Optimizing a dew point evaporative cooler in data center applications

Abstract

Abstract The escalating energy consumption of data centers has led to a pressing need for energy-efficient cooling solutions. This paper presents a countercurrent dew point evaporative cooler (DPEC) for data center refrigeration. We developed and experimentally validated a numerical model for DPEC, then formulated regression models using the response surface method. These models link eight key design factors, including geometrical and operational factors, to three performance indices: cooling capacity per unit volume, coefficient of performance, and outlet primary air temperature. We assessed the extent of factor influence on these indices. By using these regression models as objective functions, we used the genetic algorithm for design optimization under two climatic conditions, resulting in various optimal parameter combinations. Our findings highlight the strong predictive accuracy of these models. In comparison to the original design, the optimal design achieved an improvement of 104.8%, an increase of 23.9%, and a reduction of 13.8% in the three indices.