The dynamic model of resistive type molten salt heater was established by Dymola software, and the transient characteristics and internal temperature field of resistive type molten salt heater under electrical load and molten salt flow disturbance and different arrangement modes were studied on the basis of verifying the effectiveness of the model. The results show that the influence of large disturbance of electric load and molten salt flow on the dynamic characteristics of resistance type molten salt heater tends to be the same, and reaches its limit condition at 110 s and 105 s respectively. However, the occurrence of the limit condition can be greatly delayed when the two disturbances are coordinated. Multiple electric heaters arranged in series or in parallel can slow down the change of molten salt temperature, but increase the system cost. The research conclusion can provide reference for the design, control and debugging of resistance molten salt heater.

With the increasing penetration of new energy in new power system, the influence of the uncertainty of wind power output and the correlation with load on the system operation is increasingly prominent. Thus, the conventional transformer risk assessment can no longer meet the demand. Based on Copula model and Susa model, a joint probability assessment method of transformer operation risk considering wind power and load correlation is proposed. Monte Carlo method is used to calculate each risk index value and evaluate transformer operation risk. The research results show that, the conventional transformer evaluation system that does not consider the wind-load correlation will lead to a low overall risk assessment result, with the maximum error of the index up to 55.02%. Also, with the increase of wind-load correlation, the risk of thermal defects of the transformer is increasing. The research conclusions can assist to improve the accuracy of the operation risk level assessment of new power system transformers, and provide a reference for the later transformer condition assessment and maintenance plan formulation.

In order to solve the problems of user account management and security protection in current group information system, this paper proposes a three-in-one AAA system of account, authentication and audit based on zero-trust architecture. Firstly, it describes the function of user management, authentication authorization, user audit and other modules of the AAA system. Secondly, in view of the conventional network boundary protection problem, the authentication authorization method based on zero trust architecture is applied to identify the business scenario, thus to ensure the reliability of the business system environment. Lastly, it illustrates the logic of the AAA subsystem and group-level system development platform configuration. The proposed AAA system can effectively improve the business security of group-level enterprise information system, compensate for the security issues of user login account under zero-trust environment, and further improve the security protection ability of network equipment, application equipment, system and application management in group-level enterprise.

During the operation of a trough solar power station, the stability of the outlet temperature of the thermal conductor is an important control objective for the safe and reliable operation of the power station. Due to the structural characteristics of the collector tube, the outlet temperature characteristics of the trough collector have large inertia and large delay, so the outlet temperature control problem is complicated. In order to solve this problem effectively, a dynamic mathematical model of MW trough solar power collector circuit is constructed in this paper, and a temperature control system is constructed at the collector outlet. A step prediction controller for the outlet temperature of trough solar power collector circuit is proposed. Simulation experiments were carried out based on MATLAB/Simulink platform. The simulation results show that, for the groove heat collecting loop, under the disturbance of irradiation, heat conduction oil inlet temperature and ambient temperature, the stepped predictive control system has shorter adjustment time, smaller overshoot, better robustness, and significantly improved control effect compared with the traditional PID control system. The proposed predictive controller can well cope with the situation of heat conduction oil overtemperature and heat conduction oil flow fluctuation at the outlet of heat collecting field, which is conducive to the safe and stable operation of the trough heat collecting field.

The pH values of boiler feed water, steam, boiler water and other measuring points in a chemical power plant were abnormally low, and the problem could not be effectively solved by adjusting the boiler water dosing process. In order to solve this problem and ensure the safe operation of the unit, this paper discusses and analyzes the influence of water sample temperature on pH electrode, Nernst temperature coefficient slope and solution temperature coefficient (ionic activity), and verifies through experiments that the abnormally low pH measurement value is caused by the large deviation of water sample temperature from 25 ℃, and the pH measurement method cannot provide correct temperature compensation. Strict control of water sample temperature, adoption of computational pH meter or selection of high-precision pH meter with precise non-linear temperature compensation function can effectively solve the problem of abnormally low pH measurement in the water and steam system.

Taking a 660 MW wall-tangentially fired boiler as the research object, the effects of air distribution ratio on the characteristics of in-furnace coal combustion and heat transfer processes and NO_x transformation were numerically investigated. Results show that under the fixed SOFA ratio, the increase of primary air ratio makes the overall boiler performance changes in V type that deteriorates evidently at first and then gets improved somewhat. The increased in primary air ratio leads to the generation of more fuel-NO_x at the initial combustion stage, which thus increases the final NO_x emission at the furnace exit. SOFA ratio does not change the variation trend of combustion performance along with the primary air ratio, but its increase leads to the decrease of the critical primary air ratio at which coal combustion performance deteriorates significantly. The variation of primary and secondary airflow momentums caused by the air distribution ratio is the main factor affecting the overall boiler performance, and coal combustion performance deteriorates significantly when their momentums are too close. Based on this, the large increase in the primary air ratio should be avoided during the practical boiler operation process. If it is inevitable, the SOFA ratio should be decreased to alleviate the deterioration of boiler performance caused by the increased primary air ratio.

