Optimal power cost management using stored energy in data centers

By Rahul Urgaonkar, Bhuvan Urgaonkar, Michael J. Neely, Anand Sivasubramaniam. PERV, 2011

465 citations recorded by the source corpus.

Since the electricity bill of a data center constitutes a significant portion of its overall operational costs, reducing this has become important. We investigate cost reduction opportunities that arise by the use of uninterrupted power supply (UPS) units as energy storage devices. This represents a deviation from the usual use of these devices as mere transitional fail-over mechanisms between utility and captive sources such as diesel generators. We consider the problem of opportunistically using these devices to reduce the time average electric utility bill in a data center. Using the technique of Lyapunov optimization, we develop an online control algorithm that can optimally exploit these devices to minimize the time average cost. This algorithm operates without any knowledge of the statistics of the workload or electricity cost processes, making it attractive in the presence of workload and pricing uncertainties. An interesting feature of our algorithm is that its deviation from optimality reduces as the storage capacity is increased. Our work opens up a new area in data center power management.

Subfields: Computer Networks and Communications, Hardware and Architecture, Information Systems

View Paper: https://www.semanticscholar.org/paper/cc1e864c07668994d67efe8ce5723df3193cc8b5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Fanxin Kong
2. Xue Liu
3. Adam Wierman
4. Sandeep K. S. Gupta
5. Yonggang Wen
6. Miyuru Dayarathna

In Hardware and Architecture

1. Fanxin Kong
2. Xue Liu

In Information Systems

1. Fanxin Kong
2. Xue Liu
3. Adam Wierman
4. Yonggang Wen
5. Miyuru Dayarathna

Citations in the corpus

• Renewable and cooling aware workload management for sustainable data centers (2012, background): “Though there are more complex energy storage models [29], they are beyond the scope of the paper.”
• Ensuring Safety, Security, and Sustainability of Mission-Critical Cyber–Physical Systems (2012, background): “In this regard, a major challenge is to schedule workload being aware of the thermal and power availability characteristics of the data center to achieve low cost operation while meeting SLAs [25]–[27].”
• A Survey on Green-Energy-Aware Power Management for Datacenters (2014, background): “The electricity price in long-term market is usually smaller than the real-time , and thus the operator may reduce energy cost by such forward 2.3.2.”
• The Internet of Things, Fog and Cloud Continuum: Integration and Challenges (2018, unknown): “scale infrastructures, data centers in particular [67, 68, 69, 70].”
• Incentivizing Energy Trading for Interconnected Microgrids (2016, background): “Last, to incorporate the degradation of energy storage caused by charging and discharging, we introduce cs as the amortized cost of charging and discharging over the lifetime, and model the cost of energy storage operation [21] as”