A Power Load Distribution Algorithm to Optimize Data Center Electrical Flow

作者：Ferreira Joao^*; Callou Gustavo; Maciel Paulo

来源：Energies, 2013, 6(7): 3422-3443.

DOI：10.3390/en6073422

• ASTRO/Mercury
• energy flow model
• dependability
• sustainability
• data center power architectures
• power load distribution algorithm
• optimization

Energy consumption is a matter of common concern in the world today. Research demonstrates that as a consequence of the constantly evolving and expanding field of information technology, data centers are now major consumers of electrical energy. Such high electrical energy consumption emphasizes the issues of sustainability and cost. Against this background, the present paper proposes a power load distribution algorithm (PLDA) to optimize energy distribution of data center power infrastructures. The PLDA, which is based on the Ford-Fulkerson algorithm, is supported by an environment called ASTRO, capable of performing the integrated evaluation of dependability, cost and sustainability. More specifically, the PLDA optimizes the flow distribution of the energy flow model (EFM). EFMs are responsible for estimating sustainability and cost issues of data center infrastructures without crossing the restrictions of the power capacity that each device can provide (power system) or extract (cooling system). Additionally, a case study is presented that analyzed seven data center power architectures. Significant results were observed, achieving a reduction in power consumption of up to 15.5%.

• 出版日期2013-7