The fouling of heat exchangers and cooling tower fill surfaces in the external cooling water system of synchronous condenser can significantly impede the heat transfer efficiency of cooling towers, posing a serious threat to the safe operation of synchronous condenser. In order to propose more effective anti-fouling measures and elucidate the causes of fouling, this study employed characterization techniques such as SEM-EDS, XRD, FTIR, etc., to analyze the microscopic morphology and chemical composition of fouling samples. Additionally, chemical analysis methods and ICP-MS were used to analyze the makeup of makeup water and circulating water in the system. The test results revealed that the primary components of fouling in the external cooling system are CaCO₃, SiO₂and CaSiO₃. The fouling in the cooling system is closely related to the absence of wastewater discharge measures in the system, high concentration ratios during operation, and the infiltration of regional windblown sand. This research contributes to proposing targeted anti-fouling measures for on-site operation of such cooling systems, ensuring the economic and operational safety of synchronous condenser.

High temperature steam pipe is an important part of the power plant. In order to coordinate the pipeline thermal expansion and reduce the pipeline thermal expansion stress caused by the higher altitude difference and larger horizontal span, a lot of constant supports and hangers are designed in pipeline. But because friction moment exists on the rotating shafts, constant supports and hangers are not a constant force, the load deviation will make the pipeline deviate from the designed cold and hot line, and the pipeline stress will increase. For controlling the quality of constant supports and hangers, there are two quality performance control indexes among the relevant domestic standards, namely the constant degree and the load deviation degree. This article focuses on the load deviation degree. It finds out that, the load of putting out pin measured by different loading directions is different, resulting in a large difference in load deviation degree due to friction moment of the rotating shaft of the constant supports and hangers. So the load of putting out pin shall not be used as a representative parameter. The study proposes that the average load shall represent the position of the displacement-load curve, which is a representative parameter of constant supports and hangers. A new formula for calculating the average load deviation degree is proposed. It is suggested to modify the related standards to improve the quality of the constant supports and hangers.

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.