摘要
随着云计算和大数据的快速发展,数据中心的能耗问题日益突出,其中空调系统占据了数据中心总能耗的30%~40%。传统温控方式依赖经验设定,难以有效应对动态负载变化,导致能源浪费。为此,文章提出一种基于人工智能(AI)的数据中心温控与空调节能优化方法。该方法融合深度学习与强化学习技术,实现了对空调系统的实时、智能调控。
With the rapid development of cloud computing and big data,the energy consumption of data centers has become increasingly prominent.The air conditioning system accounts for 30%to 40%of the total energy consumption in a data center.Traditional temperature control methods,which rely on empirical settings,struggle to effectively handle dynamic load changes,leading to energy waste.To address this,this article proposes an artificial intelligence(AI)-based method for optimizing temperature control and air conditioning energy efficiency in data centers.This method integrates deep learning and reinforcement learning technologies to achieve real-time and intelligent control of the air conditioning system.
作者
叶俊青
YE Junqing(Gongcheng Management Consulting Co.,Ltd.,Guangzhou 510610,China)
关键词
数据中心
空调节能
人工智能优化
温控系统
强化学习
data center
air conditioning energy-saving
AI optimization
temperature control system
reinforcement learning
