To quantitatively explore axial thermal resistance distribution and radial heat transfer characteristics, experiments on axial heat transfer and steady-state radial heat transfer during startup process were conducted. Results show that the heating power has a significant impact on the axial equivalent heat transfer thermal resistance during the start-up process. As the power increases, the axial equivalent heat transfer thermal resistance first decreases and then tends to flatten out. Under low inclination angles, the axial equivalent thermal resistance significantly increases, and its impact is relatively small when the inclination angle is large. When the temperature is below 350 ℃, steam is in free molecular flow state, and the thermal resistance of the vapor-liquid interface can reach the order of 10^-4 (m²·K)/W. At higher temperatures, steam is in continuous flow state, and the thermal resistance of the vapor-liquid interface is only 10^-6~10^-5 (m²·K)/W. There may exist heat transfer thermal resistance caused by the oxide layer at the solid-liquid interface of the heat pipe, with the magnitude of 10^-4 (m²·K)/W. At low temperatures, this thermal resistance accounts for about 60% of the total radial heat transfer thermal resistance of the heat pipe, and it slightly increases with temperature. At 650 ℃, it can reach 80% of the total thermal resistance.

A loop thermosiphon with coil condenser and liquid storage tank was proposed and designed, and the start-up and internal flow heat transfer characteristics of the loop thermosiphon were studied under three liquid filling rates. Due to the strong coupling relationship between boiling and condensation processes in the loop thermosiphon, the traditional Lee model for describing phase transitions was improved, and the relationship between saturation temperature and local pressure was introduced to accurately simulate the gas-liquid phase transition and flow heat transfer process in the loop thermosiphon. Results show that the model has a good predictive effect on the heat and mass transfer processes inside the loop thermosiphon. When the loop thermosiphon operates in a quasi steady state with filling rate of 80%, the complete flow cycle can be divided into liquid overshoot, liquid drawdown, and large bubbles pushing the liquid up. As the heating power increases, the oscillation becomes more pronounced. When relying solely on the flow circulation and phase change heat transfer of the working fluid, the equivalent thermal conductivity of the loop thermosiphon can exceed 15 000 W/(m·K). At higher heat flux, the loop thermosiphon with 80% liquid filling rate forms a fast and continuously stable flow cycle, exhibiting good heat transfer performance.

Taking a coal-fired unit of a 600 ℃ ultra supercritical 650 MW power plant as the research object, combined with the overall plan of the coal-fired boiler of the 650-700 ℃ ultra supercritical power plant, the simulation study was conducted on the mixed combustion of NH₃ and coal in the boiler by replacing part of the coal with NH₃.The temperature and material distribution of NH₃ in the furnace at different mixing ratios, as well as the effects of different mixing ratios and NH₃ injection ways on NO_x emissions were explored. Results show that as the NH₃ mixing ratio increases, the flame temperature at the center of the furnace decreases significantly, the high-temperature area reduces, and the flame temperature inside the furnace shows an overall downward trend, this is mainly due to the lower theoretical flame temperature of NH₃, which prolongs the low-temperature jet and causes the delay of ignition. At the NH₃ nozzle position, the NH₃ concentration reaches its peak. As combustion progresses, NH₃ is basically consumed, and there will be no ammonia escape at the furnace outlet. Under air staged combustion, the low oxygen concentration in the main combustion zone of the furnace is conducive to the occurrence of NH₃ reduction reaction. As the NH₃ mixed fuel ratio increases, the NO_x emission concentration at the furnace outlet decreases, which results from the reduction reaction between NH₃ and NO in the furnace, inhibiting the generation of NO.When NH₃ is sprayed into the furnace in different ways, the NO_x concentration at the furnace outlet is lower when using the oil gun nozzle for injection. This is because the position of the oil gun nozzle is closer to the main combustion zone.

In order to achieve real-time monitoring of coal fed into the furnace, a coal bunker layering model was developed based on the tracking model of unique fuel feature code throughout the entire process. The coal type layering situation was roughly monitored, and the matching of moisture contents was performed based on the soft measurement results of moisture content and the coal bunker layering model. The successfully matched historical data were used as the true coal type entering the furnace, and the operating parameters such as the current and output of the coal mills were taken as feature inputs. The prediction model of the furnace feed coal based on the random forest algorithm was developed, and the erroneous parts of the coal bunker layering model were corrected by combining the model prediction results and moisture soft measurement results. Results show that test result of evaluation indicators for classification models is 0.880, which meets the engineering requirements. The proposed coal information monitoring model based on mechanism analysis and machine learning can achieve full-time identification of furnace feed coal. It lays a foundation for combustion optimization and the construction of intelligent boilers, and also realizes the closed loop of the whole-process tracking of fuel feature code.

