Cooling control based on model predictive control using temperature information of IT equipment for modular data center utilizing fresh-air

Abstract

A cooling control method based on a model predictive control (MPC) for a modular datacenter utilizing the fresh-air is proposed. The proposed method reduces the total energy consumption of information technology (IT) equipment and cooling facilities in the data center, while considering a relationship between energy-savings and the temperature information of IT equipment. This method based on MPC controls the central processing unit (CPU) temperature in servers by facility fans for cooling. To design the proposed method, it is developed a prediction model that represents the CPU temperature by the revolution speed of facility fans, the fresh-air temperature, utilization of servers, and other factors. Furthermore, the proposed control method is applied to the actual modular data center. The energy consumption of the proposed method is compared with that of a traditional method, which has controlled the temperature difference between the inlet and outlet of the server racks based on proportional integral (PI) control. Actual comparison experiments with traditional method are provided to validate effectiveness of the proposed method. The results show that the proposed method realizes energy-savings of more than 20% compared to the traditional control method in the actual modular datacenter.