The “carbon neutralization and carbon peak” goal proposed in the 14th Five-Year Plan has a profound effect on the power industry in many aspects, the transformation of electricity to low carbon direction has become an irreversible mainstream trend. This paper expounds the low-carbon power plant, low-carbon power grid, low-carbon energy consumption and related evaluation technologies in the low-carbon electric power system, and shows that the system has high efficiency, clean and recyclable low-carbon attributes in terms of energy saving, emission reduction and environmental protection. At the same time, the effect of the change of international low-carbon forms on China and the related problems in the concrete implementation of the “carbon neutralization and carbon peak” policy are analyzed, it puts forward a new scientific thinking for the implementation of the “carbon neutralization and carbon peak” strategy and the low-carbon transformation of the power industry.

Clarifying the driving factors for promoting low-carbon technology innovation in the power generation industry, and exploring incentive mechanisms for low-carbon technology innovation in the power generation industry, is of great significance for achieving the unity of economic, environmental, and social performance in the power industry, and ultimately achieving the “dual carbon” goal of the country. This article focuses on the characteristics of technological innovation in the power generation industry, starting from the two stages of low-carbon technological innovation, and based on external driving forces and internal driving forces of enterprises, it proposes 11 incentive factors to construct an internal and external collaborative incentive mechanism for low-carbon technological innovation in the power generation industry. The results show that, with the synergistic effect of the low-carbon technology innovation incentive mechanism in the power generation industry, the innovation research and development level of low-carbon technologies of enterprises can be promoted, and the economic, environmental and social performance of the enterprises can be improved through the transformation of low-carbon technology achievements. Therefore, an organic unity of enterprise development, environmental improvement and social progress is realized ultimately.

Compressed carbon dioxide energy storage system has the advantages of large energy storage density, compact system equipment and long operating life. Expander is the key equipment of the energy storage system and has a direct effect on the efficiency and performance of the entire energy storage system. This article reviews the research status of various types of expanders. The working principle and characteristics of different types of carbon dioxide expanders are introduced. The expander types that can be used in compressed CO₂ energy storage systems are provided. The problems and their countermeasures of four kinds of expanders applied to energy storage systems were analyzed. The research direction of CO₂ expander is pointed out, including design method optimization, key component structure optimization, leakage, sealing, friction, and lubrication, and so on, which provides reference for the optimal design of the expansion machine of compressed CO₂ energy storage systems.

Adiabatic compressed air energy storage technology (A-CAES) can be used for peak shaving and frequency regulation of renewable energy electricity, which is an effective means to achieve the goal of “Dual Carbon”. In order to study the influence of key parameters such as the number of stages, hot side temperature difference, and throttling valve pressure on thermodynamic efficiency and economy of the system, and achieve the lowest levelized cost of energy (LCOE), an A-CAES model based on MATLAB is constructed for calculation. The results show that, within the range of simulated working conditions, the efficiency decreases with the increase of the number of stages and the hot side temperature difference, while increases with the throttling valve pressure, and the highest efficiency can reach over 70%. The LCOE of the secondary compression and secondary expansion is the lowest, which is 0.041 3~0.045 0 dollars/(kW·h). The LCOE decreases with the increasing throttling valve pressure. When the hot side temperature difference is greater than 2.5 K, the LCOE increases with the hot side temperature difference. Therefore, the A-CAES can realize efficient and low-cost energy storage.

CO₂ geological utilization and storage (CGUS) is an important technical means to achieve the goal of “carbon neutrality”. Solving the steel corrosion problem in the process of CGUS is crucial to reduce the risk of CGUS technology and achieve the large-scale promotion and application of CGUS technology. In this paper, the proposed reaction mechanism of CO₂ corrosion of steel is reviewed, and the main factors influencing CO₂ corrosion of steels are summarized. Moreover, the effects of CO₂ partial pressure, temperature, salinity and pH value, the CGUS environment containing impurities, fluid flow and other factors on steel corrosion behavior are clarified, and the main protective measures for CO₂ corrosion of steels are summarized. On this basis, the key research directions of steel subjected to CO₂ corrosion in CGUS environment are put forward. The directions include further exploration of the reaction mechanism of CO₂ corrosion of steels, quantitative study on the coupling effect of various environmental factors on the law and degree of CO₂ corrosion, as well as the development and application of corrosion protection technologies under high CO₂ concentration conditions.

