heat storage condition decreases, there is a maximum compensation for the annual increase in peak shaving capacity, and the compensation for multiple thermal storage heat source schemes is greater than that for a single heat source scheme. The annual increase in coal consumption cost of the scheme including low-pressure bypass heat storage is much higher than other schemes, but it will decrease with the initial working condition of heat storage.

To solve the problem of severe ash accumulation and slagging on heating surface of boilers caused by a large proportion of blended economic coal, based on the close relationship between the ash fouling layer and the flue gas flow field parameters, the concept of cross-sectional “ash fouling characteristic field” is proposed, and a new intelligent soot blowing control system for boilers is developed, which includes functions such as characteristic field detection and generation, and benchmark field prediction. By comparing the difference in “drop value” and “concentration” between the benchmark feature field and the current feature field, the system can timely and accurately determine the appropriate blowing time, achieving “intelligent perception and on-demand blowing”. The new system solves the problem of lack of measurement points and low accuracy in existing model calculation methods, overcomes the disadvantage of high equipment cost in furnace observation methods, and uses on-site full section data collectors combined with intelligent prediction models for ash pollution characteristic fields to achieve low-cost and high-precision detection of ash and slag accumulation, effectively solving the problems of over blowing and under blowing. The actual application effect of the power plant shows that, after the new system was put into use for 3 months, the monthly blowing frequency decreased by 19.6%, and the monthly blowing steam consumption decreased by 229.0 tons, which is equivalent to a direct economic benefit of 284 000 yuan per year. In addition, the system also brings multiple indirect benefits, such as avoiding sudden coking that causes the unit to stop, extending the service life of the heating surface, and avoiding delayed soot blowing that leads to a decrease in boiler efficiency. The relevant control optimization experience can be used as a reference for similar units in the future.

In order to realize cascade utilization of energy in the heating system, in view of the problem that the heat load of industrial users does not completely match the heat consumption for activated carbon regeneration, the steam-air heater has been installed in flue gas desulpherization and denitration demonstration unit for No.2 coal-fired generation unit in a thermal power plant. Steam becomes primary heat source to realize activated carbon regeneration. Steam extracted from the turbine heats circulating hot air in the FGD unit firstly, then supplies remaining heat energy to different terminals outside the plant after desuperheating. Hereby this article thoroughly describes how to select control valve in steam supply system, so as to realize coupling control of heat energy between two different users. The rationality of this design has been verified during actual operation of the demonstration project, and it provides a reference for the selection of control valves in future engineering practices.

The power generation by co-firing of coal and biomass is the most economical and efficient technology for existing coal-fired power plants to achieve CO₂ emission reduction and large-scale efficient utilization of biomass. However, due to the significant alkali metal content in biomass, serious issues such as ash deposits, slagging, and corrosion arise during co-firing of coal and biomass, posing substantial threats to safe and economically viable operation of boiler equipment. Comparative analysis on slagging characteristics of heating surfaces in coal-fired boilers, biomass-fired boilers, and co-firing boilers of coal and biomass are conducted, with their influencing factors investigated. The slagging characteristic evaluating indicators for boilers firing different fuels and co-firing boilers are comprehensively discussed and evaluated. Furthermore, the applicability of these slagging evaluation indicators in specific boiler equipment is assessed. A comprehensive analysis reveals that the ash components in the fuel determine the physical and chemical properties of ash residues. The ash fusion characteristics reflect the tendency and temperature of solid-liquid transformation of ash residues, whereas ash viscosity relates to ash flowability and its propensity to deposit as slag on heating surfaces. A comprehensive consideration of these aspects enables a more accurate evaluation of boiler heating surface slagging characteristics.

The experimental data and simulation studies on ammonia co-combustion in coal-fired power plants in recent years are investigated, with a focus on the effect of ammonia fuel on NO_x generation. Through experimental observation, numerical simulation, and theoretical analysis, the spatial distribution of soot and polycyclic aromatic hydrocarbons (PAHs) during combustion is directly observed using high-speed cameras, laser-induced ignition (LII) method, and laser-induced fluorescence (PAH-LIF) method. It finds out that, the generation of NO_x during ammonia combustion is significantly higher than that of the conventional hydrocarbon fuels. Reasonable design of ammonia nozzles and selection of appropriate injection positions can significantly reduce the NO_x generation. The ammonia blending combustion technology provides a promising approach for achieving low-carbon transformation of coal-fired power plants. Although there are still challenges in the industrial application of large-scale ammonia blending combustion technology, the application prospects of ammonia fuel in coal-fired power plants are broad through continuous experimentation and technological optimization. Future research should continue to focus on the generation and emission of other pollutants during the process of ammonia combustion, and explore in depth the transformation behavior of minerals in coal in the combustion environment, providing theoretical and practical support for the industrialization of ammonia combustion technology.

