In order to investigate the effects of oxygen addition amount and type of gasification medium on coal gasification efficiency as well as the optimization of integrated gasification combined cycle (IGCC) power system, a simulation analysis is carried out by baking two kinds of coals with significant differences in oxygen content as the examples. Firstly, based on the equilibrium reaction model, the influence of oxygen carbonation stoichiometric ratios (considering the oxygen content of different coal types) on gasification characteristics for different coal types is compared. Then, the gasification characteristics are analyzed and optimized when CO₂ and steam are added as gasification media respectively. On this basis and considering CO₂ capture, a novel IGCC power cycle system with CO₂-assisted gasification, pure oxygen combustion and partial gas recirculation is proposed and analyzed, and the gas turbine model is simulated and optimized. The results show that, the coal gasification performance is the best when the total oxygen-carbonation stoichiometric ratio is around 0.47. Under this condition, adding CO₂ as the gasification medium can increase the efficiency of cold gas by about 1.3%, compared with that of the conventional way that adding steam as the gasification medium. Compared with the conventional IGCC power system with pre-combustion decarbonization, the net power efficiency of the proposed system increases by about 1.5% and the exergy efficiency increases by 1.7%, which provides a new idea for designing a low-carbon and efficient IGCC power generation system.

The coupling of photovoltaic-thermal utilization and ground source heat pump is expected to use photovoltaic waste heat to avoid performance degradation of the heat pump, and also to use photovoltaic electricity to partially meet the energy demand of the heat pump, which has a broad prospect. A simulation model of the integrated system of low-concentration photovoltaic-thermal and ground source heat pump is constructed, and the operational performance of the system is analyzed. Moreover, the key influence laws of the life cycle cost of the system are also analyzed. The research results show that, the annual solar-to-electrical efficiency of the integrated system reaches 17.73%, which is 9.58% higher than that of the single operation system. The photovoltaic waste heat of the photovoltaic-thermal device can effectively reduce the soil temperature decay, and the long-term operation performance of the heat pump is 16.58% higher than that of the reference system. The operation and maintenance cost of the system decreases with the increase of the scale of the photovoltaic-thermal device and the ground source heat pump, while the investment cost increases accordingly. The total life cycle cost of the system decreases at first and then increases with the increase of the scale. Taking the life cycle cost as the objective function, economic optimization of the system based on the particle swarm algorithm is carried out, and the life cycle cost reduces by 31.52% compared with the design of the maximum scale capacity. The relevant results can provide theoretical reference for optimal design of the photovoltaic-thermal-ground source heat pump integrated system.

In order to adapt to the harsh service environment of 700 ℃ advanced ultra-supercritical coal-fired power generation unit (700 ℃ A-USC), and facilitate the development of high efficiency, low consumption and low carbon coal-fired power generation technology, high temperature superalloy will be used to manufacture the high-temperature components in boiler and turbine. Many countries and regions such as the United States, Europe, China, Japan and India have put forward research plans of 700 ℃ A-USC technology with national characteristics, respectively. Due to the variety of elements, high welding difficulty, and high tendency to produce welding defects in high-temperature alloys, welding technology and weld joint comprehensive performance evaluation technology have a significant influence on the factory manufacturing, on-site processing and repair, as well as service safety and integrity of high-temperature components. The current progress in practical application of the 700 ℃ technology at home and abroad is slow, which is mainly due to incomplete resolution of technical barriers such as manufacturing, connection, and testing. The research plans and development prospects of the 700 ℃A-USC technology around the world are summarized. The material selection of high temperature components including the boiler side and the turbine side is discussed. The current status, advantages and disadvantages of the welding technology for superalloy are summarized, and the critical focus points of the joint comprehensive properties evaluation technology for high temperature components are analyzed. Finally, some suggestions on developing the 700 ℃ A-USC technology are put forward.

