In order to further investigate the loss mechanism in supercritical carbon dioxide turbines, the flow characteristics in a turbine stage were studied by numerical method. The losses in the passage of stator and rotor blades were decomposed, and the various loss values and their proportions were quantitatively calculated. The loss sequence of the supercritical carbon dioxide turbine stage was clarified. The results show that, the high density of supercritical carbon dioxide and low blade height result in a very large leakage loss in turbine stage. When the stage load coefficient is 0.93, the relative height of the stator clearance is 0.012 and the relative height of the rotor clearance is 0.010, the leakage loss accounts for 38.23% of the total loss, including 21.94% of the diaphragm seal leakage loss and 16.29% of the tip seal leakage loss. Except for leakage loss, when the average maximum thickness divided by chord length is 0.33 and the aspect ratio is 2.07 in stator passage, the profile loss is much higher than the endwall loss and trailing edge loss, accounting for 9.68% of the total loss. In rotor passage, when the average maximum thickness divided by chord length is 0.28 and the aspect ratio is 1.73, the difference among endwall loss, profile loss, and trailing edge loss is not significant, and the profile loss has the highest proportion, accounting for 15.39% of the total loss. The influence range of secondary flow in rotor is even wider, and its endwall loss is much higher than that of the stator. The main sources of endwall loss are viscous dissipation of fluid near the end wall and secondary loss caused by horseshoe vortices, passage vortices, etc. The research results will provide direction guidance and data support for the design and optimization of supercritical carbon dioxide turbines.

As a large number of new energy is connected to the grid, the participation of supercritical thermal power units in peak regulation tends to cause the superheat of intermediate points to fluctuate greatly, resulting in superheated steam over temperature and other problems. In order to better control the intermediate point superheat to achieve stability, a prediction method of intermediate point superheat based on double-depth input convex neural network multi-model (muti-DDICNN model) was proposed. Sub-models with different prediction step sizes were trained respectively, and the intermediate point superheat state prediction network (SPNN) and error prediction network (EPNN) were constructed. Based on the convex property of prediction network, a multi-model predictive controller (DDICNN-MPC) based on convex neural network with double-depth input is designed. The control problem is transformed into a convex optimization problem, the Jacobian matrix of control matrix to objective function is obtained, and the optimal solution of control matrix is calculated by gradient descent method. The simulation results show that, the DDICNN-MPC can track the intermediate point superheat setting quickly and stably, and the steady-state error is small, so it has good adjustment ability.

The CO₂ capture process using ionic liquids (ILs) in the coal-fired power plant is simulated, in which the physical properties of ILs and ILs-CO₂ phase equilibria are modelled based on experimental data. Analysis shows that the increase of packed height and absorption pressure is beneficial for CO₂ absorption, while the inlet temperature has the dual effect as it influences both the ILs viscosity and CO₂ solubility. The optimum condition is determined with 20 m packed height, 4 MPa absorption pressure and 50 ℃ inlet temperature. The regeneration process is more energy efficient with pressure swing method, in which the pressure of ILs-CO₂ stream is reduced to 0.1 MPa with almost no ILs loss. Energy consumption and cost analysis shows that the multistage compressor is the most energy-intensive unit, and the absorption pressure has the largest effect on the system with 4 MPa the optimum parameter. With the optimum condition, the energy consumption of the process is 2.21 GJ/t, which is more energy-efficient than the conventional carbon capture system using monoethanolamine.

It is necessary to break the technical barrier and make breakthroughs in information system, control system, device and other aspects when reforming large thermal power excitation system domestically. The article first systematically concludes and summarizes the key technologies of modern excitation technology, including control and command subsystems, communication subsystems, rectifier subsystems, and excitation subsystems. It analyzes and summarizes the research status, existing problems, and difficulties involved in each technology at home and abroad. Secondly, the localization and replacement process of the HN-i6200 excitation system for large-scale supercritical 670 MW thermal power units was described. Targeted design was carried out to meet the special requirements of the excitation system operation for thermal power units, and highly reliable domestic DC breakers were developed. Through experimental research, the operation strategy of the excitation system for thermal power units was overcome, and a nationally produced HN-i6200 excitation system was successfully developed. The on-site testing and system modeling have verified the working performance of the nationwide production excitation system, providing technical and practical references for the localization of excitation technology in the power industry.

To establish an accurate and effective dynamic model of cogeneration units, a modeling method based on digital twin technology is proposed using unit operation data. Firstly, the historical data stored in the unit data server is extracted, it is then clustered using the improved genetic simulated annealing fuzzy C-means method to establish a historical data clustering library. Then, during the operation of the unit, real-time operational data is collected and transmitted, and a multi-level similarity recognition strategy is used to retrieve the historical data closest to real-time operational data in the historical data clustering library. Then, based on the optimization, the extreme learning machine will use the searched historical data for unit modeling. Finally, a twin model of a cogeneration unit in Hangzhou is established and comparative experiments are conducted. The results show that, the built model meets the accuracy requirements and can track the real-time state response of the unit. The model accuracy can be further optimized by flexibly changing the parameter settings during the modeling process.

