An improved particle swarm optimization algorithm for the optimization and group control of water-side free cooling using cooling towers

The application of cooling towers for free cooling is an effective energy saving method for cooling systems in data centers and industrial applications. This paper presented a cooling tower performance model suitable for on-line optimization and established an experimental system to verify the cooling tower model. Based on models of the system components, an improved particle swarm optimization algorithm was proposed to achieve optimization and group control of the water-side free cooling system. The simulation results showed that the fluctuations of the optimal energy consumption and outlet water temperature were 0.66% and 3.34% respectively, demonstrating improved stability and accuracy of the proposed algorithm compared with the conventional algorithm. The results revealed that the optimal outlet water temperature of the cooling tower varied minimally with the cooling load and was approximately linearly proportional to the outdoor wet bulb temperature. The optimal gas-water mass ratios were found to be inversely correlated to the wet-bulb temperature and cooling load. These results can provide a reference for the design and implementation of on-line optimization strategies for multi-components water-side free cooling systems.