Energy optimization management strategies for data centers assisted by AI

With the rapid development of global carbon neutrality and the digital economy, the energy consumption issue of data centers, as the infrastructure of computing power, has become prominent. However, the traditional energy management model is difficult to dynamically regulate in accordance with business conditions and environmental situations. This article focuses on the application of relevant technologies of artificial intelligence (AI) in the energy optimization management of data centers, analyzes the problems of increased energy consumption and management drawbacks, and points out that the key to solving the high energy consumption problems lie in leveraging AI. The following specifically introduces the current development status of AI in the optimization of data center cooling systems, server load scheduling, integration of renewable energy, and detection of abnormal energy consumption, as well as the different levels of development in various regions. Then, it elaborates on the data quality issues, algorithm adaptation issues, cost and security issues, and talent issues it encounters when empowered by AI, and proposes four solutions and implementation processes, including establishing an integrated data governance system of "source-edge-cloud". Based on multiple cases that the author has verified, the feasibility of AI-assisted energy optimization in data centers is illustrated. Through the judgment of the current development and trend, its role in achieving the "dual carbon" goals and the sustainable development of the digital economy is pointed out.