The accurate prediction of SO₂ and NO_x emission mass concentrations can effectively guide the control of pollutants emissions, which is of great significance for the environmental protection operation of circulating fluidized bed (CFB) units. A 330 MW CFB unit is taken as the research object, and the Pearson coefficient is used to realize the screening of input variables, and the interquartile range (IQR) method is applied to screen the outliers and replace them with the normalization at the same time, to complete the data preprocessing. Subsequently, the features of input variables are extracted by convolutional neural network (CNN), and by entering into the gate-recurrent unit (GRU) the time-series features are processed. The multi-head self-attention (MHA) mechanism is introduced to capture the important relationships between features, and the model output is obtained after training. Finally, the results of the test set are evaluated using the mean absolute error (MAE), mean absolute percentage error (MAPE), and the coefficient of determination (R²). The results show that the model is able to predict the pollutants mass concentration in CFBs more accurately and achieve good prediction results, and the superior performance of the model is proved by the comparison of ablation experiments with the model. The proposed CNN-GRU-MHA model can realize the monitoring and optimization guidance of pollutants emissions CFB units, so that the power plant can adjust the operation parameters in time to ensure that the pollutants emissions meet the standards.

In order to evaluate the vibration safety of the central full partition wall of the world’s first lignite-fired 700 MW high-efficiency ultra-supercritical CFB boiler, a three-dimensional non-constant hydrodynamic model of the boiler is constructed, and the distribution of the gas-solid flow field within the furnace chamber is simulated. Furthermore, the pressure distribution and its fluctuation law of the gas-solid flow acting on the surface of the central full diaphragm wall within the furnace are solved. The vibration signals of the furnace wall of a supercritical 350 MW CFB boiler with a similar furnace structure are measured and analyzed spectrally to assess the frequency of pressure fluctuations in the furnace. The dynamic stress on the central diaphragm wall under fluctuating pressure in the furnace is calculated using the pressure fluctuations in the furnace obtained from simulation calculations and experimental tests as the excitation. The results demonstrate that the dynamic stress level of the central full diaphragm wall is below the permissible stress of the material, indicating that the central full diaphragm wall is safe.

The ignition, burnout, and slagging performance of Baoqing lignite raw coal and its dried lignite with different moisture contents was experimentally investigated using an ignition furnace and one-dimensional furnace test platform. The results show that, the ignition temperature of Baoqing raw coal is 415 ℃, which is highly prone to ignition. Compared to the influence of moisture on ignition temperature, the effect of fineness on ignition temperature is more significant. At low loads, the water and steam react with the water gas of coke in the early stages of combustion, which has a significant impact on the consumption rate of coke. Due to its high moisture content, raw coal undergoes intense reactions during the initial combustion stage, resulting in a rapid decrease in mass fraction of combustible materials in fly ash and a stronger tendency towards slagging. However, excessive moisture is not conducive to the complete combustion of coal powder in the later stage of combustion. As the fineness of coal powder R₉₀ increases, the burnout rate of coal powder decreases. But overall, the burnout rate of both Baoqing raw coal and dry coal is above 99%, indicating the Baoqing coal is highly flammable, and the effect of oxygen on burnout rate is not significant.

Circulating fluidized bed (CFB) boilers play a pivotal role in China’s power generation landscape. However, the intricate combustion system within the CFB boiler furnace exhibits strong coupling characteristics, characterized by multiple parameters, variables, nonlinearity, and time-varying dynamics, posing a significant challenge for precise system modeling and prediction. Machine learning (ML), with its robust nonlinear processing capabilities and predictive performance, holds immense promise in the domain of CFB technology. This paper delves into the application of ML techniques in this field, encompassing the prediction of minimum fluidization velocity, emissions forecasting, bed pressure forecasting, bed temperature/thermal efficiency prediction, particle circulation rate prediction, reduced-order models of computational fluid dynamics (CFD) flow fields, and boiler safety control system models. The paper critically evaluates the strengths and limitations of these technologies in various scenarios, providing an insightful perspective on the opportunities and challenges faced by CFB boilers in the era of big data. Emphasizing aspects like model interpretability, enhancing generalization capabilities, improving data quality and diversity, integrating models with conventional methods, and experimental validation are crucial areas worth attention for future advancements.

Chemical absorption using amine solution takes the dominant position for post combustion CO₂ capture of coal-fired power plants, the regeneration of amine is thermally driven, consuming large amount of steam extracted from turbine units, which results in severe power generation efficiency penalty and higher power generation cost. This limitation restricts its large-scale application in terms of both single-unit capacity and project quantity. Optimizing the heat application method in the system is an important approach to address the aforementioned issues. Focusing on the thermal energy integration utilization between the carbon capture subsystem and the power plant system, discussions and investigations are performed from the perspectives of thermal integration optimization theory and engineering energy system optimization. In terms of thermal integration optimization theory, the principles, usage methods, application results and the limitations of the exergy analysis and the pinch point analysis method in coal-fired carbon capture systems are discussed, and the suggested research interests are proposed. In the aspect of engineering energy system optimization, the beneficial effects of steam extraction parameters optimization, superheated steam utilization methods, condensate waste heat utilization methods, carbon capture and compression waste heat utilization methods, and various auxiliary machine application methods are analyzed, as well as the feasibility and economic problem of the mentioned methods during implementations. The research can provide references and ideas for further reducing system energy consumption of carbon capture of coal-fired power plants.

