To tackle the challenges associated with the poor combustion performance of ammonia fuels and the high NO_x emissions in exhaust gases, experimental research on enhancing ammonia combustion through the use of a swirling burner combined with a gliding arc plasma generator was carried out. The effects of various combustion enhancement methods, including methane-assisted combustion, plasma-assisted combustion, and plasma-coupled methane-assisted combustion, on the combustion characteristics of NH₃ swirling flames and the generation of NO were investigated. The experimental results indicated that, compared with the methane-assisted combustion, both plasma-coupled methane-assisted combustion and plasma-assisted combustion significantly enhanced the stability of ammonia combustion. This improvement was evidenced by a substantial expansion of the stable combustion limit range of the NH₃ swirling flame, enabling normal combustion within an NH₃/Air equivalence ratio range of 0~5.0. In comparison to single methane-assisted or plasma-assisted combustion, plasma-coupled methane-assisted combustion (with a plasma power of 0.8 kW and a methane flow rate of 1 L/min) significantly enhanced the active species H_α and OH generated by the discharge, thereby strengthening the chemical effects in plasma-assisted combustion. Under these conditions, the NO emission mass concentration in the exhaust gases rapidly decreased from over 7 000 mg/m³ to approximately 100 mg/m³ as the NH₃/Air equivalence ratio was increased from 0.6 to 0.8. Furthermore, the gas temperature under these conditions was only slightly lower than that observed in pure plasma-assisted combustion, where the flame temperature of ammonia combustion could reach up to approximately 2 030 K.

Under the “dual-carbon” target, ammonia as a zero carbon fuel is expected to become a substitute for fossil fuels. Focusing on the problems of slow combustion speed, high ignition energy, and significant ignition delay in ammonia combustion, the effects of initial temperature, pressure, and oxygen volume fraction on ammonia combustion characteristics are studied via Chemkin simulation, based on the different ammonia combustion chemical reaction kinetics mechanisms of Shrestha, Mei, Mei-2021, Stagni, CEU-NH₃, Gotama, and Glarborg. The results show that, as the initial temperature increases, the propagation speed of ammonia laminar flame increases, and the ignition delay time decreases, which is beneficial for ammonia ignition and combustion. The increase in pressure reduces the propagation speed of laminar flames, but significantly shortens the ignition delay time. The increase in pressure is beneficial for ignition but not conducive to flame propagation. As the volume fraction of O2 increases, the laminar flame propagation speed increases and the peak shifts towards lean combustion. Sensitivity analysis reveals that the branching ratios of H+O₂=O+OH, H₂+NO=NNH+OH, and NH₂+NO=H₂O+N₂ have a positive promoting effect on flame propagation, while that of NH₂+O=HNO+H inhibits flame propagation. The reactions H+O₂(+M)=HO₂(+M), NH₃=H+NH₂, HNO=H+NO, and NH₂+HO₂=NH₃+O₂ exhibit high sensitivity at high pressures. The sensitivity coefficients of the reactions between HNO and N_iH_i is relatively high during lean burn combustion. H₂NO is an important intermediate component that affects the ignition delay time at high pressures and low temperatures. By optimizing the conditions of ammonia combustion and regulating key reaction pathways and reaction kinetics, the characteristics of ammonia combustion can be improved.

The effect of co-firing hydrogen/ammonia on nitrogen oxides emissions from boilers is investigated. The reaction kinetics file is modified based on coal quality analysis and experimental results. A psr reactor network based on CFD simulation results is constructed according to the fluid dynamics (CFD) simulation results. Combing with the chemical reaction kinetics analysis method, the NO_x emissions after burning hydrogen/ ammonia at four positions of primary air, peripheral air, secondary air and post secondary air in five schemes are analyzed. The results show that, for the researched boiler, when the hydrogen co-firing position is located in the secondary air scheme, and the hydrogen mixing ratio is 20%, the NO emission reduces by 32.4%, and the emission concentration of unburned carbon does not change much compared to the pure coal condition. When the ammonia co-firing position is located behind the secondary air, the NO emission mass concentration is slightly higher than that under the pure coal condition, and the emission mass concentration of unburned carbon reduces significantly. The above two schemes are recommended for co-firing hydrogen/ammonia in the coal-fired boiler, with nitrogen oxide emissions as the evaluation index. This method and conclusion provides a theoretical basis for the engineering implementation of hydrogen/ammonia co-firing technology.

