Optimal energy source selection and capacity planning for green datacenters

Abstract

To reduce cost and emission, modern datacenter operators are beginning to incorporate green energy sources into datacenters' power supply. To improve service availability, they also back up datacenters using traditional (usually brown) energy sources. However, challenge arises due to distinct characteristics of energy sources used for different goals. How to select optimal energy sources and plan their capacity for datacenters to meet cost, emission and service availability requirement remains an open research problem. In this extended abstract, we briefly describe recent work in [4], which provides a holistic solution to address this problem. In [4], we present GreenPlanning, a framework to strike a judicious balance among multiple energy sources, the electrical grid and energy storage devices for a datacenter in terms of cost, emission, and service availability. GreenPlanning explores different features and operations of both green and traditional energy sources available to datacenters. The framework minimizes the lifetime total cost including both capital and operational cost for a datacenter. We conduct extensive experiments to evaluate GreenPlanning with real-life computational workload and meteorological data traces. Results demonstrate that GreenPlanning can reduce the lifetime total cost and emission by more than 50% compared to traditional configurations without integration of green energy, while still meeting service availability requirement.