Energy Efficiency and Green Computing in Large-scale Data Centers

With the development of energy efficiency measurement methods, the target demand for energy utilization in data centers is constantly improving, and the study of green energy efficiency (EE) factors in large-scale data centers based on DEA (Data envelopment analysis) is becoming increasingly important. In the construction of the entire EE factor analysis model, how to improve the green energy efficiency of the improved model and improve the efficiency of system power usage is currently a key issue that needs to be urgently solved. This article used traditional research methods on factors affecting green energy efficiency, analyzed the hierarchical composition of EE in large-scale data centers (DC), and calculated the four major energy efficiency indicators in DC. Based on the data results, the following conclusions were drawn through discussion. Through simulation experiments, six data center samples from different regions were selected, and the DEA based green energy efficiency factor analysis model was applied. Compared with traditional schemes, the green energy utilization rate has increased, with a comprehensive average improvement of 11.1%. At the same time, the power utilization efficiency has also improved, with a comprehensive average decrease of about 7.7%. This indicates that the large-scale data center green energy efficiency factor analysis model based on DEA has good results in practical applications. This study provides strong guidance and reference for the sustainable development of future data centers, and innovative solutions to address the growing digital demand and environmental challenges.