Equipment failures, weather conditions and other factors can lead to a large amount of abnormal data in distributed photovoltaic (PV) power generation systems, causing serious effects on their safe and stable operation. In order to accurately identify and remove these abnormal data, a distributed PV power generation abnormal data identification method is proposed based on dynamic time warping (DTW) and two-stage quartile. Firstly, continuous abnormal data identification and elimination are achieved by comparing the mean photovoltaic power under similar irradiance. Abnormal data are eliminated based on the comparison of the mean photovoltaic power at the same period, taking into account the fluctuation of the photovoltaic power generation curve. A comprehensive curve similarity judgment method based on DTW and Euclidean distance is used to consider the fluctuation characteristics of the data more comprehensively, thereby improving the recognition and elimination effect of continuous abnormal data. Secondly, the DTW-Two-Stage Quartile abnormal data identification algorithm is proposed, and the first-order change rate and the second-order change rate are used to eliminate discrete abnormal data from the fused data, effectively identifying and eliminating discrete abnormal data. Finally, it is determined whether a fault has occurred based on the results of abnormal data identification and elimination. Experimental results show that, after the proposed algorithm eliminates abnormal data, it can better fit the distribution of normal photovoltaic power data. Compared with the quartile method and the 3-Sigma algorithm, the linear correlation degree of the proposed algorithm before and after the elimination of abnormal data has increased by 58.15% and 68.41% respectively, with better identification results.

Low-temperature SCR denitration is one of the current research highlights in de-NO_x field. Developing efficient and stable SCR catalysts under low temperature conditions (<300 ℃) is the key to solve the problem. Carbon-based materials have developed pore structures and high specific surface area, which can provide space and surface support for the loading of active catalytic components. Carbon-based catalyst for low-temperature de-NO_x technology has broad development and application prospects. The present work introduces the low-temperature de-NO_x reaction mechanism and the commonly used carbon-based materials, and analyzes the factors affecting the low-temperature de-NO_x performance of carbon-based catalysts. Moreover, it summarizes the research progress of carbon-based catalysts from the aspects of pre-treatment to enhance oxygen-containing functional groups, active components to improve de-NO_x performance, reasonable calcination to enhance de-NO_x performance, and anti-poisoning to maintain stable denitrification performance. Finally, the prospective future development directions and suggestions are given.

The vibration mechanism and characteristics of stator housing in nuclear power turbo-generators under different excitation forces are investigated, and an analysis and treatment method for the stator housing vibration fault is proposed. Moreover, analysis and verification is conducted by using three nuclear power turbo-generator units as examples. The results show that, the main cause of excessive stator housing vibration is the structure resonance resulting from the natural frequency of the stator housing being close to the rotating frequency or its double. The structure resonance caused by rotor excitation force can be controlled in two ways: by reducing the excitation force through field dynamic balance, or by adjusting the natural frequency of the stator housing through adjustment of the stator bottom bracing load distribution. Performing on-site dynamic balancing can effectively reduce the rotor excitation force. Adjusting the natural frequency of the stator housing can be realized through load distribution adjustment of the stator feet. However, due to the limited adjustment range of the magnetic pulling force, it is necessary to control the structure resonance caused by magnetic pulling force by adjusting the natural frequency of the stator housing. To prevent structure resonance of the stator housing, it is important to adjust the stator bottom bracing load distribution during installation or maintenance of the turbo-generators to keep the natural frequency of the stator housing away from the rotating frequency and electromagnetic force frequency.

There is a delay in NO_x measurement for flexible operations in coal-fired power plants, which leads to a delayed response in ammonia injection control system of selective catalytic reduction (SCR) reactor, resulting in potential over or under-injection of ammonia and significant fluctuations in NO_x mass concentration at outlet of the SCR reactor. To enable proactive adjustment of ammonia injection and considering the interconnected factors influencing the NO_x emissions from coal combustion, a prediction model for NO_x mass concentration at the SCR reactor inlet is proposed based on convolutional neural networks (CNNs) and long short-term memory neural (LSTM) networks. By using operational parameters from a 330 MW coal-fired power plant, a Pearson coefficient method is employed to calculate the correlation between feature variables. Significant features are extracted to define the model input matrix and output matrix. The random search algorithm is used for hyper-parameters optimization to enhance predictive performance. The SHAP algorithm is then applied to interpret the model structure and explain the black-box model. Finally, the control effects of model with NO_x concentration prediction is verified through Simulink simulation. The results indicate that, the CNN-LSTM prediction model demonstrates higher predictive accuracy for the variable NO_x mass concentration at the SCR reactor inlet during the frequent load fluctuations. It can provide feedback to the ammonia injection control system of 25 seconds in advance. The optimized ammonia injection control strategy not only reduces the standard deviation between the NO_x mass concentration at the SCR reactor outlet and the set value by 28%, but also improves the response speed of NH₃/NO_x regulation, reducing the maximum ammonia slip by 22%. The research findings can provide guidance for intelligent SCR denitration system and combustion optimizing operating during flexible operation of coal-fired power plants.