The Jiangjunmiao coal of Zhundong high-iron coal was selected as the research object, and the effect of iron content on the ash-melting characteristics of Zhundong high-iron coal ash was investigated by changing the content of Fe₂O₃. Moreover, the evolution of minerals in the coal ash of Zhundong high-iron coal was analyzed, and the coal ash viscosity was calculated and analyzed. Results show that the formation of low melting point mineral calcium-magnesium yellow feldspar is the main reason for its lower ash melting temperature. When the Fe₂O₃ content in the Jiangjunmiao coal is 8%, the ash deformation temperature (DT) and softening temperature (ST) decrease to the lowest, which is mainly due to the generation of a large amount of iron olivine. When the Fe₂O₃ content in Jiangjunmiao coal is higher than 8%, mullite, a high melting point mineral, appears in the ash minerals, causing both DT and ST of coal ash to increase. After the temperature exceeds 1 000 ℃, the viscosity of the coal ash gradually decreases with the increase of temperature. The viscosity of coal ash with 8% Fe₂O₃ content is the first to enter the strong deposition zone of coal ash with the most serious staining and slagging. At temperature of 1 300 ℃, the viscosity of coal ash with different Fe₂O₃ contents is basically the same.

Supercritical unit superheater outlet headers operate under chronic high-temperature and high-pressure conditions, the frequent start-stops and long-time steady-state operations under high temperature lead to typical creep-fatigue damages in the header. An appropriate method should thus be selected to evaluate the damage state of the unit to ensure long-term steady operation of supercritical units. A numerical simulation based on finite element software Abaqus was carried out on the superheater header of a supercritical power generation unit. During the operation of the unit, the distribution of stress on the header was obtained, and the damage was evaluated with three different codes: ASME-III, RCC-MRx and R5, respectively. Results show good agreement in the allowable time evaluated by the ASME-III code with the maintenance life, conservative and overpredicted damage by the RCC-MRx code, and underpredicted damage by the R5 code with significantly less damage than the other codes. Therefore, the ASME-III code should be selected first as the criteria of the damage evaluation for this type of equipment, and the R5 code can be used as an alternative when the ASME-III code gives conservative results.

The high content of alkali metal and alkali earth metal (AAEM) elements in Zhundong coal is the root cause of serious fouling and slagging of boiler heating surfaces. In the combustion process of high-alkali coal, the occurrence characteristics of AAEM elements in coal and its sublimation and condensation behaviors during combustion significantly influence the fouling and slagging of coal ash on the heating surfaces in the furnace. In this paper, the existing methods for analyzing the occurrence characteristics of AAEM elements in Zhundong coal were studied, and their advantages and limitations were discussed. Based on the distribution of AAEM elements in water-soluble, ammonium acetate soluble, acid-soluble and acid-insoluble states, the occurrence characteristics of AAEM elements in Zhundong coal were reclassified, which were mainly divided into organic binding, organophilic binding and mineral combination states. The new classification method is helpful to further understand the association of AAEM elements with minerals and organic matters. However, in order to completely and accurately determine the specific existence state of organic binding AAEM elements in Zhundong coal, the current methods and techniques still have some limitations, so it is necessary to develop more accurate test methods and analysis techniques.

Aiming at unstable vibration phenomenon of No. 1 bearing of a 1 000 MW ultra-supercritical turbine unit, the relationship between main steam temperature deviation, cylinder offset, axis position and vibration fluctuation was observed by experiments. A computational steam flow force model was established to examine the steam forces under different working conditions and their influencing factors. Results show that the difference of main steam temperature on both sides of high pressure cylinder leads to uneven circumferential work in turbine stage and unbalanced steam flow force. The main steam temperature deviation will also cause the cylinder and rotor to offset, and further intensify the steam flow force. The larger the main steam temperature difference, the larger the steam flow force. The steam flow force acts upon the rotor, which changes the bearing load and causes unstable vibration. Adjusting the deviation of main steam temperature can eliminate the unit's unstable vibrations.

Compressed air energy storage (CAES)is a high-quality power source for grid regulation with strong peak-regulating capability and weak frequency-regulating capability, in order to alleviate the frequency problem caused by the large scale integration of renewable energy power generation. In this regard, power type flywheel energy storage was utilized to assist the operation of compressed air energy storage units to improve their frequency regulation capability. A simplified frequency calculation model of generating units, flywheel energy storage system, compressed air energy storage unit model and regional power grid frequency control model were given. Simulation experiments were carried out on the frequency characteristics of regional power grid composed of different flywheel capacity configuration models. Results show that the inclusion of flywheel energy storage system improves the primary frequency modulation performance of compressed air energy storage unit.