To solve the difficult problems of renewable energy consumption, hydrogen energy storage and transportation, an off grid integrated system for wind, solar, hydrogen and ethanol is proposed. The system operates offline, utilizing wind and photovoltaic power generation to provide electrical energy. By using batteries and hydrogen storage tanks as energy storage and hydrogen storage equipment, electricity and hydrogen energy is stably supplied in a peak shaving and valley filling manner, ensuring the stable and continuous production of methanol in the electrolytic cell and methanol generation equipment. A mathematical model for solar energy hydrogen storage alcohol is constructed with the goal of maximizing the total system revenue, and the optimal equipment capacity and operation scheduling of the system is determined through mixed integer linear programming algorithm combined with real solar energy data analysis. The operating strategy and the system energy of the system on a typical day is analyzed, and finally the economic performance of the produced green methanol is investigated. The results indicate that, the system can switch operating states reasonably based on changes in external conditions, thus to achieve energy balance in the system. On the premise of meeting various constraints, the utilization rate of renewable energy is improved and the leveling cost of methanol production in the system is reduced. This study proposes a feasible technical route for the consumption of new energy and the utilization of hydrogen energy, and provides certain guidance for the construction of related demonstration projects.

Optimization control strategies for hydrogen production system coupled with photovoltaic and energy storage are studied, and a power allocation strategy based on model predictive control that considers multi-objective optimization problems with game relationships is proposed. Firstly, the architecture of the hydrogen production system coupled with photovoltaic and energy storage is constructdd, and the power balance equation that needs to be met during the operation of the hydrogen production system coupled with photovoltaic and energy storage is clarified. Secondly, a composite algorithm model is established by combining the self-adaptive multi-objective particle swarm optimization algorithm with the MPC algorithm, and three objective functions that consider both alkaline electrolyzer (AEL) and energy storage battery characteristics are provided, then the weight coefficients of the optimal control increment are calculated. Finally, the MPC controller model is constructed using the MATLAB-function module, and the calculated weight coefficients of the optimal control increment are applied to the MPC optimization process, thus the online power allocation for the hydrogen production system coupled with photovoltaic and energy storage is ultimately achieved. Through simulation analysis and comparison with two optimization control methods, it is proven that the proposed method in this paper improves the operational indicators of the energy storage system to a certain extent while reduces the fluctuation of AEL input power, it enhances the dynamic power balance ability of the hydrogen production system coupled with photovoltaic and energy storage.

Under the background of flexible peak regulation, in order to adapt to the dynamic change of direct air-cooled unit load and the interference of environmental factors, an online learning neural network method is proposed to predict the backpressure of direct air-cooled unit. Firstly, the historical data are cleaned and Spearman correlation analysis is used to determine the important features of low redundancy affecting backpressure. Then, the Hammerstein model is used to identify the model parameters online for the backpressure. At the same time, the backpressure prediction model of direct air-cooled unit is established by using long-short memory neural network and attention mechanism, and the model is updated by online learning. The experiments results show that, the model has an absolute percentage error (MAPE) of less than 9% in predicting backpressure at different time spans within the next 1 hour, and a MAPE of less than 1% in predicting backpressure within 30 seconds. Finally, the actual power plant system is used to verify that the model can run stably in practical applications. The results of this study provide an effective method for real-time prediction of the backpressure of direct air-cooled unit, which is of great significance for the operation and management of direct air-cooled unit with flexible peak regulation.

The cooling efficiency of flat film was measured using a high-precision infrared thermal imager, and the film cooling efficiency between double-cross-row holes and single row holes is compared. The interaction between film holes and the influence of blowing ratio (M=0.65, 1.0, 1.5) and density ratio (DR=1.0, 1.5) on the cooling efficiency was analyzed. Moreover, the flow field with film cooling was compared using numerical calculation methods. The results show that, with the increase of the blowing ratio, the cooling efficiency of the single row holes decreases while that of the double-cross-row holes improved greatly, but the film coverage effect at the spanwise direction deteriorates. Increasing the density ratio will improve the cooling performance. However, the influence of double rows of film holes and blow ratio is much higher on the cooling effectiveness, compared with the density ratio. For the double rows of film holes cooling, the cooling jet forms a reverse kidney-shaped vortex downstream of the holes, which will prevent the jet blowing away from the cooling wall.