Direct air capture (DAC) technology, a representative negative carbon emission solution, stands as a pivotal technology for achieving carbon neutrality. However, it still confronts challenges of high costs and energy consumption. The synergistic integration of DAC with carbon utilization technologies, namely transforming captured CO₂ into high-value products, can enhance carbon reduction efficiency while lowering lifecycle costs, rendering it a critical component in the carbon neutrality roadmap. This paper systematically reviews the classification and underlying principles of DAC, summarizes recent advancements and challenges in its integration with photovoltaic, electrochemical, and thermal CO₂ conversion technologies, and concludes with an outlook on the future development and applications of deep coupled DAC and carbon utilization.

Carbon capture, utilization, and storage (CCUS) technology has made significant progress in reducing CO₂ emissions in recent years, but its large-scale application is hindered by high energy consumption and high complexity. To enhance energy utilization efficiency, integrated of carbon capture and utilization (ICCU) has emerged as a promising research focus. ICCU process enables the capture and in situ conversion of CO₂ via dual-functional materials (DFM), converting the captured CO₂ directly into economically valuable chemicals with high efficiency. Compared with the conventional CCUS technologies, ICCU significantly simplifies processes such as desorption, compression, and transportation, demonstrating substantial potential for large-scale application. This review focuses on ICCU-methanation (ICCU-Met) process, first providing a systematic introduction to the process and a thermodynamic analysis of its feasibility. Then, the DFMs used in ICCU-Met are discussed intensively, their performance is compared in terms of CO₂ capture capacity, catalytic activity, and stability. The review also critically examines the scaling-up challenges of ICCU-Met technology in practical applications, including issues such as the effects of real-world flue gas conditions, reactor design, and economic feasibility. Finally, the review summarizes the developmental bottlenecks of this process and proposes potential research directions for the future.

At present, under the guidance of the national dual-carbon target strategy, carbon capture technology is being vigorously developed and has become an important technology to promote the utilization of carbon dioxide resources and significantly reduce greenhouse gas emissions. As fossil fuel stocks gradually decrease and the prices continue to rise, the search for new environmentally friendly green fuel has become a research hotspot. By coupling renewable energy such as wind energy and photovoltaic with carbon capture, the conventional fossil energy is fully utilized and converted into downstream products with high added value, such as syngas, methane, methanol, formic acid, and so on, which can achieve large-scale low-carbon emission reduction, reduce the gap of energy and chemical raw materials, increase economic income, and drive the strong growth of green industry, and is in line with the national green environmental protection strategic plan. Based on the analysis on the research status, mainstream technology routes, main equipment and demonstration projects, the direction of further research and development of the integrated carbon capture and transformation technology is pointed out, and the prospect of its industrial application is prospected.

By taking a 150 000 tons/year carbon dioxide capture system in a power plant as the research object, a comprehensive analysis was conducted for its water usage, water consumption and water balance. Moreover, the water balance of the carbon capture system was experimentally studied and compared under different loads. The experimental results show that, the main problem in the current capture system’s water balance is that the outlet temperature at the top of the absorption tower is higher than the inlet flue gas temperature. Under high-load conditions, the reaction heat inside the absorption tower is relatively large, resulting in an excessively high exhaust steam temperature and a significant increase in system water consumption. After the outlet temperature of the absorption tower was reduced from 54 ℃ to 43 ℃, the system water consumption reduced by approximately 86.7%, demonstrating remarkable energy-saving effects. In light of this, combined with the actual operation situation, suggestions are put forward to further improve the temperature field of the absorption tower and reduce the outlet temperature of the absorption tower by adjusting the circulating water volume and enhancing the heat transfer efficiency of the lean solution cooler and the tail gas scrubber. The experimental results can provide guidance for efficient and economical operation of carbon capture systems.

The ecological, environmental, and social issues caused by greenhouse gas emissions, mainly CO₂, are receiving increasing attentions and concerns from human beings. At present, the carbon sequestration technology using flue gas from thermal power plants as CO₂ source is still in the pilot and industrial development stage, but there is no standardized methodology and accounting method for carbon reduction benefits of the carbon sequestration process. Combining the industrialization practice of the first domestic “CCUS Technology Research and Demonstration Project for Carbon Dioxide Chemical Chain Mineralization Utilization in Thermal Power Plants” constructed and operated by a power plant, the carbon emission reduction benefits of the CCUS technology pathway for chemical chain mineralization utilization were calculated and evaluated using the life cycle assessment (LCA) carbon emission factor method. The annual CO₂ processing capacity of the above demonstration project is 1 364.56 tons, which can achieve a net reduction of 708.12 tons of CO₂, reaching a net emission reduction rate of 52%. By scaling up the annual processing capacity of demonstration project to 100 000 tons, the net reduction rate of CO₂ emission in the project can be increased to 76%. The research method has broad prospects for carbon reduction applications and can provide technical support for China to achieve carbon neutrality goals.