A quantitative evaluation method for flame image stability was proposed. First, convolutional autoencoder was used to extract features from flame images, and then quantitative evaluation index was employed for feature analysis. The quantitative evaluation index, with a numerical interval of [0, 1], was established based on cluster analysis and statistical analysis of the image feature. The convolutional autoencoder adopted a novel loss function based on reconstruction similarity to improve training efficiency. The effectiveness of the quantitative evaluation method for flame image stability was verified through experiments on the ethylene combustion platform. Results show that the convolutional autoencoder can extract image features in an unsupervised manner, and its performance is obviously superior to traditional feature learning methods. In addition, the established quantitative evaluation index can quantitatively characterize the flame image stability, showing strong generalization ability.

The development history, strengthening mechanisms, and the degradation laws of microstructural properties during service of 2%-12%Cr ferritic heat-resistant steels for boilers were reviewed. A summary was provided on five newly developed 9%-12%Cr ferritic heat-resistant steels at home and abroad, as well as their processing techniques. Combined with engineering applications, a detailed introduction was given to the reduction adjustment in creep strength and allowable stress for 9%-12%Cr ferritic heat-resistant steels in the United States, Japan, and Europe. Discussions were conducted on issues such as the low hardness of P91 steel, type IV cracking in welded joints, and oxidation corrosion. It is suggested that in-depth research should be carried out on the effects of C, N, B, and rare earth elements on the microstructural properties of heat-resistant steels. Additionally, an analysis should be conducted on the performance degradation and damage mechanism of ferritic heat-resistant steels after deep peak shaving of the unit and long-term service, providing support for unit operation, equipment safety evaluation, and the development of new materials.

To better predict the flow-accelerated corrosion (FAC) in power plant pipelines, the physical parameters of the steam-water mixture were calculated based on the gas holdup according to the actual operating conditions of the power plant pipeline. Using COMSOL software, the flow field downstream of the orifice plate in the pipeline was simulated, and the concentration of iron ions and the distribution of turbulent kinetic energy were analyzed. The variation patterns of velocity, wall shear force, and mass transfer coefficient under different flow phases were obtained. Combined with single-phase flow and two-phase flow accelerated corrosion prediction models, the impact of gas holdup on flow-accelerated corrosion was analyzed. Results show that the presence of water vapor leads to an increase in the FAC rate of two-phase flow on the upper, middle, and lower walls of the pipeline downstream of the orifice plate, compared to the FAC rate of single-phase flow, with the most significant increase occurring on the upper wall. When the temperature is 150 ℃, the medium is two-phase mixture, and the gas holdup is 0.5%, the FAC rate at the wall is the highest, being 1.001 112 times that of the single-phase flow case.

It is required by the "dual carbon" policy that the operation of power plant boilers shall develop in a more stable and efficient direction, while the thermal efficiency of boilers is an important indicator to measure the level of boiler operation. The commonly used direct and indirect balance calculation methods, as well as some soft measurement model calculations, have poor representativeness and timeliness in obtaining boiler efficiency due to the delay of coal quality test, and cannot provide accurate and effective boiler adjustment reference. Combining the direct and indirect balance calculation methods for boiler efficiency, a dynamic update method based on the iteration of the quality of the boiler's incoming coal can improve the accuracy and timeliness of the real-time calculation results of boiler efficiency. Through comparison and verification of different boiler efficiency calculation methods, the real-time calculation results of boiler efficiency based on the dynamic update iteration of the coal quality are closer to the test results of on-site boiler efficiency, compared to the ordinary real-time calculation results of boiler efficiency.

To improve energy-saving effect of steam turbine cold end system, a data-driven modeling and operation optimization method for a steam turbine cold end system was proposed. Firstly, steady-state screening was performed on the obtained historical operating data of the turbine. Then, combining mechanism analysis and machine learning algorithms to select features, a power generation prediction model for the steam turbine and a pressure prediction model of its condenser were established. Finally, the operating mode of the cold end equipment was changed and incorporated into the model for optimization. It was applied to a 630 MW unit for actual prediction and model validation. Results show that the established prediction model has good prediction accuracy, can reflect the real operating situation of the turbine in real time, and provide reference for the optimization of the cold end system operation, which is helpful to further promote the energy-saving, emission reduction, and intelligent operation of thermal power units.