In wind turbines, the aerodynamic efficiency of wind turbines is closely related to the aerodynamic performance of excellent airfoils. Taking the conventional airfoil of wind turbine as the research object, combined with airfoil parametric modeling and self-adaptive genetic algorithm, the high performance optimized airfoil is obtained. The fitting accuracy of the conventional NACA63418 airfoil is compared between the CST method and the improved Hicks-Henne type function method, and then the Hicks-Henne type function method is selected to model the NACA63418 airfoil. The automatic calculation of aerodynamic characteristics of airfoil is realized by the coupling of self-adaptive genetic algorithm and XFOIL software, and the design efficiency of airfoil is improved. It broadens the train of thought and improves the design efficiency for the theoretical design of airfoils.

Under oceanic conditions, the coolant in the loop of a floating nuclear reactor (FNR) experiences periodic fluctuations, which affects the system’s thermal and hydraulic characteristics. A combination of theoretical derivation and numerical simulation is employed to investigate the velocity and temperature distribution characteristics within a pipe under pulsating flow conditions. Moreover, the influence of different numerical simulation boundary conditions on the velocity and temperature distribution in a circular tube under pulsating flow is compared. The results show that, under high-frequency pulsating flow conditions, laminar flow inside the pipe will experience backflow near the wall, and the wall effect will increase with the pulsation frequency. Using pulsating velocity inlet and pressure outlet as numerical simulation boundary conditions fails to predict this backflow phenomenon. However, employing fluctuating pressure inlet and flow outlet effectively captures the backflow occurrence in high-frequency pulsating flow. Concurrently, the temperature within the pipe fluctuates under pulsating flow conditions, and the amplitude of temperature fluctuations gradually decreases when the pulsation frequency increases. Numerical simulation can well simulate the temperature distribution in the pipe under pulsating flow conditions, with an error of less than 2%.The research results can provide reference for non-stationary numerical simulation methods.

Accurate carbon emissions data of gas units is one of the guarantees to ensure carbon trading. Many gas units recently installed online gas chromatography devices, so that the carbon emission is able to be real-time monitored from fuel part. For units that are not equipped with flue gas CO₂ monitoring system or have no enough equipment space, conversion with flue gas O₂ concentration is one of the feasible paths to monitor carbon emission from flue gas part. But whether direct measurement or conversion monitoring methods, there is still a lack of sufficient research on the deviation of continuous monitoring data from the fuel part and flue gas part. Therefore, for the gas units without capability to directly monitor flue gas CO₂ in the short term, this study takes the historical data of an F-class gas-steam combined cycle unit for the simulation, and conducts continuous simulation monitoring and analysis based on the conversion with flue gas O₂ concentration and online gas chromatography. It is found that there is no stable sorting rule of the monthly data and the relative deviation between different calculation methods. All the relative deviation of annual data is less than 5%. The correlation between δ_{RD,R,fluegas-flue-h} and the O₂ concentration of CEMS is the highest. The deviation of carbon emission amount in the unit is mainly in the stable combustion section with a load ratio of more than 55%. In accordance with current standards or specifications, the O₂ concentration of CEMS and the wet flue gas flow rate at the chimney outlet is most likely to cause the deviation of carbon emission amount from the fuel part and flue gas part. Under the existing technical specifications, the carbon emission from fuel part and flue gas part can be monitored in real time, which can be used for analysis on trend, but only the uncertainty of result from fuel part is below 5%. For gas units, the carbon emission monitored at fuel part is more appropriate, and the method monitoring the flue gas part may be more suitable for coal-fired units.

In order to meet the demand of estimating regional heat load for cogeneration enterprises, an estimation method using elastic network regression model is proposed. Firstly, the influencing factors of the actual heating heat index are analyzed to determine the input parameters of the model. Then, based on the actual operation data of 123 residential areas in Xi’an in the heating season from 2022 to 2023, the estimation model is established, and it is proved that the accuracy of the model is higher than that of Lasso regression and ridge regression models. Finally, part of the communities in Xi’an are selected to form a verification set to verify the elastic network regression model. The verification results show that, the elastic network regression model combines the advantages of Lasso regression and ridge regression, and has higher prediction accuracy than the conventional machine learning model. The MAE and goodness of fit of the model are 1.150 and 0.953, respectively, indicating that the method can accurately estimate the actual heating heat index with different parameters, and can meet the actual engineering needs of cogeneration enterprises.

