With the increasing depth of metal mining, thermal damage has become a serious problem that restricts mining. The thermal management system of refrigeration and ventilation is an indispensable technology in the mining of deep metal mines, which plays a key role in improving the thermal and humid environment of mines. Optimizing the performance of refrigeration and ventilation systems to reduce energy consumption has become a focus of researchers’ attention. Based on the heat current method, this research establishes the overall heat transfer and flow constraint model of the refrigeration and ventilation system, and proposes an iterative algorithm that combines the refrigerator energy consumption model and the artificial neural network model of heat exchangers. The Lagrange multiplier method is used to optimize the system with the goal of minimizing the total power consumption of the system. The results show that under 9.1 kW cooling load conditions, the total energy consumption of the system reduces by 16.5%, and the COP of the refrigerator increases by 11.6%. The optimization results provide significant guidance for the production and energy consumption reduction of the deep metal mines.

Significant harm from heat has become a key restriction for deep metal mining with increasing mining depth. This paper proposes a refrigeration ventilation system for deep metal mines combined with an existing air cycling system and builds an experimental platform with six stope simulation boxes. Using the heat current method and the driving-resistance balance relationship, the heat transfer and flow constraints of the system were constructed. An artificial neural network was used to establish models of heat exchangers and refrigerators with historical experimental data. Combining the models of the system and stope simulation box, an algorithm that iterates the water outlet temperature of the evaporator and condenser of the refrigerator was proposed to design the coupled simulation model. The heat balance analysis and comparison of the air outlet temperatures of the stope, as well as the heat transfer rates of the heat exchangers with the experimental data, validated the coupled simulation model. Additionally, the effects of cooling fans and the air inlet temperature of the cooling tower were discussed, which provided a powerful modelling method for the coupled model of a refrigeration ventilation system, helps to reduce energy consumption, and improves the sustainability of mining production.