Energy Saving Optimisation of Data Centre Cooling System Based on CSSA

Data centers are becoming increasingly important in today's world due to the quick advancement of information technology. Large-scale data transmission, processing, and storage result in enormous energy consumption in data centers. Inefficient cooling equipment operation is a significant contributing reason to these data centers' excessive energy consumption. This research presents a Chaotic Sparrow Search Algorithm (CSSA)-based energy-saving optimization technique for data center cooling systems. Using the cooling system of a data center in Shanghai as an example, we establish the cooling system optimization model in accordance with the limitations of the equipment operating conditions, use the lowest energy consumption of the cooling system as the objective function, and use the chilled water supply and return water temperature, water pump flow rate, etc. as the decision variables. According to the testing results, the cooling system may minimize energy consumption by 5.99 % in precooling mixing mode, 13.39 % in natural cold source mode, and 16.79 % in chiller cold source mode after using CSSA optimization. As a result, the plan this article suggests is crucial for lowering emissions and energy consumption in data centers.