The real gas characteristics of supercritical carbon dioxide (S-CO₂) make it difficult to obtain stable convergence results in three-dimensional numerical simulation of S-CO₂ centrifugal compressor, and the time cost of numerical calculation further increases the difficulty of compressor design optimization. To establish a flow calculation method suitable for S-CO₂ centrifugal compressor, three-dimensional numerical simulation is carried out on the compressor to obtain the flow field information and corresponding loss distribution. Then, the one-dimensional loss model is superimposed in the conventional flow line curvature method, and the CO₂ compression factor is calculated in segments along the flow line, thus to reflect the real gas compression process. Comparison between the calculation results and the three-dimensional numerical simulation results shows that, the distribution of meridian relative velocity field and enthalpy obtained by streamline curvature method are consistent with the computational Fluid dynamics (CFD) results. The temperature and pressure data at the blade outlet are close to the CFD results, with errors of 0.23% and 1.08%, respectively, and a difference of 1.5% in total static isentropic efficiency. The results indicate that the performance parameters of S-CO₂ centrifugal compressor impeller can be obtained quickly and accurately by using streamline curvature method.

The conventional flexible retrofit plan for coal motor sets is difficult to eliminate the potential life loss and equipment safety risks caused by frequent and rapid load changes to the thermal system. In order to improve the long-term safety and economy of coal-fired power units participating in deep peak shaving, a “healthy peak shaving” technical route for coal-fired power units based on hydrogen energy storage system is proposed, with a domestic ultra supercritical secondary reheat 1 000 MW coal-fired unit as the application object. The indirect carbon emission reduction significance of peak shaving coal-fired power hydrogen production is demonstrated. On this basis, the matching degree between different hydrogen production processes and the production conditions of coal-fired power plants were analyzed. It was believed that solid oxide electrolysis cell (SOEC) hydrogen production was the comprehensive optimal plan. Based on this, a principle design scheme for SOEC coupled coal-fired power peak shaving was proposed. Finally, a financial analysis was conducted on the new plan using the annual load curve. The calculation results indicate that, the SOEC assisted deep peak shaving of coal-fired power can increase the annual revenue of the example unit by 236 million yuan, and obtain other benefits such as equipment lifespan extension, consumption reduction, and carbon reduction. The relevant conclusions have reference significance for guiding the healthy and safe operation of peak shaving coal-fired power units.

With the increasing annual growth of wind and solar power generation, the issue of power consumption has become increasingly prominent. Meanwhile, high-capacity thermal power plants face relatively high auxiliary power loads, resulting in additional operating costs. To address these issues, a joint optimization dispatch model for wind-PV-thermal-storage for auxiliary power system of thermal power plant is developed based on the concept of multi-energy complementarity. Firstly, the compositional structure of the wind-PV-thermal-storage integrated power supply for auxiliary power of thermal power plants is outlined, prioritizing the supply of auxiliary power loads with wind power and photovoltaic power. Secondly, a wind-PV-thermal-storage integrated power supply optimization scheduling model is developed, taking into account the operating costs of thermal power units at different load rates and the costs associated with wind power, photovoltaic power, and energy storage. A hierarchical analysis method is employed to establish a multi-objective function based on the total cost, wind and solar curtailment costs, and environmental costs, while considering corresponding constraint conditions. Finally, various scenarios are set up to compare and analyze the optimization results of the integrated power supply system for auxiliary power. Experimental results demonstrate that the proposed model for the integrated power supply system can effectively reduce unit operating costs and environmental costs, as well as promote the integration of wind and photovoltaic power.

With the advancement of intelligent mining construction, the number of application systems is gradually increasing, and problems such as incomplete data unification, lack of overall management of the system, and repetitive construction of functions are becoming prominent. To avoid these issues, this article takes the Yimin open coal mine data center as an example to analyze the overall architecture of the coal mine data center in detail. Based on the industrial private cloud development platform and big data technology, an open, continuous integration and deployment data center is established, and it supports high load elastic scaling and meets the concept of intelligent open-pit mine management. The data center solves problems such as difficulty in data collection in the mining field, inability to store data uniformly, isolated business systems, and inability to share data conveniently and in a timely manner among mining surveying professionals. It also comprehensively utilizes the collected equipment and system data to achieve real-time control of production status and equipment status, improving management decision-making ability and means.