Characteristics such as intermittency and volatility of renewable energy pose challenges to grid scheduling. Liquid air energy storage system is one of the effective technical measures to solve this problem, not only in terms of large scale and long storage time, but also in terms of high energy storage density and not limited by geographical environment. Firstly, the principles of five classical air liquefaction cycle technologies were introduced, and the characteristics of different systems in terms of air liquefaction were analyzed. Secondly, the improved technologies of two air liquefaction cycles were analyzed, and comparisons were conducted on the advantages and shortcomings of different air liquefaction technologies in terms of liquefaction capacity and economy. It is concluded that Linde-Hampson cycle and Claude cycle should be adopted based on the comprehensive consideration of liquefaction rate, economic cost and safety. Finally, the problems of existing air liquefaction technologies in terms of liquefaction rate and cooling capacity gap have been analyzed, and the future development trend of air liquefaction technologies for liquid air energy storage systems has been discussed.

Non-uniform design of flow channels is one of the most important ways to improve the uneven distribution of physical fields inside proton exchange membrane fuel cells (PEMFCs). Existing design ideas mainly rely on a qualitative understanding of PEMFC to determine the design direction and further optimizing of parameters in this design direction. Feedback from the obtained results is not used to correct the design ideas. Therefore, a result feedback and then optimization design approach was proposed. In this approach, the structural parameters of PEMFC were first analyzed, and then the species transport processes in the calculation results were quantitatively analyzed to determine the structural design direction. Using the proposed approach, non-uniform designs were carried out for the channel width of single-channel PEMFC and the sub-channel height of single cell. Results show that compared to the base case, the net power density of PEMFC with non-uniform designs is increased by 4%-6%, and the uniformity of physical field distribution inside PEMFC becomes better. This study can provide guidance for the design direction of non-uniform PEMFC channel structure, and contribute to the development of high-performance and long-life PEMFC.

An improved multivariable decoupling model predictive control (IMDMPC) was proposed for coal-fired power generation units with complex dynamic characteristics such as large time delay and time-varying parameters, and strong coupling between main steam pressure and furnace negative pressure. Based on the historical operating data of the unit, dragonfly algorithm was used to optimize the partial least squares method to construct a multivariable coupled mathematical model with main steam pressure and furnace negative pressure as controlled variables, coal consumption and induced air volume as controlling variables. The multivariable dynamic decoupling algorithm was used to decouple it, and a multivariable model predictive controller was designed to obtain the current control amount according to the set objective function, simultaneously collect real-time system output values for feedback correction of the controller. Simulation experimental results show that compared with fuzzy adaptive PID control and uncoupled model predictive control, the improved multivariable decoupling model predictive control reduces the overshoot of main steam pressure and furnace negative pressure by 20.3% and 8.6%, respectively, and the adjustment time is shortened by 2.6 and 29.55 s, respectively, with better control accuracy and robustness. On-site application results show that the improved multivariable decoupling model predictive control strategy can stably control the main steam pressure and furnace negative pressure at ±0.24 MPa and ±0.27 Pa, respectively, improving the stability of system and significantly reducing the fluctuation amplitude, meeting the requirements of industrial on-site production.

Aiming at the issues concerning large inertia, significant time delay, and susceptibility to disturbances of reheated-steam temperature, a predictive control scheme was proposed to improve its control performance based on the equivalent input disturbance (EID) approach. A state observer and an EID estimator were devised to estimate an equivalent signal of a disturbance on the control input channel. Due to the phase lag caused by the time delay, the estimate cannot be used for real-time compensation. A disturbance predictor was designed to produce a prediction of the disturbance based on Taylor series theory. As a result, the prediction instead of the estimate of a disturbance was employed for the compensation on the control input channel. A new predictive scheme was proposed to obtain future information on the system state based on the plant model. A state feedback control law was designed using the future state. The control system was divided into two subsystems including disturbance attenuation and tracking control, thereby obtaining the stability criteria and design procedure. Simulation results show that the proposal can achieve the satisfactory performance of control accuracy and anti-disturbance.