Thermal calculation method was constructed to complete the performance evaluation and adaptability analysis of a 130 t/h oxygen-enriched biomass combustion grate boiler. Results show that under the air supply condition with 26.7% oxygen content, the superheater water spray rate is appropriate, the furnace combustion temperature is equivalent to the conventional air combustion condition, and the exhaust gas temperature is lower than the maximum allowable operating temperature of the dust collector. Under oxygen-enriched combustion conditions, the boiler efficiency increases by 0.7%, and the flue gas volume decreases by 25% compared with air conditions. The risk of high-temperature corrosion and ash accumulation increases, the wear risk decreases and the low temperature corrosion risk is small. The boiler shows good adaptability. The dust concentration in the flue gas increases by 33%, the SO₂ volume fraction remains basically unchanged, the NO_x volume fraction decreases, and the environmental protection system demonstrates good adaptability. The high concentration of CO₂ under oxygen-enriched combustion conditions creates favorable conditions for low-cost green carbon capture.

Accurate forecasting of photovoltaic (PV) power is essential for stable operation of new electricity systems. This study proposed a novel approach for short-term PV power forecasting combining the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), kernel principal component analysis (KPCA) and an improved carnivorous plant algorithm-long short-term memory (ICPA-LSTM) network. First, ICEEMDAN was employed to extract the implicit features of nonlinear signals from the meteorological data. Next, KPCA was performed to reduce the redundancy of the decomposed data and select model input parameters based on the contribution of principal components. Finally, the ICPA-LSTM model was constructed by improving the carnivorous plant algorithm (CPA). The approach was validated for PV power prediction under four typical weather conditions: sunny, rainy, cloudy, and variable weather. Results show that the proposed model reaches a determination coefficient (R²) of over 99% across all four weather scenarios, and achieves better performance compared to benchmark models.

Thermocline thickness and exergy efficiency were taken as evaluation indicators to conduct experimental study of thermocline heat storage tank. Influence of charging temperature difference, mass flow rate and radial plate-type diffuser structure on performances of the heat storage tank was studied. Results show that the formation and development of the thermocline are mainly affected by the mass flow rate and the diameter of the diffuser, and the influence of charging temperature difference is not significant. The initial thermocline thickness increases with the increase of Reynolds number Re and Froude number Fr. The exergy efficiency can quantitatively reflect the irreversibility of the formation and development process of the thermocline, and it shows a law of rapid rise and then keeping a relatively high level with a slow rise. Exergy destruction of the thermocline storage tank mainly occurs during the formation process of thermocline. Considering the charging duration and the exergy efficiency, the optimization parameters of the charging process are as follows: Reynolds number is 2 372 - 3 320 and Froude number is less than 0.235.

Battery energy storage systems are widely used in frequency and peak regulation of power systems due to their advantages of accurate power output, fast response speed, and two-way regulation, but their service life is still the core restriction of energy storage systems. The adaptive comprehensive frequency modulation strategy based on battery state-of-charge (SOC) feedback was adopted. The adaptive factor was determined by the input coefficient of the fuzzy controller adjustment and the feedback coefficient of energy storage battery SOC adjustment, and the input coefficient was determined by the frequency modulation output proportion coefficient (K) of virtual inertial control and virtual droop control. The simulation model was developed with the Matlab/Simulink platform, and the actual operation data of the frequency modulation battery of a power plant was used to study different control strategies. The rain-flow counting method was used to predict the service life of energy storage batteries. Results show that the battery life with the adaptive integrated frequency modulation strategy is 25.53% higher than that with the current strategy used in power plants, and the service life is increased by 38.19% and 22.42% compared with the fixed K method and variable K method, respectively.

