Latest ArticlesThis study aims to investigate the applicable conditions and key operational parameters for an integrated compression, purification, decarbonization, and denitrification process applied to natural gas oxy-fuel combustion flue gas. The research seeks to clarify the technical feasibility and performance boundaries of this process for achieving efficient carbon dioxide (CO2) capture coupled with deep removal of nitrogen oxides (NOx), providing a practical solution for integrated carbon capture and pollutant control in natural gas oxy-fuel combustion systems.
A steady-state process model for the compression and purification of oxy-fuel combustion flue gas was developed using Aspen Plus, which accurately describes the thermodynamic behavior of the high-pressure, multi-component gas mixture. Through systematic simulation and parametric sensitivity analysis, the study focused on the combined effects of the initial CO2 volume fraction in the flue gas and the system operating pressure on process performance. Key performance indicators evaluated include the CO2 recovery rate, liquid CO2 product purity, NOx removal efficiency, and specific comprehensive power consumption.
The simulation results establish a definitive and strong correlation between the CO2 recovery efficiency and the initial concentration of CO2 in the flue gas. A clear technical threshold is identified: to attain a CO2 recovery rate of 80% or higher, the initial CO2 volume fraction must exceed 60%. This finding defines a primary applicability criterion for the compression-purification approach. Subsequent analysis concentrated on flue gas compositions meeting this high-concentration criterion (>60% CO2). Within this domain, the system operating pressure emerges as the most influential parameter governing the synergistic relationship between NOx abatement and CO2 purification efficiency. Detailed parametric optimization reveals a distinct optimal operating pressure of 2.8 MPa. Operating at this pressure enables the process to achieve superior performance across all key metrics: the NOx removal efficiency surpasses 94%, the purified liquid CO2 product attains a purity of 95% or higher, and the target CO2 recovery rate of ≥80% is reliably maintained. Crucially, this operating point corresponds precisely to the minimum in specific power consumption, which is quantified at 120.1 kW·h per ton of CO2 captured. This represents an optimal trade-off, balancing high environmental performance with minimized energy penalty, a critical factor for economic feasibility.
The compression and purification technology is suitable for treating oxy-fuel combustion flue gas with a high initial CO2 volume fraction (>60%). By optimizing the system pressure to 2.8 MPa, efficient CO2 capture and deep NOx removal can be achieved simultaneously with low energy consumption. This study clarifies the key performance thresholds and optimal operating parameters for this integrated process, providing a concrete and feasible technical solution for achieving pollution reduction, carbon mitigation, and resource utilization in natural gas oxy-fuel combustion systems.
Accurate modeling of main-steam temperature is the foundation for studying its control strategy. To address the contradiction between mechanism completeness and model practicality of the conventional modeling methods, a hybrid modeling method for main steam temperature integrating mechanism model and system identification was proposed. A mechanistic model of main steam temperature was established based on the lumped parameter method. The model includes the effects of flue gas heat transfer, steam flow rate and desuperheating water flow rate. According to the closed-loop operation data of a thermal power plant boiler, the model parameters were identified using differential evolution algorithm. Compared with the boiler design values, the identification results show an increase in thermal resistance of ash layer and a decrease in convective heat transfer coefficient of flue gas, which conforms to physical laws. The model was then verified using operational data from different time periods. The results indicate that the mean absolute error between the calculated results and the operational data is less than 1 ℃, which proves the accuracy of the model. By utilizing the model, the dynamic characteristics of the main-steam temperature were further analyzed, and several improved control strategies were proposed, such as increasing the feedforward signals of the coal feeding rate and the attemperator inlet steam temperature, and adopting a load-based fuzzy controller. The simulation results show that the deviation of the main-steam temperature is reduced, which proves the established model has guidance effect on optimizing the main-steam temperature control system.
