To further improve the accuracy and reliability of transient stability assessment (TSA), a feature selection method (Powershap) based on the combination of statistics and Shapley values is proposed, and a power system transient stability assessment model is established. Firstly, the input feature set is constructed based on the steady-state components during the operation of the power system. Powershap is used to divide the dataset into multiple subsets for training, and key feature sets are selected. Then, multiple CatBoost models are trained using key feature sets and transient stability assessments are conduct to generate transient stability assessment models. Finally, simulation experiments are conducted on the New England 10-machine 39-node system and the New England 54-machine 118-node system with the addition of new energy generation, and evaluation results are provided. The experiments show that, in the 10-machine 39-node system in New England, using the Powershap feature selection method for classification can achieve an accuracy of 99.79%. On the improved New England 54-machine 118-node system, its accuracy can reach 99.49%, indicating that the method can effectively perform transient stability assessment of power systems. It is verified that the proposed TSA model has good robustness and generalization ability.

The large-scale integration of wind power into grid makes it difficult to sustain the peak regulation resources of the existing system, and the wind power consumption is hindered. Therefore, considering the uncertainty of wind power output and electricity price, it proposes a distribution robust optimization method for deep peak regulation of electrolytic aluminum load cooperating with thermal power and energy storage system based on Wasserstein distance. Firstly, combined with the load characteristics of electrolytic aluminum, considering the optimization of deep peak regulation capacity of the energy storage auxiliary thermal power units, an electric power system optimization framework for deep peak shaving of the electrolytic aluminum load and thermal power-energy storage system is established. Secondly, drawing on the idea of the robust model of Wasserstein distance distribution, the Wasserstein fuzzy set constraint of the purchase and sale price of the upper power grid and the output of renewable energy is constructed, and the distribution robust optimization model for deep peak regulation of the electrolytic aluminum load and thermal power-energy storage system is designed. Finally, simulation is performed to verify that the proposed method can effectively improve the peak regulation pressure, reduce the operating cost of the system, and promote the consumption of wind power. The economics and robustness of the method are verified by comparative analysis.

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.

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 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.

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.

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.

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.

To achieve the carbon peak and neutrality targets, facilitate low-cost disposal of industrial solid wastes (namely semi-coke ash), and develop new green and low-carbon composite materials, carrying out carbon capture using semi-coke ash is proposed, based on the existing semi-coke ash/sodium nitrate composite phase change heat storage materials. The performance of semi-coke ash and composite phase change heat storage materials before and after carbon sequestration is studied. The results indicate that, the optimal conditions for carbon sequestration in semi-coke ash are: gas composition of 20%CO₂/80%N₂, ventilation time of 40 minutes, and heating temperature of 650 ℃. Under the optimal experimental conditions, the carbon sequestration rate of semi-coke ash reaches 29.27%. The optimal mass ratio of the resulting composite phase change heat storage material, namely the carbon-sequestered semi-coke ash to NaNO₃ is 5:5. It achieves a heat storage density of 288.65 J/g at 100~380 ℃, with better mechanical properties, thermal stability, and chemical compatibility. The use of carbon-sequestered semi-coke ash as a skeletal material to prepare composite phase change heat storage materials is highly feasible, providing a new approach for the resource utilization and carbon emission treatment of industrial solid wastes, namely semi-coke ash.

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.