A multi-energy complementary system integrating solar-hydrogen-gas has been developed for multi-energy complementary cogeneration systems, aimed at meeting users’ demands for cooling, heating, power, and gas. In order to optimize the system performance, a multi-objective optimization evaluation system of the multi-energy complementary cooling, heating and power cogeneration system including economy, environmental protection and hydrogen doping ratio is constructed, and a mixed-integer linear programming model for multi-objective optimal scheduling is established based on this system. With the obtained Pareto frontier solution set, the optimal solution in the solution set is found by using the method of distance to the ideal solution to identify the optimal solution. By changing the blending ratio of hydrogen injected into the natural gas pipeline network, the optimal operating conditions for the devices in the electricity, heat, and cold networks are obtained. The results show that, under the condition of fixed user load, with the hydrogen doping ratio of 14.47%, the system operating cost per day is the lowest (26 794.31 yuan), and the carbon emission is the least (162.03 kg). The results indicate that the proposed scheme is not only economically better, but also has the characteristics of energy saving and emission reduction, and performs the best in comprehensive evaluation, compared with the 2 reference systems. The conversion of renewable energy sources into electricity, followed by the transformation into hydrogen and its incorporation into the natural gas pipeline network according to a specified blending ratio for application in combined cooling, heating, and power generation systems, significantly reduces the use of natural gas. This approach enhances energy utilization efficiency, maximizes the integration of renewable energy sources, and reduces carbon emissions.

The excessively high temperature gradient inside solid oxide fuel cell (SOFC) can lead to failure of the cell, so it is critical to reduce the temperature gradient in the SOFC and enhance the uniformity of the cell temperature. By combining with the electrical, thermal, flow, and mass transfer physical fields, a multi-physics field coupling model of the SOFC is established. The accuracy of the model is verified by comparing with the experimental data. The SOFC temperature and temperature gradient distributions are investigated by the SOFC model and the maximum temperature gradient in the cell reaction zone is determined as the optimization objective. The obstacle structure in flow channel is designed, and the effectiveness is proved. The shape, height and width of the obstacle structure are discussed and analyzed. It is found that the obstacle affects the maximum temperature gradient in the reaction zone mainly by changing the fluid flow rate and the oxygen molar concentration in the reaction layer. The change of the obstacle for the pressure drop in the flow path mainly affects the power density loss. Finally, the circular obstacle (h=0.8 mm, d₁=4.0 mm) is identified as the optimal structure. With the same net power density as the conventional channel, the maximum temperature gradient is 43.35 K/cm, which is 9.4% lower than that of the conventional channel.

The technology of concentrating solar power tower plant with molten salt is currently the predominant photothermal power generation technology globally. The performance of the molten salt receiver, which serves as the core device for converting solar energy into heat, directly influences the system’s power generation efficiency. Additionally, the safety of the receiver affects the operational hours of the power plant. Consequently, it is crucial to develop a heat transfer model for the molten salt receiver and ascertain its precise heat transfer characteristics. This paper systematically organizes the heat transfer calculation model for the mainstream external cylindrical molten salt receiver, delineating the calculation process and fundamental methods for input radiant energy, radiant heat loss, convective heat loss, and molten salt heat gain within the heat transfer model. Based on the refinement level of the calculation outcomes, the heat transfer model of the receiver is bifurcated into a detailed model and a simplified model. While the detailed model boasts high calculation accuracy, offering a comprehensive representation of the actual energy conversion process, it is computationally expensive and requires extended transient process calculations. Conversely, its specific working condition calculations serve as a verification reference for the simplified model’s results. The simplified model entails a judicious simplification of the theoretical model that describes the heat transfer characteristics of the molten salt receiver, facilitating faster calculations while maintaining accuracy. It is predominantly employed during the design phase. By comparing and contrasting the characteristics and performance of these models, technical guidance can be offered for selecting appropriate heat transfer models for thermal performance calculation processes in molten salt receivers.