A simulation study on a 300 MW tangentially-fired boiler with 20% ammonia doping at 60% load was carried out to analyze the combustion process of ammonia doping in pulverized coal boiler, and to seek for the best coal-ammonia co-combustion scheme to ensure the optimal combustion efficiency and the lowest pollutant emission. By adjusting the position of ammonia burners and the ratio of the separated over fire air, the temperature field of the flue gas in the furnace, the molar fraction distribution of the combustion components, as well as the combustion characteristics and the NO_x emission level at the furnace outlet were systematically analyzed using numerical simulation. The comprehensive analysis shows that, the best coal-ammonia co-combustion solution is to place the ammonia burner on top layer (tertiary air) and the CD layer (secondary air) when the ratio of the separated over fire air is 33.5%. This scheme ensures the combustion efficiency and stability while controlling the NO_x emission level comparable to that of the pure coal-fired condition, which provides a new way of thinking for large-scale coal-fired power plants to realize clean and efficient combustion.

Ammonia synthesize through hydrogen produced by green electricity offers an effective solution to the widespread abandonment of wind and solar resources and the shortage of green fuel chemicals. A wind-solar-driven proton exchange membrane (PEM) electrolyzer system in dual-mode operation for hydrogen production and hot standby with integrated ammonia synthesis waste heat storage is proposed, addressing issues of frequent start-stop cycles under fluctuating wind-solar outputs and waste heat recovery in ammonia synthesis processes. The results indicate that, the PEM electrolyzer dual-mode operating system, integrated with ammonia synthesis waste heat storage, can significantly shorten the startup time of the electrolyzer. The startup time at 25 ℃ is 512 seconds, while the hot startup from the standby mode at 47.5 ℃ requires only 274 seconds. Under hot standby mode, the system consumes electricity solely from feedwater pumps, achieving a specific hydrogen production power consumption of only 0.49 kW. The dual-tank thermal storage subsystem is configured with 10.8 tons of Dowtherm-G heat transfer oil. In heat storage mode, it absorbs waste heat gas from the ammonia synthesis unit at a flow rate of 3 kg/s, allowing the thermal tank to reach full capacity within 1 hour. In heat release mode, it heats the electrolyzer inlet water at a flow rate of 0.64 kg/s, enabling the electrolyzer to sustain standby operation for 4.68 hours. Furthermore, the new system is expected to generate long-term benefits that consistently exceed costs, ensuring sustained economic viability.

Aiming at the difficulties in renewable energy consumption and the demand for low-carbon development in the integrated energy system, an optimal scheduling method considering the joint operation of hydrogen-doped gas-fired units with hydrogen-doped and ammonia-doped coal-fired units is proposed. Firstly, to account for the uncertainty and correlation of wind and solar power outputs, a joint wind-solar output modeling approach based on the Frank Copula function is adopted. Typical wind-solar scenarios are generated through marginal distribution fitting using kernel density estimation, Monte Carlo sampling, and K-means clustering, thereby enhancing the robustness of the scheduling model. Meanwhile, energy conversion models for power-to-hydrogen and hydrogen-to-ammonia processes are developed to enable the efficient transformation of renewable energy into hydrogen and ammonia. Secondly, the refined operation model of hydrogen-doped combustion of gas-fired units and ammonia-doped combustion of coal-fired units is constructed in response to the demand for low-carbon transformation of conventional fossil energy units, so as to optimize the synergistic utilization of hydrogen and ammonia fuels in the power generation process. Then, the optimal dispatching model is constructed by combining with the laddering-type carbon trading mechanism with the goal of minimizing the total operation cost of the system, which is to minimize the total cost of the system. Moreover, the optimal scheduling model is constructed with the objective of minimizing the total operating cost of the system in combination with the stepped carbon trading mechanism and solved by the CPLEX solver. Finally, different scenarios are set up and comparative analysis are carried out. The results indicate that, the introduction of hydrogen-to-ammonia conversion, building upon hydrogen energy utilization, significantly mitigates wind and solar power curtailment within the system. The combined operation of hydrogen-doped gas-fired unit and ammonia-doped coal-fired unit leads to concurrent reductions in both total operational costs and carbon emissions. The study provides a reference for the development of decarbonization of integrated energy systems.