A regional integrated energy system based on solar, geothermal and natural gas is constructed to meet the multi-load demands of buildings, electric vehicles and hydrogen fuel vehicles. Hydrogen storage tank and heat storage tank are used to adjust the system flexibility, and to achieve systematic low-carbon economic operation on the basis of meeting the energy demand. Taking the residential community as an example, the distinctions of travel behavior for new energy vehicles on weekday and weekend are investigated, the change of travel frequency with different seasons are also considered, and the yearly loads of residential and new energy vehicles are determined. Primary energy saving rate, CO₂ emission reduction ratio and total annual expenditure reduction ratio of the proposed system are set as optimization objectives, and the capacity configuration of integrated system is optimized based on the mixed integer linear programming so as to evaluate the system performances from the aspects of economy, energy and environment. The results show that, primary energy saving rate, CO₂ emission reduction ratio, total annual expenditure reduction ratio and total investment income of the optimized system are 42.95%, 55.89%, 50.82% and 49.18%. In the integrated system, the input power of public grid only accounts for 16.93% of the total power load. This study provides theoretical basis for the integration of novel energy supply system considering coupling loads of residential building and new energy vehicles, which is helpful to promote the application of integrated energy system in building and transportation areas.

In order to explore the formation and evolution of soot during the combustion of coal, this paper uses Pingdingshan coal as combustion material, and uses the light scattering method coupled with the thermophoretic sampling article diagnostic method to measure the soot mass in flame. A light scattering measurement system capable of precise vertical movement is constructed to measure the light scattering intensity at different heights of the flame. The particle size distribution is obtained by the thermophoretic sampling particle diagnostic method, and the soot mass at different heights when the flame is calculated by Mie scattering theory. The results show that as the flame rises, the median mass diameter of soot firstly increases and then decreases. When the flame burns stably, a large amount of soot is formed at a height of H=10 mm. As the flame rises, the mass of soot decreases rapidly in the H=10~30 mm range. In the range of 10~20 mm, the soot mass of Pingdingshan coal decreases by 58.62%. When H>40 mm, the soot mass of Pingdingshan coal slowly decreases.

In order to improve thermal efficiency of the solar cavity particle receiver, this paper designs the quartz spiral tube solar cavity particle receiver with quartz spiral tube, and establishes flow model to conduct comparative analysis on the structural parameters of the receiver. Finally, the cone angle of the cavity is set to 5°, the number of spiral turns is set to 5, and quartz window is adopted. In order to analyze the heat transfer characteristics of this receiver, this paper studied the influence of different incident radiation intensities and particle mass flow on it. The results show that, within the range of incident radiation intensity of 100 000 W/m² to 350 000 W/m² and particle mass flow of 0.002 kg/s to 0.051 kg/s, the highest particle temperature at the outlet is 672 ℃, and the highest efficiency of the receiver is 70.12%. The research has reference significance for the design of high-temperature solar particle receivers.

In order to understand the performance changes and potential risks of hydrogen assisted combustion in combustion chamber of a lean-combustion premixed gas turbine, a numerical simulation study of the hydrogen injection combustion process of natural gas was carried out in the combustion chamber of Siemens SGT-800 gas turbine. The fuel ignition, temperature distribution, flame formation and NO_x emission characteristics of the combustion chamber under five working conditions of 0, 5%, 10%, 15% and 30% were investigated. Studies have shown that hydrogen-doped combustion in the current combustion chamber will lead to an earlier ignition position of the fuel, an increase in temperature peaks, a shorter axial length of the flame, and a gradual convergence of the outer duty flame towards the central mixer. The temperature distribution and flame morphology in the combustion chamber will not change significantly when the hydrogen-doped ratio is below 15%, but the ignition position in the mixer tube is seriously retracted at 30% hydrogen-doped ratio, and the flame on the outside is close to the nozzle outlet, which has a risk of tempering. In addition, the NO_x emission value of the combustion chamber outlet increases with the hydrogen doping ratio, and the NO_x emission value exceeds the standard by nearly 1/3 at 30% hydrogen doping ratio, indicating that high NO_x emission is also one of the factors restricting the high proportion of hydrogen doping in gas turbines.

Under the strategic goal of “carbon peaking and carbon neutrality”, the penetration rate of new energy sources is increasing, and coal power is gradually transforming into a flexibly adjustable power supply. While the flexible operation of coal-fired generating units will lead to energy efficiency losses and additional pollutant emissions, which have a certain degree of impact on the cost of power generation and are not conducive to the further exploitation of coal power flexibility resources. In this paper, a method for grading the flexible operating performance of coal-fired units is constructed. By calculating the performance indicators to assess the flexibility performance of coal-fired units under specific operating conditions, the relationship between the unit coal consumption rate and the generation of some air pollutants that affect the cost of power generation and the operational flexibility is investigated. Meanwhile, the kilowatt-hour cost of coal-fired power plants at the second level is estimated. Finally, second-scale operating data collected from a 330 MW unit are used to evaluate the impact of coal-fired unit flexibility on the cost of electricity generation, and build least squares support vector machine (LSSVM) model to realize the prediction of unit power cost under different flexibility levels. The research results indicate that prediction error in specific conditions can be reduced by 50% compared with that in full conditions.