Driven by the large-scale integration of renewable energy and the national “dual-carbon” strategic goals, the construction of a new power system imposes higher requirements on the flexible operation of coal-fired units. However, coal-fired units face challenges such as reduced combustion instability and steam parameters deviating from design values during low-load operation. Therefore, in-depth research on coordinated control characteristics of low-load stable combustion and flue gas temperature in boilers is of significant importance for deep and flexible peak regulation. Taking a 600 MW subcritical tangentially fired boiler in a power plant as the object, the effects of injecting primary air exhaust gas from the pulverized coal conveying system into different locations of the furnace (main combustion zone, reduction zone, burnout zone) on the velocity, temperature and component concentration field, and the flue gas temperature at the platen zone are systematically studied under 50% load condition. The analysis specifically focuses on the synergistic influence mechanism of combustion organization on the combustion stability of the boiler and the regulation of flue gas temperature. The results indicate that injecting primary air exhaust gas into various furnace locations can form a stable tangential flow pattern and high-temperature zone, without significantly affecting the boiler’s low-load combustion stability. Injecting the primary air exhaust gas into the reduction zone elevates the high-temperature flame region to some extent, which is beneficial for maintaining steam parameters during deep flexible peak regulation, yielding superior coordinated performance for both low-load stable combustion and flue gas temperature regulation. Through numerical analysis, the coordinated control strategy for achieving stable combustion at low loads and regulating flue gas temperature through the reuse of primary air exhaust gas is determined. The study results can provide a basis for the low-load operation of this type of coal-fired boiler during deep peak shaving.
Steam ejector technology integrated into combined heat and power systems enables effective thermal-electric decoupling and deep load following, with ejector performance directly influencing overall efficiency and operational stability. A one-dimensional thermodynamic design model for high-temperature and high-pressure steam ejectors is developed by incorporating the development characteristics of the compressible mixing layer. The concept of compressible mixing layer thickness is introduced based on the entrainment mechanism to determine the radial dimensions of the ejector. Numerical simulations are performed to evaluate ejector performance and flow field characteristics, which guide the optimization of axial dimensions. The optimal structural parameters are identified as a nozzle-to-mixing chamber distance of 6 mm, a mixing chamber length of 42 mm, and a diffuser angle of 4.4°. An experimental system is constructed to validate the proposed design method, and the results show an average relative error of 6.6% between the predicted and measured entrainment ratios, demonstrating the model’s accuracy. The results provide a theoretical foundation for the structural design of high-temperature and high-pressure steam ejectors and hold significant potential for practical engineering applications.
As the working medium of turbine speed-control systems in power plants, phosphate ester fire-resistant fluid (FRF) plays a vital role in the normal operation of steam turbines. During operation, the deterioration of FRF may result in an increase in acid value, a decrease in volume resistivity, and the formation of oil sludge, and the degree of decomposition and deterioration varies among different oils. The chemical composition of different kinds of FRF samples was analyzed, the deterioration process of different phosphate ester molecules was simulated, and their aging-resistance properties were tested. The results show that the performance of FRF with tris-(dimethylphenyl) phosphate as the main component is more stable than that of FRF with tert-butylphenyl phosphate as the main component. During the production of FRF, the content of dimethylphenyl in triaryl phosphate should be increased, and the content of phenyl and tert-butyl phenyl should be reduced.
As an emerging high-moisture solid waste treatment method, smoldering disposal technology shows unique advantages in the disposal of high-moisture and low-calorific sludge. However, its self-sustaining propagation process is easily affected by material characteristics and operating parameters, and there is a risk of propagation instability caused by the attenuation of reaction intensity. Taking high-moisture sludge (moisture content >65%) as the disposal object, this study systematically investigates the effects of the mixing ratio of quartz sand to sludge (2:1~5:1) and air Darcy velocities (5~8 cm/s) on smoldering propagation under biomass conditioning, and explores the boundary of biomass conditioning ratio for complete smoldering propagation. The results show that under the condition of a fixed Darcy flow rate of 5 cm/s, the critical biomass conditioning ratio linearly increases from 4% to 10% and the critical unit calorific value of the smoldering system remains stable at approximately 0.339 MJ/kg when the sand-sludge mixing ratio is increased from 2:1 to 5:1. When the sand-sludge mixing ratio is fixed at 3:1, the critical biomass conditioning ratio linearly decreases from 6% to 2% when the air Darcy velocity increases from 5 cm/s to 8 cm/s, corresponding to a linear decrease in critical unit calorific value from 0.339 MJ/kg to 0.172 MJ/kg. The material exhibits collapse characteristics after smoldering disposal, and the biomass conditioning ratio has no significant effect on the top collapse height when it exceeds the critical value. These results can provide reliable scientific references for solving the efficient smoldering disposal of high-moisture sludge.