The industrial production and urban residents’ lives have led to a large amount of wastewater and sludge, and the landfilling of sludge has caused severe ecological damage. To facilitate the large-scale disposal of municipal sludge, transform waste into valuable resources, and prepare low-carbon, low-cost thermal storage materials, an idea is innovatively proposed, in which the silicon carbide, boron nitride, and expanded graphite is added as thermal conductivity enhancers to enhance the thermal conductivity of sludge incineration ash/potassium nitrate composite phase change thermal storage materials (50% sludge incineration ash+50% potassium nitrate). The composite phase change thermal storage materials were prepared, and the effects of thermal conductivity enhancers on thermal performance of these materials were investigated. The results indicate that, the expanded graphite is not suitable as a thermal conductivity enhancer for sludge incineration ash/potassium nitrate composite phase change thermal storage materials. The addition of a thermal conductivity enhancer with a mass fraction of 2% is optimal for improving melting latent heat, with boron nitride performing better than silicon carbide. The samples with 2% boron nitride shows the most significant increase in thermal conductivity, rising by 65%, 93%, 117%, and 203% compared with samples SC3 (without thermal conductivity enhancers) at temperatures of 100 ℃ to 400 ℃, respectively. After undergoing 1 000 cycles of heating/cooling, the samples with 2% boron nitride have a latent heat of 35.29 J/g and a thermal storage density of 292.1 J/g, while the samples with 2% silicon carbide have a latent heat of 40.90 J/g and a thermal storage density of 334.9 J/g. The heat transfer rates for the samples with 2% silicon carbide and 2% boron nitride are 0.16 ℃/s and 0.17 ℃/s, respectively. This preliminary evidence demonstrates the feasibility of using silicon carbide and boron nitride as thermal conductivity enhancers for sludge incineration ash/potassium nitrate composite phase change thermal storage materials.

With the increasing proportion of new energy connected to the grid, the issue of frequency safety in the power system and mastering the regulation ability of the units have become more important. At present, in power system simulation, thermal power unit models suitable for electromechanical transient and medium-long term dynamics mainly adopt the simplified model of drum boilers and the single reheater turbine model recommended by IEEE. If a similar model is also used for the once-through boiler unit, the simulation results of the main steam pressure will deviate significantly from the actual situation due to the dynamic of thermal storage coefficient and the deviation of control system, which leads to a misjudgement of the unit’s regulation ability. By using thermodynamic modeling methods, a supercritical once-through boiler unit model suitable for multi-time scale dynamic simulation is proposed. By establishing a moving boundary model of the water wall and a dynamic heat flow model of the superheater, the heat storage capacity of the once-through boiler can be reflected more accurately. By incorporating feedwater control and superheat control, the control system is more in line with the actual unit. The high simulation accuracy of the model is verified using power plant operation data. Compared with the existing power simulation models, the simulation accuracy of the main steam pressure has been improved significantly. Therefore, the model can describe the dynamics of supercritical once-through boiler units more accurately in primary and secondary frequency regulation and peak shaving, which is helpful for simulating the frequency process of power systems.

Based on the computational particle fluid dynamics (CPFD) numerical simulation method, the study takes the 660 MW supercritical circulating fluidized bed (CFB) boiler in Pingshuo, Shanxi as the research object. A full-loop model of the furnace is established and numerically simulated. On the basis of the parameters of the actual furnace, the material distribution characteristics of six cyclone separators are investigated. By altering the ratio of primary to secondary air, the uniformity of primary air, and the uniformity of secondary air, the effect of operational parameter changes on the gas-solid flow field within the furnace and the material distribution at the cyclone separator inlets is analyzed. The results indicate that the distribution characteristics of particles within the furnace lead to a distribution feature of particle mass flow rate at the cyclone separator inlets, which is “high on both sides and low in the middle”. When the total air volume is constant, a larger ratio of primary to secondary air can reduce the deviation in particle mass flow rate at the cyclone separator inlets. The uniformity of air distribution for both primary and secondary air in the furnace also affects the particle mass flow rate distribution at the cyclone separator inlets. The deviations in particle mass flow rate at the inlets of the six cyclone separators reach their minimum when the wind speed deviation at the middle air distribution plate is 10% and the deviation in the middle secondary air volume is 5%, respectively.

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.