Research on Energy Efficiency Enhancement Strategies for the Industrial Air-Water Cooling System Based on Multi-Objective Optimization

Amidst the intensifying global energy crisis and the stringent environmental regulations, the industrial airwater cooling system, as a critical and indispensable technology in the vast majority of industrial production, becomes particularly crucial for optimization and upgrading. In this study, the working principles and the current energy efficiency status of the existing industrial air-water cooling system are investigated, the main factors influencing the system efficiency are identified, and a multi-objective optimization model is constructed based on these findings. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used as the solution algorithm to solve the model and balance the overall system energy consumption, operating costs and environmental impact. Through experimental design and model validation, this paper proposes a series of optimized control strategies and equipment configurations. These strategies significantly improve the energy efficiency of the system, as shown by the experimental results. This research not only enriches the theoretical study of optimization strategies for the industrial air-water cooling system, but also provides a scientific basis for practical applications.