Ensuring renewable energy utilization with quality of service guarantee for energy-efficient data center operations

Soongeol Kwon

Applied Energy, 2020, vol. 276, issue C, No S0306261920309363

Abstract: The reduction of greenhouse emissions is becoming a major goal of energy-intensive industries, such as data centers, and there have been significant efforts to achieve sustainable operations by meeting electricity consumption using renewable energy generations. Specifically, it has been a common practice for data centers to use renewable energy via on-site solar power generation to directly offset electricity consumption by renewable energy to contribute to environmental sustainability. However, the introduction of intermittent and non-dispatchable renewable energy generations for powering data centers that generally host time-varying workloads presents a significant challenge, and thus, this study mainly focuses on how to improve renewable energy utilization for data center operations considering the integration of co-located solar power generation and battery energy storage. The main objective is to develop a mathematical optimization model for energy-efficient and sustainable data center operations to minimize energy cost while ensuring the desired level of renewable energy utilization and the required quality of service guarantee. In particular, this study proposes a two-stage stochastic program integrated with an expected-value constraint and a chance constraint, and an integer programming and sampling-based approach are adopted to solve the problem to investigate optimal data center operations. The comprehensive numerical experiments are conducted to evaluate the proposed model compared with benchmark models for various parameter settings, and the results show that the proposed model can be successfully implemented to enable data centers to achieve the desired renewable energy utilization while improving energy efficiency.

Keywords: Data centers; Renewable energy; Quality of service; Two-stage stochastic program; Chance constraint; Expected-value constraint (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (19)

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DOI: 10.1016/j.apenergy.2020.115424

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