As a critical component of nuclear power units, the direct cooling water system plays a key role in overall performance. To maintain economic efficiency, it is necessary to adjust the circulating water flow rate as conditions change. Understanding how this system responds dynamically to varying environmental factors—such as seawater temperature and tidal levels—is essential for precise control. While previous studies have explored methods such as variable frequency control, predictive maintenance, and digital twin technologies to optimize system operations, challenges remain in addressing the dynamic response of cooling systems under complex environmental and operational conditions. In this study, the AP1000 was used as the research subject and a comprehensive mathematical model of each part of the cooling water system was built, accounting for delays in processes like pipeline transport. Sensitivity analyses were then carried out to examine how linear disturbances in environmental parameters affect system performance, and how circulating water flow, condenser back pressure, and unit efficiency are interrelated. At the same time, the frequency conversion circulating water pump adaptive adjustment system is used to find the best vacuum conditions according to the change in seawater parameters. The findings offer valuable guidance for enhancing the economic operation of nuclear power plant cooling systems.

Direct air-cooling systems use air instead of water as a cooling medium, so they are easily affected by meteorological and hydrological conditions. In this paper, considering the complex geographic conditions around the direct air-cooling units, Gambit is used to model the direct air-cooling system, including the complex mountainous terrain, and the performance simulation of the direct air-cooling system and the complex mountainous terrain near the power plant is realized by combining the CFD method with the MATLAB mathematical model of the power plant. Through the simulation, the operation of the ACC system under various meteorological conditions is obtained, and the influence of environmental factors and complex geographic conditions on the performance of the ACC system is investigated and further analyzed for the special case of the back-furnace wind. On this basis, a clustering analysis algorithm was used to obtain the results of turbine zoning in different wind directions and to analyze the physical field shifts of the units caused by geographic factors.