The optimal scheduling of energy systems is important in ensuring the balance of energy supply and demand. Quantitative comparative studies of the development status, hot spots and trends in this field at home and abroad for more than 30 years, the research of energy systems optimal scheduling was analyzed in the CNKI and WoS databases from 1990—2022 by CiteSpace software. The results show that this field is in the conventional scientific stage but the literature has a high growth rate, the domestic literature growth rate is faster than the international and the inter-institutional exchange is close; the foreign hotspots are optimization algorithms, uncertainty and stability control for microgrids, dynamic scheduling with energy storage for integrated energy system (IES), as well as reinforcement learning and game theory for scheduling technique; the domestic hotspot trends are algorithms, dynamic optimization/bilayer optimization/time-sharing tariffs, multi-intelligent bodies, demand side management and deep learning for microgrids, as well as uncertainty, energy hubs, electricity to gas, integrated demand response, data driven, carbon trading, carbon capture and reinforcement learning for IES. The results show heuristic algorithms and deep learning techniques are expected to achieve a paradigm shift in future large-scale energy systems.

A novel hybrid design that combines solid waste plasma gasification, gas turbine, absorption heat pump, and coal-fired combined heat and power plant has been proposed. In the integrated scheme, medical waste is sent to the plasma gasifier and converted to syngas, which is conveyed into the gas turbine system after the necessary treatment. In terms of waste heat utilization of syngas and flue gas, some are used by the absorption heat pump for heating, and the rest are used to heat the feedwater of the coal-fired combined heat and power plant directly. Based on a typical coal-fired combined heat and power plant, the benefits of this system are examined in terms of both thermodynamics and economics. Once the heat supply and the net electricity from coal remain the same, the net power generated by the waste in the hybrid design is 7.47 MW, while the net waste-to-energy efficiency reaches 47.96%. In just 5.23 years, the initial investment in the proposed system is recouped, and in its 25-year lifetime, the system achieves a net present value of 50 362.94 thousand CNY.

Energy conservation and emission reduction work have attracted global attention. Accelerating lowcarbon transformation work has also reached a consensus in the shipping industry. Among them, hydrogen energy ships have good development prospects. In the face of the problem that hydrogen energy ships have no stable hydrogen source, it is urgent to find a stable hydrogen source for hydrogen energy ships. This paper introduces the development status of hydrogen production from offshore wind power and hydrogen energy ships, breaks the traditional concept of hydrogen energy, puts forward the system architecture of hydrogen production and hydrogenation on offshore platforms, and uses offshore wind power to directly prepare hydrogen, which provides a new idea for solving the hydrogen source problem of hydrogen energy ships and realizing the consumption of offshore wind power. Through the discussion and economic analysis of the integrated development of offshore wind power and marine ranching hydrogen energy ships, it is found that the integrated development of offshore wind power and marine ranching hydrogen energy ships is economically feasible, will contribute to carbon emission reduction work, and has good development prospects. This paper can serve as a reference for the comprehensive development of offshore wind power and hydrogen ships and put forward the prospect of building offshore hydrogen energy passage in coastal areas.

In the study, a computational fluid dynamics (CFD) model based on a 600 MW tangentially coal-fired boiler was established. According to orthogonal conditions (L₁₆(4⁵)), the heat flux distributions of the water-cooled wall under 100% BMCR, 75% THA, 50% THA and 35% BMCR loads were obtained. In addition, the factors also included: primary to secondary air rate, degree of air-staging, swing angles of burners and SOFA nozzles. Then, the spiral water-cooled wall temperature distributions under various conditions were calculated through coupling the heat absorption, temperature calculation and hydrodynamic characteristics of the water-cooled wall. Due to the discontinuity of orthogonal condition, the machine learning was used for predicting the spiral water-cooled wall temperature distribution within the range of parameters covered by orthogonal conditions. The results showed that a wall temperature peak up to 730 K would appear in the area among burner system. The heat transfer deterioration was easy to occur when the flame center height in furnace coincided with the phase change height of the working fluid during the boiler load adjusting process. The goodness of fit R² of the ensemble learning on the training set and the test set of the wall temperature data had reached 0.99, which could be used to predict the wall temperature of the boiler under wide load. At the same time, the machine learning established the mapping relationship between the wall temperature distribution and the operating parameters of the boiler. In the future study, the wall temperature safety of the water wall can be guaranteed by reasonably adjusting and optimizing the operating parameters through the optimization algorithm.