Chiller Operation Performance Optimization Method Based On Association Rule Algorithm

Abstract

As the core component in industrial production, the chiller is composed of compressor, condenser, evaporation tower and other components. There are problems such as poor coordination and low heat dissipation efficiency between various components in the chiller, and a coordination method is needed to control them. Based on this, this paper proposes an association rule algorithm to optimize the operation performance of the chiller, and calculate the temperature difference between the compressor, condenser and evaporation tower. Then, the material and structure of the components are integrated to control the power, water volume, and fan to maximize the heat dissipation effect of the chiller. At the same time, the chiller is comprehensively constrained to reduce the heat decay during operation, control the operating energy consumption, and achieve the optimization of the target value. The results show that under the rated load, the association rule algorithm can increase the chiller's heat dissipation rate by 15% and reduce energy consumption by 10%, significantly outperforming traditional genetic algorithms and whale optimization algorithms. Additionally, the temperature difference between the compressor and other components is less than 2°C. Under the constraint conditions, the correlation rule algorithm can reduce the thermal decay rate of compressor and condenser by 25%, save the operating cost of chiller by 25%, and make the response time of hot start less than 1.5s and the standby power decrease by 12%, which is better than the previous algorithm. Therefore, the association rule algorithm can improve the chiller's operation performance.