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.

The rapid and comprehensive determination of coal quality is of great significance for the optimization of boiler combustion and the digital transformation of coal-fired power plants. Laser-induced breakdown spectroscopy (LIBS) has the potential to be applied effectively in the rapid determination of coal quality. In order to meet the application goal of rapid coal inspection, 46 sets of spectral data of coal samples from different power plants were collected by the experimental device of coal particle flow LIBS, and the research of simultaneous rapid inspection of multiple indicators of coal quality by combining LIBS with machine learning was carried out systematically. In view of the considerable spectral fluctuations observed in the particle flow state, the number of single-pulse acquisitions was optimized. In addition, invalid spectral screening, spectral averaging and spectral normalization data preprocessing methods were established. Furthermore, four machine learning algorithms (PLSR, SVR, PSO-SVR, and LSTM) and four spectral feature inputs (full spectra, eigenbands, intensity integration, and PCA extraction) were compared in terms of their performance in predicting multiple indicators of coal quality. The results demonstrate that the uncertainty of the spectral signals can be maintained at a maximum of 5% when 200 single-pulse spectra are collected for spectral averaging in a single test. The PSO-SVR algorithm exhibits the most optimal prediction performance in the quantitative analysis of coal quality indicators, and the PCA algorithm reduces the dimensionality of the spectral data, which reduces the amount of model computation and at the same time improves the prediction performance of the model, and the model established by combining both of them has the best performance, the root mean square error (RMSEP) of the coal heat content is 0.289 MJ/kg, and the mean absolute error (MAE) is 0.231 MJ/kg. The coal carbon mass fraction, ash content and volatile matter content are also predicted satisfactorily, with the RMSEP of 0.987%, 1.310% and 1.612%, and the MAE of 0.839%, 1.014%, and 1.033%, respectively. The results show that, combined with appropriate machine learning algorithms, the LIBS technique can achieve simultaneous accurate and rapid determination of multiple indicators of coal quality, which has a broad application prospect in the scenario of efficient and clean coal utilization.

To achieve simulation validation for the control software and hardware platform of a gas turbine control system, the co-simulation method based on real-time and virtual environments is studied. A real-time simulation hardware platform is built using a real-time simulator, signal conditioning devices, and fault injection devices. Additionally, a detailed simulation model of the gas turbine and fuel system is developed based on multi-domain physical modeling methods, taking into account dynamic factors such as thermal soak effects, volume effects, and rotational inertia. A virtual simulation environment is constructed using a virtual controller for the control system, and logic modeling methods are used to create simulation models for auxiliary systems such as the lubrication and electrical systems. Signal interaction between the real-time simulation platform, virtual simulation platform, and control system hardware platform is achieved through hardwiring and communication methods, enabling integrated co-simulation operation. The results show that, the co-simulation method, combining real-time and virtual environments, not only provides a lightweight simulation environment for the gas turbine control software, encompassing all critical link elements, but also allows for functional and performance testing of the control logic. Moreover, it offers a validation environment for the control system hardware platform under various gas turbine operating conditions, enabling functional and performance testing of the hardware in multiple operational scenarios. This research can be applied for integrated validation of both software and hardware in gas turbine control systems, supporting the development of domestic gas turbine control systems and the retrofitting of control systems in existing units for domestic applications.

At present, foreign brands almost occupy the entire fan lubrication market share, and domestic oil products lack opportunities to enter the market. To demonstrate the feasibility of domestic substitution of lubricating oil for wind turbine gearboxes, the testing and analysis database for domestic gearbox lubricating oil and foreign competitors is established by adopting laboratory analysis to test the physical and chemical performance indicators (including kinematic viscosity, viscosity index, flash point, pour point, moisture, acid value, demulsibility, foam characteristics, liquid phase corrosion, and copper corrosion), tribological performance indicators (sucn as maximum seizure free load, sintering load, friction coefficient, wear spot diameter, comprehensive wear), and other lubricating oil performance indicators (like antioxidant performance, ferrography, infrared spectroscopy, and PQ index). The comprehensive performance of domestic gearbox lubricating oil products is systematically evaluated, and the feasibility study of domestic substitution of wind turbine lubricating oil is completed. The results indicate that there is not much difference in the basic performance indicators between domestic brand fan gearbox lubricating oil products and imported brands, and the substitution is feasible.