From the perspective view of the practical engineering application, the control system called the single-tower and double-circulation wet flue gas desulfurization (SD-WFGD) system was established. Firstly, the dynamic model was developed by analyzing the impact of the unit frequency change of the absorption tower variable frequency slurry circulation pump on the flue gas SO₂ concentration at different slurry pH during the operation of the SD-WFGD system. Secondly, the direct sulfur balance control (DSC) strategy was proposed based on the desulfurization capacity of the slurry pH. The established dynamic model was then applied as a control model, and a serial control system for the SD-WFGD system was established by combining traditional PID controllers with the DSC strategy. Simulation test results demonstrated that, compared to traditional PID control schemes, the proposed optimized control scheme reduces fluctuations in slurry supply flow and outlet SO₂ concentration, significantly enhancing the control performance of the SD-WFGD system. This model can ensure the safe, stable, economical, and flexible operation of the desulfurization system in the context of flexible operation at coal-fired power stations.

To investigate the NO_x formation characteristics of ammonia-hydrogen swirl premixed flames under acoustic excitation, hydroxyl radical plannar laser induced fluorescence (OH-PLIF) imaging technology was used to analyze the flame structure at the sound frequency of 180 Hz and the pressure amplitude of 200 Pa. Flame structure and surface density distribution were obtained through image processing techniques. The effects of combustion and acoustic field pulsation coupling on NO_x emissions under different equivalence ratios (Φ) and hydrogen blending ratios (Z_f) were explored. Results show that the acoustic field can suppress the formation of NO_x in ammonia-hydrogen swirl premixed flames to some extent, with the reduction effect influenced by Φ and Z_f. The acoustic field mainly affects the combustion flow field by creating periodic pulsating flows around the flame, thus demonstrating a better NO_x reduction effect in combustion fields dominated by air momentum at low equivalence ratios (Φ≤0.8). In combustion fields dominated by fuel chemical reactions at high equivalence ratios (Φ>0.8), the effect on NO_x emissions is less significant. Under the influence of the acoustic field, the surface density of lean flames increases, and the average OH intensity decreases, as the acoustic field enhances flame combustion intensity, accelerates the combustion rate, and improves heat and mass transfer with the surrounding flow field. When the hydrogen blending ratio is low (0.20≤Z_f<0.30), the acoustic field causes the flame area to shrink, leading to a relatively higher NO_x reduction. When the hydrogen blending ratio is high (0.30≤Z_f≤0.35), the compressive effect on the flame area weakens, and the NO_x reduction effect is slightly reduced.

In response to the dual-carbon target and the hydrogen-energy-development planning and strategies, combined with solar photovoltaic-thermal (PV/T) technology and proton exchange membrane (PEM) electrolysis hydrogen production technology, a photovoltaic-thermal electrolysis hydrogen production model was proposed using PV/T power supply and preheating electrolytic water supply. The PEM electrolyzer components were established and the system model was constructed in TRNSYS software for transient analysis. Then, it was compared with a non-preheating system under the same conditions. Results show that preheating affects the temperature rise and fall of the electrolyzer and makes the electrolyzer work at a higher temperature, which improves the efficiency and increases the hydrogen production.The gain effect of preheating on the temperature, efficiency and production is more obvious under weather conditions with low electrical power or strong radiation fluctuations.The efficiency of the system's solar hydrogen production is around 12%, and the annual hydrogen production is 8 003.08 m³, which is 24.11 m³ more than that of the none preheating case, with a growth rate of 0.30%.

Proton exchange membrane (PEM) hydrogen production by electrolysis technology is an efficient and environmentally friendly method for high-purity hydrogen production, and its pressure control in this process is important for the system efficiency, life and safety. The pressure control of hydrogen production by electrolysis system was studied to enhance the anti-disturbance performance of the system. Firstly, a dynamic pressure model was established and verified by experiments. Then, various control strategies, including proportional-integral-differential (PID), loop shaping, pre-filtering, and lead-lag compensation, were utilized to design hydrogen-oxygen pressure controllers. Finally, a simulation analysis of the controllers was conducted to determine the optimal parameter configuration with good stability and dynamic response. Results show that, the optimized control strategy enables the system to stably maintain hydrogen-oxygen pressure under fluctuating power, achieving efficient and stable operation of the system. The controller shows strong anti-disturbance ability and can accurately control the hydrogen-oxygen pressure.