Traditional biomass resources are rarely adopted by coal-fired power plants due to their seasonal availability and regional dispersion. A novel Arundo donax L. variety, characterized by high yield and robust adaptability to marginal lands such as tidal flats and coastal wetlands, offers a viable solution to these challenges. In this study, based on a 2×1 000 MW ultra-supercritical pressure once-through boiler, co-firing experiments of this novel Arundo donax L. were carried out, and its effects on thermal system, powder making system, and combustion characteristics of thermal power units were analyzed. The results show that the thermal power plant unit operation is stable after adding 15% Arundo donax L. particles. However, the stone coal discharge increases, the coal mill current is elevated by about 5%~10%, the maximum elevation of the coal mill inlet and outlet differential pressure is elevated by 10%~15%, the combustion intensity in the furnace decreases slightly. The low grindability index of Arundo donax L. is the key factor affecting the operation of the unit, and the study concludes that the torrefaction interval of about 250~300 ℃ is the best interval to improve the grindability index of Arundo donax L.
Biomass fuel is a renewable and clean energy source that can replace fossil fuels and reduce carbon emissions. However, during storage and transportation, microbial metabolism in biomass can cause self-heating, which, through the “chimney effect”, accelerates air circulation and promotes aerobic reactions, potentially leading to thermal runaway and fires. Given that biomass typically has rod-like and flake-like shapes, conventional porous media gas flow resistance models are poorly adapted for assessing these processes. In this study, a testing platform for the gas flow resistance characteristics of biomass porous media was established. Gas flow resistance tests were conducted on rice straws and soybean shells at different bulk densities. The parameters of the conventional Ergun model and the modified Ergun model were optimized. The results show that the resistance experienced by gas flowing through biomass porous media significantly increases with bulk density and gas velocity, exhibiting a pronounced upward parabolic relationship. As the load applied to the biomass increases from 50 kg/m2 to 2 800 kg/m2, its bulk density can increase by approximately two times. Ignoring the changes in bulk density and porosity caused by stacking height in biomass self-heating numerical simulations can lead to prediction deviations. Both the Ergun model and the modified Ergun model can be used to evaluate the gas flow resistance of typical flake-like or rod-like biomass. The modified Ergun model, with fewer parameters and direct calculation based on bulk density, significantly enhances engineering applicability.
Coal-fired power generation coupled with biomass is one of the efficient carbon-reduction technologies for coal-fired units. As a typical energy plant, arundo donax has the characteristics of high yield, strong environmental adaptability and high calorific value, and can be used for large-scale coal-fired power generation. To investigate the effect of co-firing arundo donax in a pulverized-coal boiler on NOx emissions and explore the migration pathways of fuel nitrogen during the co-combustion of coal and arundo donax, a co-combustion reaction model of arundo donax and coal was established with a two-stage plug flow reactor (PFR). The formation characteristics and reaction mechanisms of nitrogen oxides during co-combustion of the arundo donax and coal in a pulverized-coal boiler were studied, focusing on exploring the influences of co-firing ratio, over-fire air (OFA) ratio, and OFA position on the formation characteristics of nitrogen oxides. The results show that the NOx emission can be reduced by co-firing arundo donax, and the mass concentration of NOx decreases with the increase in co-firing ratio of arundo donax. The NOx conversion rate and NOx mass concentration first decrease and then increase with the increase in over-fire air ratio, and there is an optimal over-fire air ratio (around 33%) to minimize NOx emissions. Delaying the position of the OFA leads to a decrease in both the NOx conversion rate and NOx mass concentration. By studying the NOx formation characteristics and the nitrogen migration pathways during co-combustion of coal and arundo donax, theoretical guidance can be provided for parameter setting and reducing exhaust NOx emissions in the co-combustion of arundo donax for coal-fired power generation.
The existing alkaline electrolysis hydrogen production technology primarily focuses on performance testing of electrolyzers and optimization of flow fields in electrolysis cells, and little attention is paid to overall description of the hydrogen production system as well as the mechanism modeling and simulation of key equipment. To solve this problem, using gPROMS process simulation software and referencing chemical process simulation methods, a distributed parameter model based on mechanism analysis was established for a 200 m³/h (standard condition) alkaline water electrolysis hydrogen production system. The key equipment of the system was finely modeled and simulated. By comparing the simulation results with experimental data, the results show that the simulated values of the main performance parameters of the system have good consistency with the measured data. The calculated average error is less than 5%, which verifies the effectiveness of the model. The established model can describe and predict the changes in system parameters, providing methods and support for subsequent system design, optimization, and control.