Smart coal-fired power generation plays a pivotal role in facilitating flexible unit operations aimed at achieving carbon neutrality. The digital unit architecture based on cloud platforms is an essential component. However, an in-depth exploration concerning the construction of cloud platforms for the existing units is scarce. The research and practice of the critical technologies involved in the construction of big-data cloud platform for two 350 MW units were performed. A cost-effective deployment technology for cloud platforms integrating six existing servers in the plant was developed, which ensured the normal operation of units throughout the construction phase. Considering the requirements of trillions of data storage annually and data retrieval in the application scenarios of power plant, cloud platform database synchronization technology, database management and storage methodologies, and data interface services were developed. These innovations allow the cloud platform database to achieve second-level write capabilities for 10⁵-level measurement data and facilitate single-point retrieval within 3 s across an entire year's data. Based on these foundations, a large-scale optimization algorithm utilizing 2.45×10⁹ data points was implemented, offering visualized operational guidance for unit energy consumption. A preprocessing model for high-noise measurement data was established, effectively extracting trends from variables such as wind speed. Furthermore, a neural network prediction model for inlet NO_x concentration of SCR was developed by integrating a feedback adjustment mechanism that accounts for load variations to address varying demands for ammonia injections. The proposed modeling framework allows for flexible adjustment and expansion, which can be implemented on the cloud platform. The proposed technical solutions offer a reference for the construction of intelligent cloud platforms for thermal power enterprises and novel low-carbon/zero-carbon combustion systems.

The effect of reaction temperature, oxygen volume fraction, and gas residence time on the catalytic oxidation of NO/SO₂/Hg⁰ by the prepared nano TiO₂, Mn-TiO₂ and Mn-Ce-TiO₂ catalysts was studied. The oxidation mechanism of NO/SO₂/Hg⁰ by these catalysts was analyzed in low temperature plasma. Results show that the oxidation rates of NO,SO₂ and Hg⁰ are enhanced with the elevated temperature and gas residence time in the catalytic reactor. However, prolonged residence time might induce side reactions. The removal mechanism of NO/SO₂/Hg⁰ varies between the absence and presence of oxygen. Compared to TiO₂ and Mn-TiO₂, the Mn-Ce-TiO₂ catalyst exhibits superior performance in removing NO/SO₂/Hg⁰. Synergistic treatment by surface dielectric barrier discharge (SDBD) and catalysts shows greater removal efficacy of NO/SO₂/Hg⁰ compared to the individual, specifically, the combination of SDBD and Mn-Ce-TiO₂.

A capacity optimization configuration model was established for a wind-solar-diesel-storage complementary power generation system in a certain region, with the total system cost and load power deficit rate being the optimization objectives. The model was optimized using the multi-objective grey wolf optimizer (MOGWO), and the optimization results were compared with that of the multi-objective particle swarm optimizer (MOPSO). Additionally, the entropy weight-TOPSIS multi-objective decision-making method was employed to screen the optimized solution set, which was aimed at reducing the impact of subjective factors on the weight coefficients and enhancing the rationality of the optimal solution. Results show that the optimization accuracy of MOGWO surpasses that of MOPSO. In the example analysis, the optimal system configuration is 37 wind turbines, 836 solar panels, 5 diesel generators, and 531 batteries, with a total system cost of 1.169 04 million yuan.

Taking a typical thermoelectric integrated energy system as an object, an asynchronous optimal predictive control strategy considering the difference of multi-energy characteristics was proposed, which took into account the different control requirements of both thermal and electrical sides, and reduced the burden of real-time optimization calculation and ensured the coordinated control performance of the system through the reconstruction of prediction model and the switching of control targets. Results show that compared with the synchronous control optimized by electric side small step length and thermal side wide step length, the asynchronous optimal control strategy can reduce the average calculation time of the former controller by 54%, and the control deviations of residual generation power and heating water temperature by 77.1% and 88.8%, respectively.

An optimal scheduling model for a wind-solar-storage combined multi-energy complementary system based on thermal power generation was adopted and the wind and photovoltaic renewable energy generation units were used in coordination with thermal power units to meet basic urban load demands. Energy storage units were utilized to compensate for the instability of power generation of renewable energy units, and to further reduce the carbon emissions of the system, the green certificate trading-carbon trading mechanism was introduced. Under both trading schemes, a ladder pricing system was applied. The carbon emission reduction brought by the green certificate can offset part of the carbon emission, and the number of tradable green certificates participating in the green certificate market and the tradable carbon emissions participating in the carbon market were adjusted. The example aimed to maximize the comprehensive operating income of the system, while considering the operation economy and low carbon of the system. The simulation analysis of the proposed model was carried out. The result of the example proves the rationality and effectiveness of the model in terms of carbon reduction and economy.