To address issues of new energy accommodation and hydrogen energy storage, transportation and utilization, a grid-connected wind-solar hydrogen production and ammonia synthesis system was proposed. Based on the real data of wind and solar power throughout a year, a mathematical model of the system was developed with the optimization goal of maximizing the total system revenue. The optimal equipment capacity and operation scheduling plan of the system were determined with a mixed integer linear programming algorithm. Results show that the proposed new system can switch working states reasonably and achieve energy balance according to changes in wind and solar resources and electricity prices. Under the condition of satisfying various constraints, the utilization rate of renewable energy is improved, and the levelized cost of system ammonia production is reduced.

For the energy storage plan of off grid new energy hydrogen production systems, based on the requirements of operation, the minimum energy storage scale configuration was optimized. Firstly, for off grid new energy hydrogen production systems, considering the application of Markov chain transition matrix, a new energy curve generation method was proposed based on k-Shape clustering algorithm and optimization indicators. Secondly, with the goal of maximizing the hydrogen production, a storage optimization model for off grid new energy hydrogen production systems was proposed by fully considering the new energy output curve, basic response characteristics of electrolysis tanks, and energy storage response characteristics. And then, combining the new energy curve and energy storage optimization model and and considering the operating indicators of the hydrogen production system, a production simulation method was adopted to propose an energy storage scale correction method based on continuous production simulation. Finally, a multi-year case study was conducted on an off grid hydrogen production system with 84 MW photovoltaic power, 30 MW wind power, and 14 hydrogen production devices with 1 000 m³ of per device. Results showed that the system could achieve good operational performance when equipped with 4.973 MW/4.973 MW·h energy storage, which verifying the rationality and effectiveness of this method and achieving a balance between operational requirements and economy in the process of energy storage scale configuration.

Using compact fluidized bed as calcium cycle biomass gasifier to explore the techo-economic feasibility of synergistic capture of CO₂ and hydrogen production through calcium cycle biomass gasification, thereby achieving negative carbon emissions. Models for zero carbon and negative carbon biomass gasification hydrogen production systems were established, simulation on both systems was conducted, and analysis of economic performance was conducted. Results show that the levelized cost of hydrogen (LCOH) of the compact fluidized bed gasifier is 2.78 and 2.93 $/kg under zero carbon and negative carbon emission conditions, respectively. Considering the CO₂ market price, LCOH under negative carbon emission condition can be further reduced to 2.47 $/kg. The negative carbon emission biomass hydrogen production system based on compact fluidized bed gasifier not only has lower cost, but also exhibits superior carbon emission reduction potential.

In order to solve the problem of the thermal effect of hydrogen storage in metal hydride, a two-dimensional simulation model of the hydrogen storage reactor was developed, and the influence of adding heat exchange tube bundles in the reaction dead zone on the hydrogen storage performance was studied. The optimal arrangement of the tube bundles in the dead zone of the reactor with different sizes was obtained. Results show that when 15 tubes are added in the dead zone of 45 mm radius reactor, the temperature of the metal hydride in the dead zone decreases from 339 K to 297.6-311.4 K, and the reaction fraction increases from 0.2-0.5 to above 0.89. When the reactor radius is 35, 45 and 55 mm, the optimal number of dead zone tubes is 6, 15 and 18, respectively, which results in a reduction of hydrogen storage time by 8.53%, 9.95% and 9.68% compared with that before optimization. The volume fraction of the tube bundles only increases by 0.49%, 0.74% and 0.60%, respectively, and the maximal variation in hydrogen storage time across reactors of varying sizes is less than 2.43% after optimization. Therefore, the addition of tubes can effectively eliminate the effect of the dead zone on the hydrogen storage.

In order to optimize the design of hydrogen turbo-expander based on the mean-line model, a genetic algorithm (GA) was used to obtain the design parameters under optimal performance. The effects of critical parameters such as flow coefficient, load coefficient, mass flow rate and rotational speed on the performance of hydrogen turbine expander were investigated. Results show that the efficiency of the hydrogen turbo-expander is improved by 3.08% after adopting the optimal design parameters. The variation of mass flow rate and rotational speed has significant influence on hydrogen turbo-expander efficiency. Under the optimal turbo-expander geometry, when the mass flow rate is in the range of 0 to 0.5 kg/s, the efficiency of the hydrogen turbo-expander is above 70%, which can realize efficient operation of the hydrogen turbo-expander.