Matching geographically distributed micro-datacenters’ energy consumption with renewable energy

Abstract

The enormous and growing demand of datacenters are consuming more energy than ever. Energy consumption of datacenters has become a significant issue. High energy consumption not only results in high carbon emission, but also experiences large electricity costs. For this reason, IT carbon footprints are th reason of 2 percent of global greenhouse gas (GHG) emissions. Recent research works suggest geographical load-shifting for reducing carbon emission as well as energy cost. This research work focuses on integrating renewable energy sources in small-scale micro-datacenters by considering load-shifting strategy. Our work specifically explores and analyses geographical load-shifting to encourage use of renewable energy instead of brown energy. We make two contributions. First, we explore systematic approaches for finding the best combination of solar panel angles to ensure more solar energy production during a day. Second, a distributed micro-datacenter scenario is conducted in Amazon cloud infrastructure to track energy consumption behaviour by considering real-weather updates. The aim of our work is to explore possibilities of integrating renewable sources to replace dependency on brown energy while maintaining Quality of Services (QoS).