H₂S is an important product produced by power plant boilers in the process of low NO_x combustion. To solve the problems that H₂S may cause various hazards to thermal power plants due to its inflammability, strong corrosion and extreme toxicity, tunable diode laser absorption spectroscopy (TDLAS) method combined with multi-pass cell and computer is employed to build an online measurement system for detecting the molar fraction of low-concentration gas. By using this measurement system, accurate online measurement of H₂S in the mixed gas with the molar fraction of 10^–6 magnitude is realized, and the H₂S high-temperature reaction experiment is carried out to explore the influence of experimental temperature and the molar fraction of O₂ in the mixed gas on the reaction. The experimental results show that, under the conditions of pressure of 80 kPa and molar fraction of O₂ ranging from 0 to 5%, the temperature at which H₂S begins to react changes with the molar fraction of O₂. On the whole, the higher the molar fraction of O₂ in the mixed gas, the lower the temperature at which H₂S begins to react. The experimental results can provide some data basis for the generation, transformation and harm control of H₂S in boiler flue gas.

Chloride ion is the key operating index in desulfurization system of power plants. Rapid and accurate monitoring of chloride ion content in desulfurization slurry is of great significance for anti-corrosion of desulfurization equipment, optimization and adjustment of operation process, as well as desulfurization waste water discharge and water saving. By studying the pretreatment method of sample, a high-efficiency composite medium filter is developed, and the method suitable for the desulfurization system sample pretreatment is studied, and the laboratory test is carried out. At the same time, by studying the principle of online measurement method of chloride ion in desulfurization system, a solid polymer membrane chloride selective electrode is developed, and on-line monitoring technology of chloride ion in desulfurization system of power plant is developed, and the accuracy test in laboratory and field industrial application test are carried out. The results show that, the technology can realize continuous and accurate online monitoring of chloride ion content in desulfurization slurry, reduce the workload of laboratory personnel greatly, and improve the accuracy of chloride ion measurement. It is of great significance to realize the economic and intelligent operation of desulfurization system equipment.

Infrared spectroscopy detection technology has been widely used in petrochemical, pharmaceutical and other industries due to its fast detection speed, no damage to the sample, no pollution, easy to operate and other characteristics. The infrared spectroscopy detection mainly includes qualitative detection and quantitative detection. The qualitative detection usually uses comparative method, which compares with standard substances or consults standard spectra. The quantitative detection calculates the corresponding components content by measuring the intensity of characteristic absorption bands and combining with chemometrics methods. This article elaborates the applications of chemometric methods (including artificial neural networks and partial least squares) in detection scenes such as acid value, moisture, antioxidants and furfural for electric power oil. Finally, some proposals of infrared spectroscopy in oil detection are put forward.

Rapidly growth of organic solid waste (OSW) has caused serious social and environmental issues. Co-combustion is an economical and environmental method to treat OSW. However, there will be a variety of heavy metals discharged with flue gas during combustion as OSW contains them. Therefore, this study conducted an experiment on the migration of heavy metals and generation of micro particles during the co-combustion of OSW and lignite. The results show that, the release of heavy metals during combustion not only depends on the concentration of heavy metal the fuel contains, but also on the chemical mechanism at high temperature. The content of Pb, Cd and As in the flue gas of blending fuel is obviously lower than that of sole OSW, but Cu, Zn, Co and Mn shows opposite tendency. In addition, the particle size distribution of the four fuels all shows a normal distribution at 800 ℃ and 850 ℃, but large particle size generates when the combustion temperature rises to 900 ℃.

At present, China’s thermal power plant steam/water pipeline design standard stipulates that the load variation coefficient of spring hangers should not exceed 25%. Accordingly, the designed proportion of the constant support hanger is too high, and the “illegal” transfer of the load will cause the pipe operation deviates from the design line, and the stress increases. This paper analyzes the relationship between the constant degree and the load variability factor of constant hanger. The optimization design case shows that, properly increasing the load variation coefficient of spring hangers in the design of steam/water pipelines can increase the proportion of spring hanger configuration and reduce the occurrence of abnormal pipeline expansion.